Clearly, this year's Duke team is neither entitled nor even favored to win the National Championship. The widely respected human opinion polls put, at time of writing, half a dozen teams above a Duke team that has failed to receive a single first-place vote this entire season. Clearly, something scatters the blue sunshine. There are many common memes surrounding Duke, though only a few of them actually apply to this years' team. Let's take a look at some of the common criticisms levied against this year's Duke squad, analyzed from a tempo-free perspective (statistics, as always, from Ken Pomeroy).
1) Duke has played a soft schedule. If we go based on the tempo-free stats, nothing could be further from the truth. Pomeroy ranks Duke's schedule second in the nation, behind West Virginia. Sure, their non-conference schedule is ranked 83rd, but take a look at the teams on top of the non-conference SOS rankings: other than Butler, none of the top 20 have a prayer at an at-large tournament bid. And a number of the teams up top are probably there because they played Duke... this criticism is tired and should be sent to the land of misfit memes.
Making the argument worse is the observation that not only does Duke have the #3 offense in raw efficiency (1.17 points/possession), they have accomplished such lofty efficiency against a harder slate of defenses than anyone in the nation (adjusted efficiency of defenses Duke has played: 0.95 points/possession).
Taken more subjectively, Duke will play 15 non-conference games this regular season (counting Thursday's game against Tulsa). Of these, as many as 7 teams could make the NCAA tournament; what is a better preparation for NCAA tournament play than contests against teams that will actually be there? For comparison, Duke is #2 in the Sagarin strength of schedule as well, and played the fifth-toughest slate in this version of RPI.
2) Lack of backcourt depth. It seems only yesterday that the meme was about the lack of frontcourt depth (well, last year anyway). Assuming that Kyle Singler counts as a guard, Duke's main men play a ton of minutes, while backup shooting guard Andre Dawkins has struggled in limited minutes. I have a problem with this criticism on a number of levels. Part of this argument comes from the same area as the Duke Fade, which is that too many minutes are given to the Big Three. Here's the tempo-free stats.
Player......%Minutes........ORtg....%Possessions
Scheyer.........91.6.............130.7.........23.1
Singler.........89.5............114.3.........23.1
Smith.........82.2.............117.5.........23.1
First of all, pretty cool that all three are used in the same percentage of possessions. Second, if you have three players capable of contributing those massive tempo-free player ratings, why would it be a bad thing to play them all the time? If a player was used so much that they tired in-game, his offensive rating would plummet, due to the extended number of possessions played. Duke's top three men (by % minutes played) have a higher combined rating (362.5) than the top three men on Kansas (358.5), Syracuse (333.4), Purdue (343.1), West Virginia (354.4) and Kentucky (334.5), to pick a few. Scheyer/Singler/Smith are doing it in far more minutes than any of those teams, save perhaps WV, who do get 80%+ minutes from Butler and Jones.
For another avenue of argument, I shall paraphrase what I overheard this morning on 99.9 The Fan in Raleigh: "While Duke has the best trio of players in the country, what happens when they are all shut down?" This, of course, has an easy answer: Duke would lose. The better question is: "what's the likelihood of all three being shut down?" The three Duke stars average a combined 53.8 points/game; the fewest they've scored, combined, was 41 in the Preseason NIT championship win over UConn. In Duke's four losses, the trio has averaged about the same amount, and scored a combined 61 points in the loss at Georgetown. Indeed, it seems that Duke's wins will come down to how many points they can drag out of their frontcourt. Which leads to...
3) Duke has no talent in the frontcourt. I should hope that the last three games would silent anyone who would make such a bold claim. There is clearly some talent in the frontcourt, and that is in the (massive) form of Brian Zoubek. The man who makes girls swoon so hard that their marriage proposal signs are upside down has averaged nearly a double-double (9.7 points, 12.7 rebounds) in those games. With his new-found ability to avoid foul trouble, Zoubek has slipped back above the 40% minutes played mark. This finds him back atop the nation in offensive rebounding. Let's nail that home for the readers too lazy to click on the link:
Category: Percentage of a team's missed shots rebounded by a player while he's on the court.
Qualification: 40% of a team's minutes played (that's about 16 min/game, ignoring OTs)
1. Brian Zoubek, Duke 23.0%
2. Demarcus Cousins, Kentucky, 22.8%
3. Anthony Johnson, Fairfield, 17.4%
So, other than the stud freshman at Kentucky, no one is even close to Brian Zoubek in offensive rebounding ability. Against Maryland, Zoubek used missed shots by the Big Three to have an amazing offensive night, scoring 16 points with 17 rebounds (8 OR). Then, against Virginia Tech, Zoubek benefited from Duke's cold shooting for another 16 rebounds (8 OR). This time he tended to kick the ball out to open men, including two assists on Nolan Smith three-pointers.
The tempo-free world is only six years old, but in that time, only three players have had an OR% above 21%: DeJuan Blair was at 23.6% last year. (The next highest season total is 20.8%).
Of course, there's more to the frontcourt than Zoubek, and the tempo-free stats have mixed feelings about Duke's other big men. Miles Plumlee is a very strong defensive rebounder, and at 22.6% is currently vying for Duke's best defensive rebounding mark since Pomeroy started tracking individual stats in 2005 (Shelden Williams' best was 22.0%). Mason Plumlee currently has the lowest offensive rating on the team (94.5), thanks to a triple-whammy of low effective field goal percentage, small rebounding numbers, and a very high turnover rate. While analysts have been high on Mason's potential, the tempo-free stats haven't shown that this season.
Lance Thomas is generally seen as the "glue" of the 2009-2010 Duke team, and the captain is certainly one of the emotional leaders. As with many in this position, his contributions are said to be "intangible." Indeed, tempo-free statistics don't have much to say about LT. He has an average offensive rating, and the only stat which really stands out is his turnover rate, which is the highest on the team: Duke turns the ball over on 26.1% of his possessions. This could be partially due to Lance, who turns the ball over 1.6 times/game; it could also be unlucky that he's on the court when turnovers occur. Don't view this as a total knock on Thomas, however. These stats of course only include offense, and while Thomas' contribution may not be exactly "intangible" it is certainly "unmeasured" by this system.
Overall, this criticism is still hanging on by a few threads. Clearly, Duke's frontcourt is responsible for a massive number of rebounds, so much so that it can prop up a poor shooting night against many teams. Whether one of the Plumlees or Zoubek can be a viable offensive threat remains to be seen. For now, only Zoubek is impressive from the tempo-free perspective.
For the heck of it, let's throw in:
4) Duke gets all the calls. While pretty hilarious in most seasons, this conspiracy theory has a pretty steep piece of evidence to overcome this year: this season, Duke has a free throw rate (FTA/FGA) of 37.8, which is 171st in the nation, good for almost exactly median. In addition, Duke gets only 21.9% of their points from the charity stripe, good for 119th in the nation. This season, the refs seem to have been paid off by the fans of Kansas State (Free Throw Rate: 53.3) and Wyoming (27% of points from FTs). What Duke does have going for them, however, is free throw percentage: 8th in the nation at 75.9%.
So, what are Duke's real weaknesses, as shown by tempo-free stats?
1) Fouls. As alluded above, Duke struggles more than usual to get to the free throw line, and so cannot benefit as much from their high percentages from the line. While in most years, Duke has multiple players drawing more than 5 fouls per 40 minutes, only Scheyer is above that mark, and no one else is very close.
On the other side of the basketball, committing fouls has been a huge problem, particularly for Brian Zoubek (8.2 Fouls Committed/40 minutes) and Mason Plumlee (7.2 FC/40). In all three of Duke's January losses, they allowed their opponents to get to the free throw line at a rate of about 50 FTA/FGA.
2) Slow Pace On each team's "Game Plan" page, Pomeroy has tables of correlation coefficients. Each of these is a measure of how correlated a particular statistic is with offensive/defensive efficiency. At the moment for Duke, one of these, on offense, is the "pace" of the game, measured by the number of possessions. As Duke's number of possessions goes up, so does their offensive efficiency. For example, Duke's fastest game this season was against Pennsylvania, in which Duke scored 115 points in 75 possessions (Offensive Efficiency: 151.8!) . In Duke's slowest game, at Clemson, the Blue Devils scored just 60 points in 61 possessions, for an efficiency of 98.8. This will definitely be a trend to keep an eye on, should Duke face a team notorious for slow play in March (looking at you, Big Ten).
3) Allowing 2-pointers Duke's defense is ranked 18th in efficiency, but it has it's definite weaknesses. While the Blue Devils are second in the nation in 3-point shooting percentage against (27.4%), they allow opponents to shoot over 45% inside the arc (81st). Put another way, Duke's opponents score 60.8% of their points from 2-point range, which is the 8th most in the nation (to be fair, the 18.4% of opponent's points from beyond the arc is fourth lowest). Duke's strategy clearly makes some sense: it doesn't take a math degree to deduce that 3 > 2. However, some teams are just not built for chucking up treys. This season, Georgetown, NC State, and Wisconsin all used Duke's spread defense to their advantage, scoring backdoor layups and short-range jumpshots.
As the rankings sit today, Duke is the best team in the nation, measured from a tempo-free perspective. They have the best offense, a good defense, and have played a very strong schedule. We've seen that many of the common criticisms of Duke fall apart when seen from the perspective of tempo-free stats. Still, this is a college basketball world without perfection, and while Pomeroy's statistics can help us see that Duke is a little underrated by the human polls, there is still room for improvement as March looms.
Monday, February 22, 2010
Wednesday, February 17, 2010
The Duke Fade: A Response
Earlier today, Alex Fanaroff of Duke's daily newspaper The Chronicle posted a wonderful article, "Duke Does Decline, Objectively Speaking." It's a refreshing look at basketball in a way that we love here at the Immaculate Inning: using tempo-free statistics. Fanaroff describes the general issue:
1) Duke fades down the stretch.
2) This is due to the starters playing way too many minutes, causing them to get tired.
Fanaroff went into the article expecting to at least debunk #1 as a myth, but ended up finding a strong correlation between Duke's efficiency margin (Offensive Efficiency - Defensive Efficiency), and the number of ACC games played. This suggested that over the last seven years, the data indeed does suggest a Duke Fade. Fanaroff was unable, however, to show that "minutes by starters" had any effect on efficiency margin. Naturally, I was intrigued, and wanted to dial further into the data. Here are a number of issues:
1) Year effects do matter. In his accompanying blog post, Faranoff says "Predictably, most seasons failed to produce robust trends due to the limited sample size, though all seasons from 2004-2009 demonstrated a downward trend." This statement is misleading on two accounts. First of all, here is each year plotted individually, with the linear regression line on each:
True, there is a downward trend most years, and Faranoff does mention that Duke's trend is technically upwards this season. Most seasons, that line is not significant: there is not enough evidence to say that the regression line differs from no slope.
However, the null hypothesis can be rejected in 2004 (r-squared 0.2177, p = 0.04406) and 2008 (r-squared 0.2993, p = 0.01879). Here's my question: if a declining efficiency margin during ACC play is a bad thing, then why did the 2004 team make the Final Four, despite having one of of the few significant in-year declines?
2) Opponents matter. As many folks over at the fine institution of DBR have pointed out, Duke always plays Carolina as its last ACC regular season game. Then, while the early rounds of the ACC tourney may provide a brief dip in competition, Duke almost always advances to the end of the tournament, and they naturally find better teams there. We can look at the effect of Opponent Rank (determined by Pomeroy) on Efficiency:
The scatterplot doesn't look like much, but the trend line is there, and it is significant: Duke's opponents get tougher as the season goes on. And Duke does play much better against inferior competition:
Since Duke's opponents are harder later in the season, and Duke has lower efficiency margins against better opponents, how can we take this into effect? One way is with an Analysis of Variance (ANOVA: more info here), in which we can specify variance components. Basically, we have two main effects on efficiency margin: ACC Game # and Opponent Rank. If we account for the variance accounted for by the strength of the opponent, is the correlation still significant? For the stat-geeks out there, here's the ANOVA table:
Anova Table (Type III tests)
Response: Delta.100
......Sum Sq....... Df........ F value........ Pr(>F)
(Intercept) 0.12776 ....1 ........6.0593 ..........0.015267 *
Opp.Rank 0.48675 ..1...... 23.0858 .........4.563e-06 ***
Game 0.19808 .....1 ........9.3947 ...........0.002693 **
Residuals 2.50903 ....119
To summarize, there is still an overall significant downward trend in efficiency margin as the season progresses, although the significance is reduced.
3) Home Court Matters? When Ken Pomeroy adjusts for home court, he adds 1.4% to the home team's offensive efficiency and visiting team's defensive efficiency, and subtracts the same from the home team's DE and visiting team's OE. So the difference between Faranoff's raw data and what Pomeroy would consider "adjusted" is -2.8 for Duke's home games and +2.8 for Duke's away games. What happens to the correlation if we make the "Pomeroy Adjustment"?
The correlation coefficient decreases, as does the significance, but not to the point where the slope becomes non-significant. There is still a Duke Fade when we account for home and away games.
I must say I come away unimpressed with other explanations for the Duke Fade. Opponents do get tougher but not enough to overcome the efficiency drop. Adjusting for home and away games also doesn't have much of an effect. It is very important to note that nowhere have I suggested a causal agent for the Duke Fade. This is to avoid the common fallacy that correlation implies causation. Clearly, Duke can still have an historic season (2004) despite having one of the few significant in-year Duke Fades.
Instead, I'll take an "I Report, You Decide" kind of approach here. These are the statistical facts, and I'll be happy to attempt more rigorous investigations if they are suggested in the comments.
1) Duke fades down the stretch.
2) This is due to the starters playing way too many minutes, causing them to get tired.
Fanaroff went into the article expecting to at least debunk #1 as a myth, but ended up finding a strong correlation between Duke's efficiency margin (Offensive Efficiency - Defensive Efficiency), and the number of ACC games played. This suggested that over the last seven years, the data indeed does suggest a Duke Fade. Fanaroff was unable, however, to show that "minutes by starters" had any effect on efficiency margin. Naturally, I was intrigued, and wanted to dial further into the data. Here are a number of issues:
1) Year effects do matter. In his accompanying blog post, Faranoff says "Predictably, most seasons failed to produce robust trends due to the limited sample size, though all seasons from 2004-2009 demonstrated a downward trend." This statement is misleading on two accounts. First of all, here is each year plotted individually, with the linear regression line on each:
True, there is a downward trend most years, and Faranoff does mention that Duke's trend is technically upwards this season. Most seasons, that line is not significant: there is not enough evidence to say that the regression line differs from no slope.However, the null hypothesis can be rejected in 2004 (r-squared 0.2177, p = 0.04406) and 2008 (r-squared 0.2993, p = 0.01879). Here's my question: if a declining efficiency margin during ACC play is a bad thing, then why did the 2004 team make the Final Four, despite having one of of the few significant in-year declines?
2) Opponents matter. As many folks over at the fine institution of DBR have pointed out, Duke always plays Carolina as its last ACC regular season game. Then, while the early rounds of the ACC tourney may provide a brief dip in competition, Duke almost always advances to the end of the tournament, and they naturally find better teams there. We can look at the effect of Opponent Rank (determined by Pomeroy) on Efficiency:
The scatterplot doesn't look like much, but the trend line is there, and it is significant: Duke's opponents get tougher as the season goes on. And Duke does play much better against inferior competition:
Since Duke's opponents are harder later in the season, and Duke has lower efficiency margins against better opponents, how can we take this into effect? One way is with an Analysis of Variance (ANOVA: more info here), in which we can specify variance components. Basically, we have two main effects on efficiency margin: ACC Game # and Opponent Rank. If we account for the variance accounted for by the strength of the opponent, is the correlation still significant? For the stat-geeks out there, here's the ANOVA table:
Anova Table (Type III tests)
Response: Delta.100
......Sum Sq....... Df........ F value........ Pr(>F)
(Intercept) 0.12776 ....1 ........6.0593 ..........0.015267 *
Opp.Rank 0.48675 ..1...... 23.0858 .........4.563e-06 ***
Game 0.19808 .....1 ........9.3947 ...........0.002693 **
Residuals 2.50903 ....119
To summarize, there is still an overall significant downward trend in efficiency margin as the season progresses, although the significance is reduced.
3) Home Court Matters? When Ken Pomeroy adjusts for home court, he adds 1.4% to the home team's offensive efficiency and visiting team's defensive efficiency, and subtracts the same from the home team's DE and visiting team's OE. So the difference between Faranoff's raw data and what Pomeroy would consider "adjusted" is -2.8 for Duke's home games and +2.8 for Duke's away games. What happens to the correlation if we make the "Pomeroy Adjustment"?
The correlation coefficient decreases, as does the significance, but not to the point where the slope becomes non-significant. There is still a Duke Fade when we account for home and away games.
I must say I come away unimpressed with other explanations for the Duke Fade. Opponents do get tougher but not enough to overcome the efficiency drop. Adjusting for home and away games also doesn't have much of an effect. It is very important to note that nowhere have I suggested a causal agent for the Duke Fade. This is to avoid the common fallacy that correlation implies causation. Clearly, Duke can still have an historic season (2004) despite having one of the few significant in-year Duke Fades.
Instead, I'll take an "I Report, You Decide" kind of approach here. These are the statistical facts, and I'll be happy to attempt more rigorous investigations if they are suggested in the comments.
Labels:
Duke,
Duke Fade,
Pomeroy Stats,
Tempo-Free Stats
Saturday, January 30, 2010
Duke-Georgetown Tempo-Free Preview
Seven inches of powdery white stuff has fallen from the sky this morning, which means it's a perfect time to stay home and analyze basketball statistics. From a tempo-free standpoint, today's game between Duke and Georgetown is an elite matchup. The Hoyas are ranked 15th in the nation by Pomeroy, but have an adjusted offense (19th) and an adjusted defense (32nd) ranking below their overall level. The reason for this is that most teams around their level in the Pomeroy rankings have one excellent score and one mediocre score (e.g. Villanova: 3rd on offense, 71st on defense).
Georgetown's strength of schedule also boosts their Pomeroy ranking. The Hoyas are coming off a blow out loss at Syracuse (3rd Pomeroy), and overall they rate as the 4th toughest schedule in the nation, and have played against the second toughest slate of defenses of all the division 1 teams. While this means that G-Town is battle tested, it also means that their raw offensive and defensive scores are much lower: they have averaged 108.7 points/100 possessions (58th) while giving up 93.1 points/100 possessions (46th). Part of the low offensive output has come while on the road against good teams-- they failed to crack the 1.0 points/possession mark at both Syracaue and Villanova.
Duke, meanwhile, is a well-kept tempo free secret this year. For whatever reason, Duke always seems to be near the top of the Pomeroy rankings in January and February, and this season is no different. Duke currently sits behind only top-ranked Kansas overall, and the Blue Devils continue to have the best adjusted offense in the country. In fact, it has only been in the past week (since the loss at NC State) that Duke has not also had the highest raw offensive efficiency as well (and are still in the top five). Clearly those numbers were going to come down with ACC play, but like Gerogetown, Duke is playing against some pretty tough defenses (6th toughest defense against).
It's hard to put a finger on what exactly is making Duke's offense so good. Pomeroy lists the "four factors" he believes are most critical to consistent play, regardless of the game's pace. Duke is a top 20 team in two of these factors: turnover rate (16.8% of possessions, 14th) and offensive rebounding percentage (40.1% of missed shots rebounded, 15th). Less impressive is the effective field goal percentage (52.9%, 41st) and FTA/FGA (36.4%, 202nd). Clearly the Duke alums have not been paying the refs off enough this year, because they are not getting to the free throw line very often at all. On the bright side, Duke's 77.0% FT% is fourth in the nation.
This is a game that will be won underneath the baskets. The first issue is Duke's shooting ability: while Duke has their characteristic 3-point shooting ability, they have struggled at times shooting from close range, and rank 79th with just 50.6% from inside the arc. Georgetown, meanwhile, struggles to keep opponents' percentages down. Because this game is being played at the Verizon Center, Duke can be expected to miss their fair share of shots. This shifts the focus to a battle between an elite offensive rebounding unit (Duke) and an elite defensive rebounding unit (Georgetown). For Duke's big men, the goal should be to grab that rebound and then go up strong through the usually foul-conscious Greg Monroe. But if the Hoya sophomore can handle Zoubek and the Plumlees, it could be a long afternoon for Duke.
In the rare event that Duke has a lights-out shooting performance on the road, the final tally could get quite high-scoring. One of the things Georgetown does do well is shoot the ball, with a 55.4% eFG% (12th). However, they are not very skilled at the other four factors (offensive rebounding, limiting turnovers, and getting to the free throw line). It's a strange game to predict because if the game were played at Cameron, one could see Duke making their shots and limiting their opponent's strength on the defensive glass, while the Blue Devils dominate their own defensive glass after limiting Georgetown's shooting ability.
But the game is being played in DC's downtown Chinatown, which adds expectation to Georgetown's shooting ability and detracts from Duke's. That's bad news as Georgetown has four players (Freeman, Vaughn, Wright and Clark) who put up eFG% north of 55. A cold shooting night from Duke and road defense as dismal as shown at NC State, and Duke looks to fall in a big way. However, more recent games have shown Duke's defense to be back on solid ground, and so if Georgetown's shooters are cooled, then look for a fight to the finish.
Prediction: Mason Plumlee and Brian Zoubek, combined, have about as much playing time (86.7% minutes played combined) as Greg Monroe (84.7%). Whoever has the most rebounds (MP2 + Zoo vs Monroe) will be on the victorious team.
Georgetown's strength of schedule also boosts their Pomeroy ranking. The Hoyas are coming off a blow out loss at Syracuse (3rd Pomeroy), and overall they rate as the 4th toughest schedule in the nation, and have played against the second toughest slate of defenses of all the division 1 teams. While this means that G-Town is battle tested, it also means that their raw offensive and defensive scores are much lower: they have averaged 108.7 points/100 possessions (58th) while giving up 93.1 points/100 possessions (46th). Part of the low offensive output has come while on the road against good teams-- they failed to crack the 1.0 points/possession mark at both Syracaue and Villanova.
Duke, meanwhile, is a well-kept tempo free secret this year. For whatever reason, Duke always seems to be near the top of the Pomeroy rankings in January and February, and this season is no different. Duke currently sits behind only top-ranked Kansas overall, and the Blue Devils continue to have the best adjusted offense in the country. In fact, it has only been in the past week (since the loss at NC State) that Duke has not also had the highest raw offensive efficiency as well (and are still in the top five). Clearly those numbers were going to come down with ACC play, but like Gerogetown, Duke is playing against some pretty tough defenses (6th toughest defense against).
It's hard to put a finger on what exactly is making Duke's offense so good. Pomeroy lists the "four factors" he believes are most critical to consistent play, regardless of the game's pace. Duke is a top 20 team in two of these factors: turnover rate (16.8% of possessions, 14th) and offensive rebounding percentage (40.1% of missed shots rebounded, 15th). Less impressive is the effective field goal percentage (52.9%, 41st) and FTA/FGA (36.4%, 202nd). Clearly the Duke alums have not been paying the refs off enough this year, because they are not getting to the free throw line very often at all. On the bright side, Duke's 77.0% FT% is fourth in the nation.
This is a game that will be won underneath the baskets. The first issue is Duke's shooting ability: while Duke has their characteristic 3-point shooting ability, they have struggled at times shooting from close range, and rank 79th with just 50.6% from inside the arc. Georgetown, meanwhile, struggles to keep opponents' percentages down. Because this game is being played at the Verizon Center, Duke can be expected to miss their fair share of shots. This shifts the focus to a battle between an elite offensive rebounding unit (Duke) and an elite defensive rebounding unit (Georgetown). For Duke's big men, the goal should be to grab that rebound and then go up strong through the usually foul-conscious Greg Monroe. But if the Hoya sophomore can handle Zoubek and the Plumlees, it could be a long afternoon for Duke.
In the rare event that Duke has a lights-out shooting performance on the road, the final tally could get quite high-scoring. One of the things Georgetown does do well is shoot the ball, with a 55.4% eFG% (12th). However, they are not very skilled at the other four factors (offensive rebounding, limiting turnovers, and getting to the free throw line). It's a strange game to predict because if the game were played at Cameron, one could see Duke making their shots and limiting their opponent's strength on the defensive glass, while the Blue Devils dominate their own defensive glass after limiting Georgetown's shooting ability.
But the game is being played in DC's downtown Chinatown, which adds expectation to Georgetown's shooting ability and detracts from Duke's. That's bad news as Georgetown has four players (Freeman, Vaughn, Wright and Clark) who put up eFG% north of 55. A cold shooting night from Duke and road defense as dismal as shown at NC State, and Duke looks to fall in a big way. However, more recent games have shown Duke's defense to be back on solid ground, and so if Georgetown's shooters are cooled, then look for a fight to the finish.
Prediction: Mason Plumlee and Brian Zoubek, combined, have about as much playing time (86.7% minutes played combined) as Greg Monroe (84.7%). Whoever has the most rebounds (MP2 + Zoo vs Monroe) will be on the victorious team.
Labels:
Duke Game Preview
Friday, January 22, 2010
Worst Duke Defensive Performances
It's been a while since we've done college basketball here, and I have a few things planned for the coming months, including a systematic re-do of last year's tournament simulation. In the meantime, I want to nip any "Matt's a Duke fanboy" criticism in the proverbial bud by doing a negative post about Duke.
The tempo-free era of college basketball began with the 2003-2004 season as Ken Pomeroy started putting posting his rankings based on offensive and defensive efficiency. Duke, for whatever reason, has always done pretty well during the regular season in Pomeroy's adjusted (for opponent offensive and defensive strength) rankings:
Year/Offensive Efficiency/ Defensive Efficiency
2010/1/18
2009/10/20
2008/11/9
2007/40/5
2006/5/13
2005/15/1
2004/2/4
Nevertheless, Duke has put up some hard-to-believe individual games on both sides of the ball. Defense, however, is so intricately tied to Coach K's philosophy that it is the better choice for a comprehensive breakdown. Defensive ability puts players on the floor for Coach K, and can limit the minutes of potentially explosive offensive perimeter players, if they cannot grasp Duke's defensive philosophy (c.f. Taylor King, Elliot Williams, Andre Dawkins). Usually, the result is a solid defensive gameplan that has consistently been in the top 20 the past six and a half seasons.
There have been great defensive efforts, and not always against inferior competition. In fact, the best defensive performance of the 228 games recorded on kenpom.com is this one, played December 19, 2009 against Gonzaga in Madison Square Garden. Duke held the Zags to an efficiency of 57.1, which is absolutely stellar when you consider that Gonzaga's 2009-2010 average is 111.3! But it has not been all good news for Duke this year, and it is an historic defensive lapse that is the reason for this post. Here are the top 10 worst defensive performances since 2003-2004:
#10 (118.4): January 14 2006 at Clemson (Duke W 87-77). We start with a surprising performance in that not only is it a Duke win, but also a win on the road. Although the 2005-2006 Duke team was frequently spotlighted for it's excellent defense, led by Shelden Williams' shotblocking ability, on this night at Littlejohn, things did not go well. Giving up more than a point per possession to a Clemson team that did not make the NCAA tournament and finished 94th in the nation in adjusted defense was simply not acceptable. Duke had some other defensive clunkers along the way, but eventually fell in the NCAA tournament due to their worst offensive performance in the tempo-free era. (But as Alton Brown might say, that's another post...)
#9 (119.0) November 16 2008 vs Rhode Island (Duke W 82-79). This was the night that RIU's Jimmy Barron almost got a permanent middle name from Duke fans. Barron hit seven straight three-pointers before Dave McClure came off the bench to get a hand in Barron's face, causing him to heave an air-ball with 1:24 remaining and Duke down by 2 (ESPN's play-by-play calls the shot a 2-pointer, but I was at the game and remember differently). This was by far the loudest I've heard Cameron in a non-conference game. I also had the pleasure of high-fiving Jimmy Barron as he ran off the court, and I have not washed that hand since.
#8 (119.1) March 8 2009 at North Carolina (Duke L 79-71). This was the closer of the two Duke-UNC games last year, and both teams were had worse efficiencies than the earlier matchup. The pace was 13 possessions slower as well. The biggest standout is that the Tar Heels rebounded over 40% of their missed shots, while Duke's offensive rebounding percentage was a dismal 18.8%. Eww.
#6t (121.3) February 18 2004 at Wake Forest (Duke L 90-84). Duke's best team during the Tempo-Free era only lost six games all season, and every time they did, they allowed more than a point per possession. It was Duke's second loss in a week (they lost at NC State earlier) and is perhaps the best lesson for Chicken-Little Duke fans and Duke haters alike, concerning this year's Duke team. Despite the efforts of the media and the common fan, "consistency" just doesn't mean anything. Especially in ACC road games. A team can put up clunkers in consecutive games in January and still get within an Okafor of the national championship game.
#6t (121.3) January 21 2006 at Georgetown (Duke L 87-84). From the second paragraph of that ESPN recap: "That's my child," the elder Thompson said. "I love my child. After all he's had to go through, he deserves this." Duke never led in a classic execution of the Princeton offense, and JJ Redick scored 41 points, and with Duke almost matching the Hoyas' offensive efficiency with a 117.3 rating. Free throws were the difference, as Georgetown got to the line more often than Duke. It is unclear what the elder Thompson said of Duke's destruction of Georgetown in 2009.
#5 (124.5) February 22 2009 vs Wake Forest (Duke W 101-91). Last year was Duke's worst from a defensive standpoint, and it shows in this top ten list. This game was the polar opposite of the game a few weeks earlier in Winston-Salem, a two point loss for Duke in which neither team topped 95 in efficiency. The rematch in Cameron however had a similar number of possessions and basically no defense.
#4 (125.8) February 20 2005 vs Wake Forest (Duke W 102-92). An eerily similar game to the one above, although this rematch played out exactly like the preceding game at Wake Forest (see below); the only difference was the result for Duke. Interesting point about the 2004-2005 Duke team; if you check here, you can see all the factors that were correlated to Duke's defensive performance that year. Interestingly, nearly all the factors are in bold, indicating a significant (at the 95% confidence level) correlation. Duke's defensive performance that year was strongly tied to their opponents' shooting, rebounding ability, turnover rate, and ability to get to the free throw line. Defense was also significantly correlated to Duke's own offensive ability that night, especially on Duke's offensive glass. It should come as no surprise, then, that Duke was knocked off in the Sweet 16 in a game to a Michigan State team that was among the best in offensive rebounding, among other things.
#3 (127.0) January 19, 2010 at NC State (Duke L 88-74). Ah, the inspiration for this post. Duke was outplayed on their defensive end in a big way, and NC State was helped by a healthy 62.7 effective field goal percentage. They also protected the ball, turning it over on just 13% of their possessions, and turnover rate seems to be a relative strength of this year's Wolfpack team. Offensive efficiency, however, has not exactly been consistent for NC State, and while they put up similar numbers against Georgia Southern and UNC-G, an effort like this against a top-20 defense was completely unexpected. I see no reason to see the game as anything other than a fluke for Duke, and while winning at Littlejohn tomorrow will be a tough task, if Duke loses it will not be due to another defensive calamity. For this, in K, I trust.
#2 (127.6) February 11 2009 vs North Carolina (Duke L 102-87). Easily the worst Duke game I have ever attended, as Duke was never really in this game. Unlike some of the other games, this was not a defensive lapse against an otherwise mediocre offense. This was a lashing at the hands of the eventual champs who could not stop two All-Americans from doing whatever they want on the court. Yes, I'm a little bitter that I slept outside in a tent to watch this game. Next.
#1 (131.6) February 2 2005 at Wake Forest (Duke L 92-89). So many surprising things about this list, including the number of home games (4) and the number of Duke wins (4) and the number of appearances by the Demon Deacons (4). There is quite a wide gap between #2 and this game, and Duke almost pulled off the win! This was a collision of elite squads, as Duke finished the 04-05 season with the best defense in the nation, while Chris Paul's team was the #2 offense. Wake's inability to stop anyone came back to bite them in March, as they couldn't shoot their way out of early exits in both the ACC and NCAA tournaments.
To be fair, Wake Forest dominated the the middle 36 minutes of the game and it was only the 3-point abilities of the talented Mr. Redick that brought the game close at the end: JJ hit three from beyond the arc and Sean Dockery made it 90-89 with two seconds left. Taron Downey hit both of his free throws and Redick missed a running three to end the game. Notably, Duke's offensive efficiency in this game was 127.3, and so one must conclude that it was indeed Duke's defense that prevented the win. As the rematch (see #4) showed, home court has a lot to do with the outcome of games like these.
The biggest absence from this top 10 list: games in March. For all of the hate heaped upon Duke for its struggles in the month of March, not once did they make an NCAA tournament exit due to a sudden lack of defense. In fact, the worst NCAA tournament performance is (predictably) the 2007 first-round loss to VCU, which is 27th on the list at 112.0, followed by last year's win over Texas (36th at 109.3). But those games are miles from the ones above, and allowing around 110 points/100 possessions is probably to be expected from some of the elite offenses in the nation. Coach K gets his teams prepared on the defensive end for March, combined with playing non-ACC teams unfamiliar with Duke's defensive style. There are relatively more games in ACC tournament on the list.
I have compiled the stats from kenpom.com from all years into one spreadsheet, which can be found here for your sorting pleasure. Tempo-free stats can tell us a lot about a team that we weren't expecting to hear. This would be not-so-subtle foreshadowing of a future post about Duke. For a further hint, see this and this.
The tempo-free era of college basketball began with the 2003-2004 season as Ken Pomeroy started putting posting his rankings based on offensive and defensive efficiency. Duke, for whatever reason, has always done pretty well during the regular season in Pomeroy's adjusted (for opponent offensive and defensive strength) rankings:
Year/Offensive Efficiency/ Defensive Efficiency
2010/1/18
2009/10/20
2008/11/9
2007/40/5
2006/5/13
2005/15/1
2004/2/4
Nevertheless, Duke has put up some hard-to-believe individual games on both sides of the ball. Defense, however, is so intricately tied to Coach K's philosophy that it is the better choice for a comprehensive breakdown. Defensive ability puts players on the floor for Coach K, and can limit the minutes of potentially explosive offensive perimeter players, if they cannot grasp Duke's defensive philosophy (c.f. Taylor King, Elliot Williams, Andre Dawkins). Usually, the result is a solid defensive gameplan that has consistently been in the top 20 the past six and a half seasons.
There have been great defensive efforts, and not always against inferior competition. In fact, the best defensive performance of the 228 games recorded on kenpom.com is this one, played December 19, 2009 against Gonzaga in Madison Square Garden. Duke held the Zags to an efficiency of 57.1, which is absolutely stellar when you consider that Gonzaga's 2009-2010 average is 111.3! But it has not been all good news for Duke this year, and it is an historic defensive lapse that is the reason for this post. Here are the top 10 worst defensive performances since 2003-2004:
#10 (118.4): January 14 2006 at Clemson (Duke W 87-77). We start with a surprising performance in that not only is it a Duke win, but also a win on the road. Although the 2005-2006 Duke team was frequently spotlighted for it's excellent defense, led by Shelden Williams' shotblocking ability, on this night at Littlejohn, things did not go well. Giving up more than a point per possession to a Clemson team that did not make the NCAA tournament and finished 94th in the nation in adjusted defense was simply not acceptable. Duke had some other defensive clunkers along the way, but eventually fell in the NCAA tournament due to their worst offensive performance in the tempo-free era. (But as Alton Brown might say, that's another post...)
#9 (119.0) November 16 2008 vs Rhode Island (Duke W 82-79). This was the night that RIU's Jimmy Barron almost got a permanent middle name from Duke fans. Barron hit seven straight three-pointers before Dave McClure came off the bench to get a hand in Barron's face, causing him to heave an air-ball with 1:24 remaining and Duke down by 2 (ESPN's play-by-play calls the shot a 2-pointer, but I was at the game and remember differently). This was by far the loudest I've heard Cameron in a non-conference game. I also had the pleasure of high-fiving Jimmy Barron as he ran off the court, and I have not washed that hand since.
#8 (119.1) March 8 2009 at North Carolina (Duke L 79-71). This was the closer of the two Duke-UNC games last year, and both teams were had worse efficiencies than the earlier matchup. The pace was 13 possessions slower as well. The biggest standout is that the Tar Heels rebounded over 40% of their missed shots, while Duke's offensive rebounding percentage was a dismal 18.8%. Eww.
#6t (121.3) February 18 2004 at Wake Forest (Duke L 90-84). Duke's best team during the Tempo-Free era only lost six games all season, and every time they did, they allowed more than a point per possession. It was Duke's second loss in a week (they lost at NC State earlier) and is perhaps the best lesson for Chicken-Little Duke fans and Duke haters alike, concerning this year's Duke team. Despite the efforts of the media and the common fan, "consistency" just doesn't mean anything. Especially in ACC road games. A team can put up clunkers in consecutive games in January and still get within an Okafor of the national championship game.
#6t (121.3) January 21 2006 at Georgetown (Duke L 87-84). From the second paragraph of that ESPN recap: "That's my child," the elder Thompson said. "I love my child. After all he's had to go through, he deserves this." Duke never led in a classic execution of the Princeton offense, and JJ Redick scored 41 points, and with Duke almost matching the Hoyas' offensive efficiency with a 117.3 rating. Free throws were the difference, as Georgetown got to the line more often than Duke. It is unclear what the elder Thompson said of Duke's destruction of Georgetown in 2009.
#5 (124.5) February 22 2009 vs Wake Forest (Duke W 101-91). Last year was Duke's worst from a defensive standpoint, and it shows in this top ten list. This game was the polar opposite of the game a few weeks earlier in Winston-Salem, a two point loss for Duke in which neither team topped 95 in efficiency. The rematch in Cameron however had a similar number of possessions and basically no defense.
#4 (125.8) February 20 2005 vs Wake Forest (Duke W 102-92). An eerily similar game to the one above, although this rematch played out exactly like the preceding game at Wake Forest (see below); the only difference was the result for Duke. Interesting point about the 2004-2005 Duke team; if you check here, you can see all the factors that were correlated to Duke's defensive performance that year. Interestingly, nearly all the factors are in bold, indicating a significant (at the 95% confidence level) correlation. Duke's defensive performance that year was strongly tied to their opponents' shooting, rebounding ability, turnover rate, and ability to get to the free throw line. Defense was also significantly correlated to Duke's own offensive ability that night, especially on Duke's offensive glass. It should come as no surprise, then, that Duke was knocked off in the Sweet 16 in a game to a Michigan State team that was among the best in offensive rebounding, among other things.
#3 (127.0) January 19, 2010 at NC State (Duke L 88-74). Ah, the inspiration for this post. Duke was outplayed on their defensive end in a big way, and NC State was helped by a healthy 62.7 effective field goal percentage. They also protected the ball, turning it over on just 13% of their possessions, and turnover rate seems to be a relative strength of this year's Wolfpack team. Offensive efficiency, however, has not exactly been consistent for NC State, and while they put up similar numbers against Georgia Southern and UNC-G, an effort like this against a top-20 defense was completely unexpected. I see no reason to see the game as anything other than a fluke for Duke, and while winning at Littlejohn tomorrow will be a tough task, if Duke loses it will not be due to another defensive calamity. For this, in K, I trust.
#2 (127.6) February 11 2009 vs North Carolina (Duke L 102-87). Easily the worst Duke game I have ever attended, as Duke was never really in this game. Unlike some of the other games, this was not a defensive lapse against an otherwise mediocre offense. This was a lashing at the hands of the eventual champs who could not stop two All-Americans from doing whatever they want on the court. Yes, I'm a little bitter that I slept outside in a tent to watch this game. Next.
#1 (131.6) February 2 2005 at Wake Forest (Duke L 92-89). So many surprising things about this list, including the number of home games (4) and the number of Duke wins (4) and the number of appearances by the Demon Deacons (4). There is quite a wide gap between #2 and this game, and Duke almost pulled off the win! This was a collision of elite squads, as Duke finished the 04-05 season with the best defense in the nation, while Chris Paul's team was the #2 offense. Wake's inability to stop anyone came back to bite them in March, as they couldn't shoot their way out of early exits in both the ACC and NCAA tournaments.
To be fair, Wake Forest dominated the the middle 36 minutes of the game and it was only the 3-point abilities of the talented Mr. Redick that brought the game close at the end: JJ hit three from beyond the arc and Sean Dockery made it 90-89 with two seconds left. Taron Downey hit both of his free throws and Redick missed a running three to end the game. Notably, Duke's offensive efficiency in this game was 127.3, and so one must conclude that it was indeed Duke's defense that prevented the win. As the rematch (see #4) showed, home court has a lot to do with the outcome of games like these.
The biggest absence from this top 10 list: games in March. For all of the hate heaped upon Duke for its struggles in the month of March, not once did they make an NCAA tournament exit due to a sudden lack of defense. In fact, the worst NCAA tournament performance is (predictably) the 2007 first-round loss to VCU, which is 27th on the list at 112.0, followed by last year's win over Texas (36th at 109.3). But those games are miles from the ones above, and allowing around 110 points/100 possessions is probably to be expected from some of the elite offenses in the nation. Coach K gets his teams prepared on the defensive end for March, combined with playing non-ACC teams unfamiliar with Duke's defensive style. There are relatively more games in ACC tournament on the list.
I have compiled the stats from kenpom.com from all years into one spreadsheet, which can be found here for your sorting pleasure. Tempo-free stats can tell us a lot about a team that we weren't expecting to hear. This would be not-so-subtle foreshadowing of a future post about Duke. For a further hint, see this and this.
Labels:
Bottom Ten,
Defense,
Duke,
Tempo-Free Stats
Monday, December 28, 2009
2009 AFC Playoff Scenarios
One year ago, we constructed a popular post about the playoff permutations in the AFC East. This year, a logjam in the middle of the AFC leaves many meaningful games for week 17.
It is possible that five teams could finish 9-7 (Jets, Denver, Baltimore, Pittsburgh, Houston). In this scenario, strength of conference record ranks the teams first. This eliminates the Texans and Steelers, since both teams would finish at 6-6 in conference, while the other three teams would finish 7-5. Next, record in common games applies:
Versus NE, OAK, IND, and CIN:
Jets: 4-1
Broncos: 3-2
Ravens: 1-3
This gives the Jets the #5 seed and the Ravens would take the #6 seed thanks to their victory over the Broncos.
A different, crazier, possibility exists. With one week to play, it is possible that EIGHT AFC teams can finish at a mediocre 8-8, which in addition to giving ex-commisioner (and lover of parity) Paul Tagliabue a spring in his step, it brings upon the NFL the full power of the sometimes mysterious NFL Tiebreaking procedures. So what if the stars align and all eight teams finish at 8-8?
The key is that ties within divisions are broken first, with only one team per division advancing:
Within Division:
East: Mia > NYJ (head2head)
North: Bal > Pit (Division record)
West: Den
South: Jax (3-way h2h):
Jax 3-1 vs Hou, Ten
Ten 2-2 vs Hou, Jax
Hou 1-3 vs Ten, Jax
In a multi-team tiebreaker, a head to head sweep would prevail but the teams did not all play each other. Baltimore's win over Denver is irrelevant now.
This lands with the games-within-conference tiebreaker, and an 8-8 Jacksonville would have 7 wins in conference, so they're in.
The remaining three teams would be 6-6 in conference.
The next tiebreaker is record in common games (minimum four), and each team has played NE, PIT, IND, and SD:
Denver 2-3
Baltimore 2-3
Miami 2-3
This, troublesomely, leaves each team at 2-3, causing us to enter the magical land of Strength of Victory. Luckily, in the Everyone 8-8 Scenario, many games have been decided for us.
Denver beat: CIN (11), CLE (4), OAK (6), DAL (10, Play PHI), NE (11), SD (12, Play WAS), NYG (8, Play MIN), KC (4)
Ravens beat: KC (4), SD (12, Play WAS) , CLE (4), DEN (8), CLE (4), PIT (8), DET (2, Play CHI), CHI (5, play MIN and DET)
Miami beat: BUF (5, Play IND), NYJ (8), NYJ (8), TB (3, Play ATL), CAR (7, Play NO), NE (11), JAX (8), PIT (8)
So the games we would know for sure:
DEN: 66
BAL: 47
MIA: 58
The superior record of teams the Broncos have beaten is insurmountable, and so the Broncos would get the final playoff spot.
Meanwhile, the wins by the Patriots (over Houston) and Bengals (over the Jets) would put them both at 11-5 and at 8-4 in the conference. Moving on to record in common games against the Jets, Ravens, Texans, and Broncos:
NE: 3-2
CIN: 3-2
Which leaves Strength of Victory:
NE beat: NYJ (8), BAL (8), HOU (8), BUF (5, play IND), ATL (3, play TB), TEN (8), TB (3, play ATL), MIA (8), CAR (7, play NO), BUF (5, play IND), JAX (8) (71 wins)
CIN beat: NYJ (8), BAL (8), BAL (8), PIT (8), GB (10, play ARI), CLE (4), CHI (5, play MIN and DET), PIT (8), CLE (4), DET (2, Play CHI), KC (4) (69 wins)
So New England would have multiple ways to increase its lead over Cincinnati in the Strength of Victory department next week, while the Bengals will have to wait for everything to fall into place in order to grab the 3rd seed.
In summary, the Great Mediocrity Scenario of 2009 would create the following playoff matchups:
1. Indianapolis (bye)
2. San Diego (bye)
3. New England vs 6. Denver
4. Cincinnati vs 5. Jacksonville
Feel free to point out any errors I have made in the comments.
Update 1: Fixed Ravens-Broncos error pointed out in the comments. I blame NFL.com's difficult to read schedule page...
It is possible that five teams could finish 9-7 (Jets, Denver, Baltimore, Pittsburgh, Houston). In this scenario, strength of conference record ranks the teams first. This eliminates the Texans and Steelers, since both teams would finish at 6-6 in conference, while the other three teams would finish 7-5. Next, record in common games applies:
Versus NE, OAK, IND, and CIN:
Jets: 4-1
Broncos: 3-2
Ravens: 1-3
This gives the Jets the #5 seed and the Ravens would take the #6 seed thanks to their victory over the Broncos.
A different, crazier, possibility exists. With one week to play, it is possible that EIGHT AFC teams can finish at a mediocre 8-8, which in addition to giving ex-commisioner (and lover of parity) Paul Tagliabue a spring in his step, it brings upon the NFL the full power of the sometimes mysterious NFL Tiebreaking procedures. So what if the stars align and all eight teams finish at 8-8?
The key is that ties within divisions are broken first, with only one team per division advancing:
Within Division:
East: Mia > NYJ (head2head)
North: Bal > Pit (Division record)
West: Den
South: Jax (3-way h2h):
Jax 3-1 vs Hou, Ten
Ten 2-2 vs Hou, Jax
Hou 1-3 vs Ten, Jax
In a multi-team tiebreaker, a head to head sweep would prevail but the teams did not all play each other. Baltimore's win over Denver is irrelevant now.
This lands with the games-within-conference tiebreaker, and an 8-8 Jacksonville would have 7 wins in conference, so they're in.
The remaining three teams would be 6-6 in conference.
The next tiebreaker is record in common games (minimum four), and each team has played NE, PIT, IND, and SD:
Denver 2-3
Baltimore 2-3
Miami 2-3
This, troublesomely, leaves each team at 2-3, causing us to enter the magical land of Strength of Victory. Luckily, in the Everyone 8-8 Scenario, many games have been decided for us.
Denver beat: CIN (11), CLE (4), OAK (6), DAL (10, Play PHI), NE (11), SD (12, Play WAS), NYG (8, Play MIN), KC (4)
Ravens beat: KC (4), SD (12, Play WAS) , CLE (4), DEN (8), CLE (4), PIT (8), DET (2, Play CHI), CHI (5, play MIN and DET)
Miami beat: BUF (5, Play IND), NYJ (8), NYJ (8), TB (3, Play ATL), CAR (7, Play NO), NE (11), JAX (8), PIT (8)
So the games we would know for sure:
DEN: 66
BAL: 47
MIA: 58
The superior record of teams the Broncos have beaten is insurmountable, and so the Broncos would get the final playoff spot.
Meanwhile, the wins by the Patriots (over Houston) and Bengals (over the Jets) would put them both at 11-5 and at 8-4 in the conference. Moving on to record in common games against the Jets, Ravens, Texans, and Broncos:
NE: 3-2
CIN: 3-2
Which leaves Strength of Victory:
NE beat: NYJ (8), BAL (8), HOU (8), BUF (5, play IND), ATL (3, play TB), TEN (8), TB (3, play ATL), MIA (8), CAR (7, play NO), BUF (5, play IND), JAX (8) (71 wins)
CIN beat: NYJ (8), BAL (8), BAL (8), PIT (8), GB (10, play ARI), CLE (4), CHI (5, play MIN and DET), PIT (8), CLE (4), DET (2, Play CHI), KC (4) (69 wins)
So New England would have multiple ways to increase its lead over Cincinnati in the Strength of Victory department next week, while the Bengals will have to wait for everything to fall into place in order to grab the 3rd seed.
In summary, the Great Mediocrity Scenario of 2009 would create the following playoff matchups:
1. Indianapolis (bye)
2. San Diego (bye)
3. New England vs 6. Denver
4. Cincinnati vs 5. Jacksonville
Feel free to point out any errors I have made in the comments.
Update 1: Fixed Ravens-Broncos error pointed out in the comments. I blame NFL.com's difficult to read schedule page...
Labels:
meh,
nfl,
playoff scenarios
Monday, September 07, 2009
Congrats to Ross Ohlendorf(and belatedly to A.J. Burnett)
On Saturday, Ross Ohlendorf pitched an immaculate seventh inning against the Cardinals. You can watch it here. I'd have to defer to mehmattski on this, but I would bet that it's the first time that an Immaculate Inning has been throw where every strikeout was a dropped third strike.
On June 20th, AJ Burnett threw an immaculate inning of his own. You would think that a blog written by a Yankees fan and a Marlins fan who also follows Former Marlins, would've noticed when a Former Marlin throws an Immaculate Inning for the Yankees, against the Marlins. To our 6 readers and AJ Burnett, we wholeheartedly apologize for not posting about it when it happened.
On June 20th, AJ Burnett threw an immaculate inning of his own. You would think that a blog written by a Yankees fan and a Marlins fan who also follows Former Marlins, would've noticed when a Former Marlin throws an Immaculate Inning for the Yankees, against the Marlins. To our 6 readers and AJ Burnett, we wholeheartedly apologize for not posting about it when it happened.
Labels:
baseball,
cookie,
Immaculate Inning
Tuesday, April 28, 2009
Immaculate Inning: Daniel Bard
We at Immaculate Inning take a lot of pride in chronicling the rare feat which gives our blog its name; that is, striking out three batters in an inning using just nine pitches. It has only happened 41 times in major league history, but unfortunately we have no idea how common the feat is at the minor leagues. A few years ago it came to our attention that Chris Mason twirled an Immaculate Inning in a AA game. The immaculate inning fires take a while to get stroked with these minor league games, but we are proud to recount the feat of Red Sox prospect Daniel Bard. Major hat-tip to the Projo Sox Blog for bringing the performance to my attention.
Daniel Bard is a 23-year old righthander pitching for the Pawtucket Sox in AAA. He finished last season at AA, retiring 20 of his final 23 batters; that domination has continued into this season, as he sports a 1.69 ERA and has struck out 18 in 10.3 innings. One of those innings, and three of those strikeouts, came against the Rochester Red Wings on April 22. Some video of the immaculate inning can be found here.
The batters were Jason Pridie, Matt Tolbert, and Luke Hughes, the first three batters in the Rochester order. All of them are career minor leaguers, although the 23 year old Hughes appears to be a legit prospect. Pridie appears to go down swinging on three straight fastballs right down the pipe. Tolbert follows the advice of a nearby heckler ("swing!") and misses at three more fastballs from Bard. Some kind of offspeed pitch (curveball) is taken for a strike by Hughes before he swings way late on two fastballs, the second around his eyes. Bard, meanwhile, looks to be rather bored with AAA pitching, and should expect a call up to the majors sometime this season. Regardless of his future, Bard has solidified a place in history with his immaculate inning, and we offer him the highest congratulations!
Daniel Bard is a 23-year old righthander pitching for the Pawtucket Sox in AAA. He finished last season at AA, retiring 20 of his final 23 batters; that domination has continued into this season, as he sports a 1.69 ERA and has struck out 18 in 10.3 innings. One of those innings, and three of those strikeouts, came against the Rochester Red Wings on April 22. Some video of the immaculate inning can be found here.
The batters were Jason Pridie, Matt Tolbert, and Luke Hughes, the first three batters in the Rochester order. All of them are career minor leaguers, although the 23 year old Hughes appears to be a legit prospect. Pridie appears to go down swinging on three straight fastballs right down the pipe. Tolbert follows the advice of a nearby heckler ("swing!") and misses at three more fastballs from Bard. Some kind of offspeed pitch (curveball) is taken for a strike by Hughes before he swings way late on two fastballs, the second around his eyes. Bard, meanwhile, looks to be rather bored with AAA pitching, and should expect a call up to the majors sometime this season. Regardless of his future, Bard has solidified a place in history with his immaculate inning, and we offer him the highest congratulations!
Labels:
Immaculate Inning
Tuesday, March 24, 2009
Sweet Sixteen Predictions by Simulation
Now that I've taken a day to recover from watching some 40+ hours of basketball over the weekend, let's revisit the predictions made by my NCAA Tournament Simulator. Here's a link to bracket that I picked based on the highest number of average wins in the tournament. As you can see, the picks did pretty well, landing in the 72nd percentile overall on ESPN. Thirteen of the sweet Sixteen teams were picked correctly, and the bracket lost zero Elite Eight teams over the first weekend of play. The three most notable exceptions were West Virginia, UCLA and Wake Forest. The simulation could not have taken into account how absolutely uninspired these teams would play. It also missed the Western Kentucky over Illinois, since the simulation didn't know about the injury to Chester Frazier.
West Virginia did replace Michigan State in the Most Likely Elite Eight according to the one million simulations. How likely was the first round overall? I wrote a script to count the number of times the simulation predicted the exact first round results in each region:
West = YES! 41733 times!
Midwest = YES! 2325 times!
East = YES! 84894 times!
South = YES! 13648 times!
Overall = Nope. 0 matches.
Upsets of Wake Forest, Utah, and West Virginia at the same time in the Midwest region rarely occurred in the same simulation, and when they did, that simulation did not get one of the other regions correct. In fact, in my pool of 1 million simulations, just 66 produced the correct first round results in three of the four regions. It seems that even if I could have entered all one million simulations, it would not be enough to win Yahoo's Perfect Bracket $1 million. Oh well.
So what do the Pomeroy ratings tell us about the Sweet Sixteen and beyond? To answer that I have two different approaches. One is to simply report the results of the final simulation from Sunday night, the results of which can be found in the data and graphs in this post. Those results are based on the Pythagorean Winning Percentages posted before the first round of the tournament. Four days and forty-eight games (not counting NIT games) later, the rankings are a bit different. How does the added information enhance or suppress the national title chances of each team left in the tournament?
Elite Eight Chances (Click for Chart)
Final Four Chances (Click for Chart)
Championship Game Chances (Click for Chart)
National Title Chances (Click for Chart)
Basically, the inclusion of all the statistics from the tournament games has improved the chances of Connecticut and Memphis winning the national championship, and hurt the chances for nearly everyone else. For Thursday and Friday's games, the teams that most improved were Connecticut (+8.2%), Villanova (+5.5%), North Carolina (+4.5%), and Kansas (+4%). Predictably, the teams that were most hurt by the newer statistics were the immediate opponents of those four teams. UNC-Gonzaga has gone from a tossup (51%-49%) to a more solid favoring of the top seed (55%-45%). The closest game of the Sweet Sixteen now projects to be Oklahoma-Syracuse, with the third-seeded Orange winning 52% of the time.
In the Final Four, Connecticut has actually seen its chances decrease, due to a much higher proportion alocated to Memphis and Missouri, but the Huskies still win the West region in 35% of the one million simulations. From the Midwest, Louisville is still the favorite with a slight edge over Kansas; Michigan State saw a drop in their chances with the inclusion of the new stats. The South is just as open as it was to start the tournament, but Syracuse maintains a healthy advantage, followed by Oklahoma. There is then a huge dropoff between those two and North Carolina and Gonzaga. Finally, the East regional still projects a showdown between Pittsburgh and Duke, with the Blue Devils giving an ever so slight edge (29.00% to 28.28% for Pitt).
The updated stats say that the national title game is less likely to have a representative from the East region, compared with pre-Tourney stats. This is because the four remaining South regional teams all improved their title-game chances, while Duke had the biggest drop of all the teams (from 17.01% to 14.82%). The other half of the title game is still most likely to come from the West, which had Connecticut, Memphis, and Missouri all increase their chances with the inclusion of new stats.
It has, so far, been a tournament small on upsets. The simulator predicts that this trend will continue, with one small exception (#3 Syracuse over #2 Oklahoma), although many of the games project to be very close. One thing that could be improved in the model is the log5 predictions for teams with such similar Pythagorean Winning Percentages. This is one of the things I will be taking a look at in the offseason. In the meantime, it's only two more days until things get kicked off in Glendale, Arizona. Hooray basketball!
West Virginia did replace Michigan State in the Most Likely Elite Eight according to the one million simulations. How likely was the first round overall? I wrote a script to count the number of times the simulation predicted the exact first round results in each region:
West = YES! 41733 times!
Midwest = YES! 2325 times!
East = YES! 84894 times!
South = YES! 13648 times!
Overall = Nope. 0 matches.
Upsets of Wake Forest, Utah, and West Virginia at the same time in the Midwest region rarely occurred in the same simulation, and when they did, that simulation did not get one of the other regions correct. In fact, in my pool of 1 million simulations, just 66 produced the correct first round results in three of the four regions. It seems that even if I could have entered all one million simulations, it would not be enough to win Yahoo's Perfect Bracket $1 million. Oh well.
So what do the Pomeroy ratings tell us about the Sweet Sixteen and beyond? To answer that I have two different approaches. One is to simply report the results of the final simulation from Sunday night, the results of which can be found in the data and graphs in this post. Those results are based on the Pythagorean Winning Percentages posted before the first round of the tournament. Four days and forty-eight games (not counting NIT games) later, the rankings are a bit different. How does the added information enhance or suppress the national title chances of each team left in the tournament?
Elite Eight Chances (Click for Chart)
Final Four Chances (Click for Chart)
Championship Game Chances (Click for Chart)
National Title Chances (Click for Chart)
Basically, the inclusion of all the statistics from the tournament games has improved the chances of Connecticut and Memphis winning the national championship, and hurt the chances for nearly everyone else. For Thursday and Friday's games, the teams that most improved were Connecticut (+8.2%), Villanova (+5.5%), North Carolina (+4.5%), and Kansas (+4%). Predictably, the teams that were most hurt by the newer statistics were the immediate opponents of those four teams. UNC-Gonzaga has gone from a tossup (51%-49%) to a more solid favoring of the top seed (55%-45%). The closest game of the Sweet Sixteen now projects to be Oklahoma-Syracuse, with the third-seeded Orange winning 52% of the time.
In the Final Four, Connecticut has actually seen its chances decrease, due to a much higher proportion alocated to Memphis and Missouri, but the Huskies still win the West region in 35% of the one million simulations. From the Midwest, Louisville is still the favorite with a slight edge over Kansas; Michigan State saw a drop in their chances with the inclusion of the new stats. The South is just as open as it was to start the tournament, but Syracuse maintains a healthy advantage, followed by Oklahoma. There is then a huge dropoff between those two and North Carolina and Gonzaga. Finally, the East regional still projects a showdown between Pittsburgh and Duke, with the Blue Devils giving an ever so slight edge (29.00% to 28.28% for Pitt).
The updated stats say that the national title game is less likely to have a representative from the East region, compared with pre-Tourney stats. This is because the four remaining South regional teams all improved their title-game chances, while Duke had the biggest drop of all the teams (from 17.01% to 14.82%). The other half of the title game is still most likely to come from the West, which had Connecticut, Memphis, and Missouri all increase their chances with the inclusion of new stats.
It has, so far, been a tournament small on upsets. The simulator predicts that this trend will continue, with one small exception (#3 Syracuse over #2 Oklahoma), although many of the games project to be very close. One thing that could be improved in the model is the log5 predictions for teams with such similar Pythagorean Winning Percentages. This is one of the things I will be taking a look at in the offseason. In the meantime, it's only two more days until things get kicked off in Glendale, Arizona. Hooray basketball!
Labels:
NCAA Tourney,
predictions,
simulation,
Sweet Sixteen
Friday, March 20, 2009
Progression of Final Four Chances
At the Immaculate Inning we've been playing all week with different ways to present data generated by our NCAA Tournament simulation. Here is what I feel is the most dynamic view of things: after every set of games on both Thursday and Friday, I set the probability of the losing teams to "0" and re-ran the simulation. I've then graphed the final four chances of every team, by section. You can see the results below (also click here to view the whole source spreadsheet):
You can click on each tab to view the chart for each region. There lots of interesting in trends in each region. The re-simulations are based on the Pomeroy rankings from Thursday, and do not take into account statistics from the first round games themselves.
South Regional: The story here is the Final Four chances of #1 seed North Carolina. Note that these statistics do not take into account Ty Lawson's injury, and yet UNC has had their chances drop over the last two days. More specifically, they've stayed in about the same place, while four other teams have passed them in Final Four chances. Oklahoma is now the odds-on favorite, their chances jumping tremendously with the upset of Clemson elsewhere in the bracket. That is the story throughout; teams rarely improve their own Final Four chances with a win. Instead it's other teams losing that sends waves through the simulations. Three of the four remaining teams in the bottom half of the regional have a better final four shot than UNC, as does Gonzaga in the top half. Arizona State, meanwhile, has climbed from sixth to second in terms of Final Four chances, because they are favored in their matchup with Syracuse (52%-48%).
East Regional: Not much movement going on here, just some strengthening of chances for the favorites as the upsets just don't come. Remember, Wisconsin was heavily favored over FSU in the simulation, so the Seminoles' overtime loss doesn't have much effect on the rest of the regional. Basically, Wisconsin is now at 9%, having added FSU's original 4% to the Badgers' own 5% chances. Among the remainging teams, Texas has the worst chances, since they could have to go through Duke, UCLA, and Pitt (the top 3 teams, statistically), to make it to Detroit. Pittsburgh has the best chance of winning their second round game over Oklahoma St, while the Xavier-Wisconsin game should prove to be the closest of the second round.
Midwest Regional: One of the biggest jumps of the first round was in this regional-- Louisville is no longer the favorite, but instead Kansas wins the West 25% of the time. This only had a little bit to do with Kansas' win over North Dakota St. As you can see from the graph, the gigantic jump came at 5 PM, when simulation favorite West Virginia went down in an uninspiring performance against Dayton. Louisville, the #1 seed, also reached a Final Four chance of 25% by the end of the day, thanks to the upset of Wake Forest by Cleveland State (an upset we predicted in this post). There seems to be two types of games in the second round-- Kansas and Louisville are 80% favorites, while Michigan State and Arizona are favored at the 60-65% rate. If a Sweet Sixteen berth for a low-seeded, mid-major team is your defnition of "Cinderella," then Cleveland State's 38% chance of beating Arizona is the best slipper bet.
West Regional: Not much going on here, because there haven't been that many upsets. Our model did not see Maryland taking out Cal, but clearly they are a different team than the one which put up very mediocre numbers throughout the season. If Maryland can click their offense to the tune of 1.23 points/possession like against Cal, Memphis is going to be in for a long day. Purdue vs Washington is a coinflip (50.9% to 49.1%) and should be a very good game, while Missouri could have a tough time with Marquette.
Final Four Picture: There are tossups in pretty much every regional now, with Louisville-Kansas joining Pittsburgh-Duke and Memphis-Connecticut in the two-dog races. The South regional is as open as ever, and sees Oklahoma as the most likely representative. A UConn-Pittsburgh final still seems to be the most likely, while UConn and Memphis are the only teams winning more than 8% of the time (both are over 11%). This dynamic should change considerably after this weekend; currently the only major change was the elimination of West Virginia. Gonzaga and Kansas have slipped past Duke and are the fourth and fifth most likely championship teams.
So that's where we stand after the first thirty-two games of the 2009 NCAA tournament. Tomorrow and Sunday I'll be updating frequently with the chances of each team's advancement, and I will follow next week with a new simulation from the Sweet-Sixteen onwards! Till then, may your brackets be less busted than mine!
You can click on each tab to view the chart for each region. There lots of interesting in trends in each region. The re-simulations are based on the Pomeroy rankings from Thursday, and do not take into account statistics from the first round games themselves.
South Regional: The story here is the Final Four chances of #1 seed North Carolina. Note that these statistics do not take into account Ty Lawson's injury, and yet UNC has had their chances drop over the last two days. More specifically, they've stayed in about the same place, while four other teams have passed them in Final Four chances. Oklahoma is now the odds-on favorite, their chances jumping tremendously with the upset of Clemson elsewhere in the bracket. That is the story throughout; teams rarely improve their own Final Four chances with a win. Instead it's other teams losing that sends waves through the simulations. Three of the four remaining teams in the bottom half of the regional have a better final four shot than UNC, as does Gonzaga in the top half. Arizona State, meanwhile, has climbed from sixth to second in terms of Final Four chances, because they are favored in their matchup with Syracuse (52%-48%).
East Regional: Not much movement going on here, just some strengthening of chances for the favorites as the upsets just don't come. Remember, Wisconsin was heavily favored over FSU in the simulation, so the Seminoles' overtime loss doesn't have much effect on the rest of the regional. Basically, Wisconsin is now at 9%, having added FSU's original 4% to the Badgers' own 5% chances. Among the remainging teams, Texas has the worst chances, since they could have to go through Duke, UCLA, and Pitt (the top 3 teams, statistically), to make it to Detroit. Pittsburgh has the best chance of winning their second round game over Oklahoma St, while the Xavier-Wisconsin game should prove to be the closest of the second round.
Midwest Regional: One of the biggest jumps of the first round was in this regional-- Louisville is no longer the favorite, but instead Kansas wins the West 25% of the time. This only had a little bit to do with Kansas' win over North Dakota St. As you can see from the graph, the gigantic jump came at 5 PM, when simulation favorite West Virginia went down in an uninspiring performance against Dayton. Louisville, the #1 seed, also reached a Final Four chance of 25% by the end of the day, thanks to the upset of Wake Forest by Cleveland State (an upset we predicted in this post). There seems to be two types of games in the second round-- Kansas and Louisville are 80% favorites, while Michigan State and Arizona are favored at the 60-65% rate. If a Sweet Sixteen berth for a low-seeded, mid-major team is your defnition of "Cinderella," then Cleveland State's 38% chance of beating Arizona is the best slipper bet.
West Regional: Not much going on here, because there haven't been that many upsets. Our model did not see Maryland taking out Cal, but clearly they are a different team than the one which put up very mediocre numbers throughout the season. If Maryland can click their offense to the tune of 1.23 points/possession like against Cal, Memphis is going to be in for a long day. Purdue vs Washington is a coinflip (50.9% to 49.1%) and should be a very good game, while Missouri could have a tough time with Marquette.
Final Four Picture: There are tossups in pretty much every regional now, with Louisville-Kansas joining Pittsburgh-Duke and Memphis-Connecticut in the two-dog races. The South regional is as open as ever, and sees Oklahoma as the most likely representative. A UConn-Pittsburgh final still seems to be the most likely, while UConn and Memphis are the only teams winning more than 8% of the time (both are over 11%). This dynamic should change considerably after this weekend; currently the only major change was the elimination of West Virginia. Gonzaga and Kansas have slipped past Duke and are the fourth and fifth most likely championship teams.
So that's where we stand after the first thirty-two games of the 2009 NCAA tournament. Tomorrow and Sunday I'll be updating frequently with the chances of each team's advancement, and I will follow next week with a new simulation from the Sweet-Sixteen onwards! Till then, may your brackets be less busted than mine!
Labels:
Final Four,
NCAA Tourney,
simulation
ACC Teams in NCAAT: Day 2
Above is a real time progression of the Final Four chances and the number of average wins for the seven ACC teams using my NCAA Tournament simulation. Yesterday there were a number of interesting trends, including the downward trend of Carolina's Final Four chances despite crushing Radford earlier in the day. In fact, they are no longer the favorite to win the South regional. Maryland improved their average number of wins from 0.44 to 1.15, despite the fact that they now have one actual win. This reflects the 15% chance that they will beat Memphis on Saturday.
As we enter Day 2, it will be interesting to see the chances of Boston College, Wake Forest, and Florida St before and after they play their games. It will also be interesting to follow the progression of Duke and Carolina's chances as the number of upsets increases. My next update will be after the 12 PM games. I don't expect there to be much effect on the ACC teams, but some upsets could send waves through other teams' chances (for example, if Stephen F. Austin upset Syracuse, it would solidify Oklahoma as the South regional favorite).
Labels:
NCAA Tourney,
predictions,
Real Time Chances
Thursday, March 19, 2009
ACC Teams in NCAAT: Real Time Chances
Throughout the day, I'm going to re-simulate the NCAAT as each team loses. Then, I am going to plot for each ACC team, their chances of making the Final Four. The first update should be around 2:30 Eastern, and will definitely have implications for North Carolina. Check back here often to see your team's chances change, in real time*!
Starting Chances:
North Carolina (#1 South): 15.28%
Duke (#2 East): 17.61%
Wake Forest (#4 Midwest): 9.72%
Florida State (#5 East): 4.62%
Boston College (#7 Midwest): 1.61%
Maryland (#10 West): 0.90%
*What the hell does "real time" mean anyway? As opposed to fake time? How would I update in fake time, anyway?
Update 1: 3:18 PM
Just ran a new simulation, taking into account the results of the 12 PM games. Three games, and already one pretty large upset, although you wouldn't tell it from the seeds. In the initial simulation, Butler beat Texas A&M 63% of the time. As you can see, there is not much change for the ACC teams. Click on the other tabs to see a handy progression chart for Final Four chances and for Average Wins. The biggest positive effects seem to be on the chances of UConn and Texas A&M making the final four (up 3-4% each), while no teams dipped all that much. The next update will be around 5 PM with the results of the 2:30 games, which will have a much bigger impact on the ACC teams, since two of them are playing...
Important note: the Pythagorean Win Percentages used to make this simulation are different from the ones used Sunday. I mistakenly did not save the original rankings, and the new rankings take into account adjustments based on the NIT results... if an NIT team played well, all of their opponents will have better adjusted stats. That is the reason why teams like Wake had their chances change from pre-tourney. I think the rest of the first round I will use today's statistics, rather than have them adjust each time.
Update #2: 12:52 AM
The results of Day 1 of the NCAA tournament are final. There were some exciting finishes in the first sixteen games, and by the seeds only one true upset. However, by the statistics there were some fairly unlikely results; BYU was favored 2-to-1 over Texas A&M, and Maryland was a 3-to-1 underdog against California. But as they say, that's why they play the games. Overall the "average wins" bracket was 12 for 16 (75%) on the first day, and lost zero teams beyond the second round. One of the games was as close to a coin flip as one can probably get; Butler beat LSU a slim 50.62% of the original simulations.
For the ACC, the major changes are obviously for Clemson, upset by a hot shooting Michigan team, and Maryland, whose one actual win only improves their "average wins" score by 0.74! In terms of Final Four probability, both Duke and Carolina saw their chances decrease throughout the day, despite winning. This is because while both teams were heavily favored to win their games, the teams in their way were not as heavily favored. In those matchups where Duke was playing Minnesota and American on the way to the Elite Eight, Duke would be the heavy favorite; those matchups are now impossible in the simulation.
Overall, the team with the biggest "bump" today was Memphis, which rose to an 11.73% chance of winning it all, thanks to the Maryland upset. Connecticut also benefited from the Texas A&M "on paper" upset, rising to 11.14%. Those two teams now sit at a combined 50% chance to win the west region; it doesn't look promising for the challengers there.
The biggest story is probably that North Carolina is no longer favored to win the South regional. After their win over Morgan St, and a very favorable matchup against Michigan in the second round, raised Oklahoma to 22.93% chance to make the Final Four. This is exactly the sort of thing we were looking for with these predictions-- how the matchups dictate who has the best chances to survive and advance. This will probably change dramatically tomorrow, especially if Syracuse and Arizona St. hold serve in the rest of Oklahoma's bracket. Certainly something to keep an eye on.
Starting Chances:
North Carolina (#1 South): 15.28%
Duke (#2 East): 17.61%
Wake Forest (#4 Midwest): 9.72%
Florida State (#5 East): 4.62%
Boston College (#7 Midwest): 1.61%
Maryland (#10 West): 0.90%
*What the hell does "real time" mean anyway? As opposed to fake time? How would I update in fake time, anyway?
Update 1: 3:18 PM
Just ran a new simulation, taking into account the results of the 12 PM games. Three games, and already one pretty large upset, although you wouldn't tell it from the seeds. In the initial simulation, Butler beat Texas A&M 63% of the time. As you can see, there is not much change for the ACC teams. Click on the other tabs to see a handy progression chart for Final Four chances and for Average Wins. The biggest positive effects seem to be on the chances of UConn and Texas A&M making the final four (up 3-4% each), while no teams dipped all that much. The next update will be around 5 PM with the results of the 2:30 games, which will have a much bigger impact on the ACC teams, since two of them are playing...
Important note: the Pythagorean Win Percentages used to make this simulation are different from the ones used Sunday. I mistakenly did not save the original rankings, and the new rankings take into account adjustments based on the NIT results... if an NIT team played well, all of their opponents will have better adjusted stats. That is the reason why teams like Wake had their chances change from pre-tourney. I think the rest of the first round I will use today's statistics, rather than have them adjust each time.
Update #2: 12:52 AM
The results of Day 1 of the NCAA tournament are final. There were some exciting finishes in the first sixteen games, and by the seeds only one true upset. However, by the statistics there were some fairly unlikely results; BYU was favored 2-to-1 over Texas A&M, and Maryland was a 3-to-1 underdog against California. But as they say, that's why they play the games. Overall the "average wins" bracket was 12 for 16 (75%) on the first day, and lost zero teams beyond the second round. One of the games was as close to a coin flip as one can probably get; Butler beat LSU a slim 50.62% of the original simulations.
For the ACC, the major changes are obviously for Clemson, upset by a hot shooting Michigan team, and Maryland, whose one actual win only improves their "average wins" score by 0.74! In terms of Final Four probability, both Duke and Carolina saw their chances decrease throughout the day, despite winning. This is because while both teams were heavily favored to win their games, the teams in their way were not as heavily favored. In those matchups where Duke was playing Minnesota and American on the way to the Elite Eight, Duke would be the heavy favorite; those matchups are now impossible in the simulation.
Overall, the team with the biggest "bump" today was Memphis, which rose to an 11.73% chance of winning it all, thanks to the Maryland upset. Connecticut also benefited from the Texas A&M "on paper" upset, rising to 11.14%. Those two teams now sit at a combined 50% chance to win the west region; it doesn't look promising for the challengers there.
The biggest story is probably that North Carolina is no longer favored to win the South regional. After their win over Morgan St, and a very favorable matchup against Michigan in the second round, raised Oklahoma to 22.93% chance to make the Final Four. This is exactly the sort of thing we were looking for with these predictions-- how the matchups dictate who has the best chances to survive and advance. This will probably change dramatically tomorrow, especially if Syracuse and Arizona St. hold serve in the rest of Oklahoma's bracket. Certainly something to keep an eye on.
Labels:
Liveblog,
NCAA Tourney,
Real Time Chances
Immaculate Inning Bracket
My NCAA tournament simulations have been the most popular thing I've ever done on Immaculate Inning. With the tournament starting in one hour, I thought I'd get my personal pics out there. First of all, here is the tournament, selected simply by picking the team with the most average wins in the tournament (click to enlarge):
But there's more to March Madness than simply statistics. Here is what I call the "Educated Intuition" bracket. It resembles the simulation bracket because I used those to educate my decisions. However, I overrulled the bracket in several key matchups. Plus, I always have to have one bracket where Duke wins it all!
I'll be coming back to Tournament Simulations and breakdowns throughout the weekend and into next week. Thanks for visiting Immaculate Inning for your tourney prognostication needs!
But there's more to March Madness than simply statistics. Here is what I call the "Educated Intuition" bracket. It resembles the simulation bracket because I used those to educate my decisions. However, I overrulled the bracket in several key matchups. Plus, I always have to have one bracket where Duke wins it all!
I'll be coming back to Tournament Simulations and breakdowns throughout the weekend and into next week. Thanks for visiting Immaculate Inning for your tourney prognostication needs!
Labels:
Duke,
NCAA Tourney,
picks,
predictions
Tuesday, March 17, 2009
Upset Special!
Hello again, welcome back to Immaculate Inning as we continue our week-long dive into the NCAA tournament, simulation style. In case you missed the posts, I've simulated the tournament one million times, and I've pulled from the data the most likely championship games and final fours. The link to the all-mighty spreadsheet (here).
This time I'm going to take a look much earlier in the tournament, as we fast approach the most exciting weekend of the sports year. Everybody loves a Cinderella, and everyone wants to brag about how they picked the upsets that filled the perfect brackets at work on Monday. This is going to be different from upset analysis you may have seen elsewhere, such as AccuScore, which simulates individual games 10,000 times. I've simulated the result of each game in the tournament once, then repeated that one million times. That number of simulations allows me to use statistical power that not even the flashy WhatifSports can match.
First, let's look at the upsets that are matters of probability; the efficiency ratings say, point blank, that the lower seed should be favored to win.
Upset Special #1: #10 Southern California (65.5%) over #7 Boston College (34.5%). The Trojans have the highest percentage of winning the first round game for any double-digit seed, and they might not have even been in the tournament if it weren't for capturing the Pac-10 tournament title. Both teams are strong on the offensive glass and weak on the defensive glass, and both teams don't take very many threes. This game could be a bruiser in the paint. One trouble spot for a USC upset potential is their poor free-throw ability; in a close game, Boston College has a clear edge there.
Upset Special #2: #12 Wisconsin (53.1%) over #5 Florida State (46.9%). As an avid fan of nearly all ACC teams when it comes to the tournament, this one hurts. The Seminoles enter the big dance as one of the hottest teams in the nation, knocking off (an admittedly wounded) North Carolina on the way to a runner-up finish in the ACC Tournament. Toney Douglas is exactly the kind of player that can go off in a big tournament and carry his team a long way. Wisconsin, meanwhile, is plodding-- 59.9 possessions is 334 out of 344 division 1 teams; is mistake-free-- #5 in turnovers/possession and #6 in steals/possession in the nation on offense. They also failed to win twenty games and have no one particularly scary. This is one where I personally would have a hard time following my own simulation, but they won just 0.82 games on average, by far the worst among the #5 seeds.
In terms of pure upsets predicted by the simulations, that's it for the first round. In general, if we were grading the committee based upon how well they matched higher seeded teams with higher Pomeroy efficiency ratings, they did pretty well. However, there are quite a few games that are "too close for comfort," when taking the seeds into account.
TCFC #1: #3 Kansas (80.7%) vs #14 North Dakota St (19.35%). NDSU, in their first tournament in their first year of eligibility, is a favorite upset pick among statheads like myself. The numbers were prettier a few weeks ago, but the Thundar (really? Thundar?) put up a pretty good offense for a minor-conference team. They can shoot lights out (40.2%, 10th in the nation), and Kansas hasn't defended the 3 very effectively this season. They also protect the ball pretty well (14th in turnovers/possession), while Kansas does not (244th). Bill Self's squad could be in trouble with this one.
TCFC #2: Dueling #13 seeds-- Mississippi St (23.8%) and Cleveland St (24.9%) both have much higher chances of knocking off their respective 4-seeds (Wake Forest and Washington). While the SEC champs would make for a nice story, the clear media favorite would be Cleveland St, a team which upset Butler in the Horizon league final to make the tournament. The Spiders won't spook anyone offensively, but they have a defense that is among the nation's best at taking the ball away. Washington, meanwhile, are in the middle of the pack in taking care of the ball, and their size should be more than enough to take care of Cleveland St. If I were the Huskies, I wouldn't be sleeping easy about a 1-in-4 chance of losing, however.
As for Wake Forest, I think we're noticing a trend; my simulation hates ACC teams not named Duke or Carolina. The other team not mentioned yet is Maryland, and my simulation has Maryland winning the fewest average games of any 10 seed, although they have a better shot at winning their opening round game than Michigan does, barely (35%). The folks filling out their bracket on ESPN disagree strongly, favoring Maryland over Cal 2-to-1.
Most casual bracket-fillers will lose interest after their brackets are busted by sometime Sunday evening; but the one who picks the correct surprise Sweet Sixteen teams is going to be the one bragging come Monday morning. So which low-seeded teams have the best chance to be standing after this weekend? These teams showed up in the Sweet Sixteen in at least ten percent of the simulations:
Wisconsin (#12 E): 26.5%
Southern California (#10 MW): 26.3%
Arizona (#12 MW): 17.9%
Michigan (#10 S): 10.9%
Minnesota (#10 E): 10.3%
I think it would be wise to be cautious about picking these #10 seeds to win two games this weekend. To see why, consider what the simulation was doing: picking at random (weighted by expected winning percentage) the winner of each game. So in some number of trials, the #2 seeds fell in the first round (Robert Morris and Morgan St. each won 8% of the time, for example). In those scenarios in which the #15 and #10 teams both won, the #10 seed is going to be a heavy favorite in the second round game. This inflates the chances of a #10 team making it to the second round; only a little bit has to do with the ability of the #10 seed to beat the #2 seed, by far the more likely opponent.
This is not the same with the #12 seed "Cinderellas" (not that major conference teams could ever count as such). Their upset win pits them, at worst, with a similarly-seeded #13 seed. Their high percentage really does suggest good matchups.
To finish, I present the best chances of winning two games this weekend, by seed:
1 seed: Louisville (80.23%)
2 seed: Memphis (83.98%)
3 seed: Missouri (60.50%)
4 seed: Gonzaga (68.66%)
5 seed: Purdue (47.16%)
6 seed: UCLA (54.30%)
7 seed: Clemson (34.66%)
8 seed: Brigham Young (24.29%)
9 seed: Tennessee (13.42%)
10 seed: Southern California (26.29%)
11 seed: Temple (9.05%)
12 seed: Wisconsin (26.51%)
13 seed: Cleveland St. (8.33%)
14 seed: North Dakota St. (4.01%)
15 seed: Robert Morris (1.62%)
16 seed: East Tennessee St. (1.09%)... yes, they have a 6% shot at beating Pittsburgh....
This time I'm going to take a look much earlier in the tournament, as we fast approach the most exciting weekend of the sports year. Everybody loves a Cinderella, and everyone wants to brag about how they picked the upsets that filled the perfect brackets at work on Monday. This is going to be different from upset analysis you may have seen elsewhere, such as AccuScore, which simulates individual games 10,000 times. I've simulated the result of each game in the tournament once, then repeated that one million times. That number of simulations allows me to use statistical power that not even the flashy WhatifSports can match.
First, let's look at the upsets that are matters of probability; the efficiency ratings say, point blank, that the lower seed should be favored to win.
Upset Special #1: #10 Southern California (65.5%) over #7 Boston College (34.5%). The Trojans have the highest percentage of winning the first round game for any double-digit seed, and they might not have even been in the tournament if it weren't for capturing the Pac-10 tournament title. Both teams are strong on the offensive glass and weak on the defensive glass, and both teams don't take very many threes. This game could be a bruiser in the paint. One trouble spot for a USC upset potential is their poor free-throw ability; in a close game, Boston College has a clear edge there.
Upset Special #2: #12 Wisconsin (53.1%) over #5 Florida State (46.9%). As an avid fan of nearly all ACC teams when it comes to the tournament, this one hurts. The Seminoles enter the big dance as one of the hottest teams in the nation, knocking off (an admittedly wounded) North Carolina on the way to a runner-up finish in the ACC Tournament. Toney Douglas is exactly the kind of player that can go off in a big tournament and carry his team a long way. Wisconsin, meanwhile, is plodding-- 59.9 possessions is 334 out of 344 division 1 teams; is mistake-free-- #5 in turnovers/possession and #6 in steals/possession in the nation on offense. They also failed to win twenty games and have no one particularly scary. This is one where I personally would have a hard time following my own simulation, but they won just 0.82 games on average, by far the worst among the #5 seeds.
In terms of pure upsets predicted by the simulations, that's it for the first round. In general, if we were grading the committee based upon how well they matched higher seeded teams with higher Pomeroy efficiency ratings, they did pretty well. However, there are quite a few games that are "too close for comfort," when taking the seeds into account.
TCFC #1: #3 Kansas (80.7%) vs #14 North Dakota St (19.35%). NDSU, in their first tournament in their first year of eligibility, is a favorite upset pick among statheads like myself. The numbers were prettier a few weeks ago, but the Thundar (really? Thundar?) put up a pretty good offense for a minor-conference team. They can shoot lights out (40.2%, 10th in the nation), and Kansas hasn't defended the 3 very effectively this season. They also protect the ball pretty well (14th in turnovers/possession), while Kansas does not (244th). Bill Self's squad could be in trouble with this one.
TCFC #2: Dueling #13 seeds-- Mississippi St (23.8%) and Cleveland St (24.9%) both have much higher chances of knocking off their respective 4-seeds (Wake Forest and Washington). While the SEC champs would make for a nice story, the clear media favorite would be Cleveland St, a team which upset Butler in the Horizon league final to make the tournament. The Spiders won't spook anyone offensively, but they have a defense that is among the nation's best at taking the ball away. Washington, meanwhile, are in the middle of the pack in taking care of the ball, and their size should be more than enough to take care of Cleveland St. If I were the Huskies, I wouldn't be sleeping easy about a 1-in-4 chance of losing, however.
As for Wake Forest, I think we're noticing a trend; my simulation hates ACC teams not named Duke or Carolina. The other team not mentioned yet is Maryland, and my simulation has Maryland winning the fewest average games of any 10 seed, although they have a better shot at winning their opening round game than Michigan does, barely (35%). The folks filling out their bracket on ESPN disagree strongly, favoring Maryland over Cal 2-to-1.
Most casual bracket-fillers will lose interest after their brackets are busted by sometime Sunday evening; but the one who picks the correct surprise Sweet Sixteen teams is going to be the one bragging come Monday morning. So which low-seeded teams have the best chance to be standing after this weekend? These teams showed up in the Sweet Sixteen in at least ten percent of the simulations:
Wisconsin (#12 E): 26.5%
Southern California (#10 MW): 26.3%
Arizona (#12 MW): 17.9%
Michigan (#10 S): 10.9%
Minnesota (#10 E): 10.3%
I think it would be wise to be cautious about picking these #10 seeds to win two games this weekend. To see why, consider what the simulation was doing: picking at random (weighted by expected winning percentage) the winner of each game. So in some number of trials, the #2 seeds fell in the first round (Robert Morris and Morgan St. each won 8% of the time, for example). In those scenarios in which the #15 and #10 teams both won, the #10 seed is going to be a heavy favorite in the second round game. This inflates the chances of a #10 team making it to the second round; only a little bit has to do with the ability of the #10 seed to beat the #2 seed, by far the more likely opponent.
This is not the same with the #12 seed "Cinderellas" (not that major conference teams could ever count as such). Their upset win pits them, at worst, with a similarly-seeded #13 seed. Their high percentage really does suggest good matchups.
To finish, I present the best chances of winning two games this weekend, by seed:
1 seed: Louisville (80.23%)
2 seed: Memphis (83.98%)
3 seed: Missouri (60.50%)
4 seed: Gonzaga (68.66%)
5 seed: Purdue (47.16%)
6 seed: UCLA (54.30%)
7 seed: Clemson (34.66%)
8 seed: Brigham Young (24.29%)
9 seed: Tennessee (13.42%)
10 seed: Southern California (26.29%)
11 seed: Temple (9.05%)
12 seed: Wisconsin (26.51%)
13 seed: Cleveland St. (8.33%)
14 seed: North Dakota St. (4.01%)
15 seed: Robert Morris (1.62%)
16 seed: East Tennessee St. (1.09%)... yes, they have a 6% shot at beating Pittsburgh....
Labels:
NCAA Tourney,
predictions,
upsets
The Most Likely Final Four
Sorry that it has taken so long since my last post, I know that the masses are in need of more data, and help filling out their brackets. I have been working on a Python script to parse the massive amounts of data I produced with my 1 million NCAA tournament simulations. Essentially, what resulted is a data file containing the winners of each game in a single simulation; that file is 611 MB, if you were wondering. What I have done is pull out from that massive file the most common Final Fours and the most common Championship games, which I will present in a minute.
Yesterday was the most successful day in Immaculate Inning history, with over 740 unique visitors, most of you coming from BallHype.com. I want to take a minute and point out some differences between what you'll find here and what other sites are producing. First, I noticed this article by the Wages of Wins Journal-- they do basically what I did for the ACC tournament, using both Pomeroy and Sagarin ratings. It's important to remember that the data on that site is discrete probabilities multiplied against each other; it's impossible to know how the winner of one game will affect the rest of the tournament.
Next, we have Joel Sokol of Georgia Tech, who uses a logarithmic regression model, based solely on margin of victory, to rank every team in Division I. He selects his bracket by picking the team that ranks higher, and according to his analysis, this method outperforms every other major bracket-picking method, whether it's seeds, ESPN's experts, or Sagarin rankings. That's pretty impressive, but once again, his choices do not take into account the effect of upsets on a single tournament.
Finally, there's a competing NCAA tourney simulation by Upon Further Review. There are two main differences between that simulation and mine. First, and perhaps most important; he doesn't show his work. A cursory look at the rest of the website shows a predilection for Basketball Prospectus, so perhaps we can assume he used efficiency ratings, but we just don't know. The second difference is that his is just 1,000 simulations. I'll admit that it doesn't seem obvious at first why having 1,000 times more simulations is necessarily better, other than the novelty of seeing Alabama State winning the tournament one or two times. I'm hoping to convince folks that the one million simulations really are better, because I can produce results like these: (click here to view the full spreadsheet)
The Most Likely Championship Game: Connecticut vs Pittsburgh
I searched my simulation output file for the winners of the initial final four matchups-- the championship game participants. There were 840 different matchups in the one million simulations. The championship games appearing in at least 1% (1,000) simulations, in order of decreasing likelihood:
Connecticut / Pittsburgh : 2.21%
Memphis / Pittsburgh : 1.86%
Louisville / Pittsburgh : 1.71%
Connecticut / Duke : 1.66%
Connecticut / North Carolina : 1.59%
Memphis / Duke : 1.43%
Memphis / North Carolina : 1.33%
Connecticut / Gonzaga : 1.31%
Louisville / Duke : 1.29%
Connecticut / Oklahoma : 1.28%
Connecticut / Syracuse : 1.27%
Louisville / North Carolina : 1.26%
Connecticut / Arizona St. : 1.22%
Connecticut / UCLA : 1.22%
Memphis / Gonzaga : 1.12%
West Virginia / Pittsburgh : 1.11%
Memphis / Syracuse : 1.09%
Memphis / Oklahoma : 1.09%
Louisville / Gonzaga : 1.02%
Memphis / UCLA : 1.02%
Memphis / Arizona St. : 1.02%
I'm fairly confident that a simulation of only 1,000 tournaments would be unable to separate the occurrence of one game versus another with any kind of power. As you can see, the first three most likely Championship Games include Pittsburgh. UCLA and Arizona St, both six seeds, are the lowest seeds commonly making an appearance in these most likely title game matchups. The left side of the bracket, representing the West/Midwest half of the tournament, appears a lot more stable than the right side; with one exception (WV), just three teams are represented: Louisville, Connecticut, and Memphis. The right side of the bracket, meanwhile, has a lot more variability, with three teams from the East and four from the South each making an appearance in the likely title games list.
In case you're worried about my arbitrary cutoff of 1%, the next three most common championship games all featured Louisville (vs Syracuse, Oklahoma, and UCLA), followed by a Michigan St-Pittsburgh matchup and yet another Louisville game (vs Arizona St). Following a unique matchup between Purdue and Pittsburgh at 0.90%, there is a sharp dropoff in the frequency. The first 25 or so matchups are clearly the most common, and therefore the most likely. I suppose it means that if you are looking for a sure thing, Pittsburgh is a good bet to make the title game. However, if you're looking for a sleeper (not a #1 or #2 seed) to make the title game, it would be better to replace Pittsburgh with UCLA, Arizona St, or Gonzaga, because low seeds making the title game out of the West and Midwest is just not likely.
The Most Likely Final Four: Connecticut, Louisville, Pittsburgh, Oklahoma
As a Duke fan, I was saddened that Duke did not represent the East region in the most likely final four. However, I am overjoyed that the only non-#1 seed to be there is North Carolina...
The power of the #1 seeds was actually quite strong-- the first five most likely brackets, representing nearly 1 percent of all simulations, featured UConn, Louisville, and Pittsburgh (one of which also included North Carolina). Anyway, there are 26,790 unique final fours in the simulation, 6,134 of which appear only once. Only 2,434 Final Fours occured more than 100 times (0.01 percent). The most likely final four, listed above, occured 2009 times (how's that for symmetry), or 0.2 percent.
Once again, the top heavy nature of the West region was clear; it was not until the 42nd most common final four that the West representative was not Connecticut or Memphis (it was Purdue). The first nine most common final fours list Louisville as the Midwest champ, and some sprinklings of West Virginia and Michigan State follow until the 37th most likely final four, which features Kanas. In the East, Pitt did capture those first five spots, and most of the top 20 (replaced by Duke in five of them, then UCLA in the 21st most likely final four). The first team to come out of the East that was not Pitt, Duke, or UCLA was Xavier in the 48th most likely Final Four. Finally, the South is just as wide open as we've been advertising, with five different teams in the first five most likely scenarios!
What does all of this mean for you, humble bracket filler? It means that under the most common bracket pool rules, (more points for late round games than early round) someone is going to win the pool by picking the correct South regional winner. The other regions are farily top-heavy with just a few likely options, but the South is where the money is at. These breakdowns don't really point to a favorite in the five-team cluster, although the initial simulation calls North Carolina the favorite.
It is a bit strange to note that Memphis is neither in the most likely title game, nor the most likely Final Four. They were a slight favorite to win the tournament in the initial simulation, just beating out UConn. I suppose you could say that whoever wins the West regional should be the odds-on favorite to capture the title!
Xenod and I are working on expanding the search through the simulation to incorporate the Elite Eight and Sweet Sixteen. I'm not sure if 1 million is enough to tease apart the variance at those levels, but we will try. I'll also take a look at first and second round matchups from a different perspective. Stay tuned to all the tourney simulations you can handle, right here at Immaculate Inning!
Yesterday was the most successful day in Immaculate Inning history, with over 740 unique visitors, most of you coming from BallHype.com. I want to take a minute and point out some differences between what you'll find here and what other sites are producing. First, I noticed this article by the Wages of Wins Journal-- they do basically what I did for the ACC tournament, using both Pomeroy and Sagarin ratings. It's important to remember that the data on that site is discrete probabilities multiplied against each other; it's impossible to know how the winner of one game will affect the rest of the tournament.
Next, we have Joel Sokol of Georgia Tech, who uses a logarithmic regression model, based solely on margin of victory, to rank every team in Division I. He selects his bracket by picking the team that ranks higher, and according to his analysis, this method outperforms every other major bracket-picking method, whether it's seeds, ESPN's experts, or Sagarin rankings. That's pretty impressive, but once again, his choices do not take into account the effect of upsets on a single tournament.
Finally, there's a competing NCAA tourney simulation by Upon Further Review. There are two main differences between that simulation and mine. First, and perhaps most important; he doesn't show his work. A cursory look at the rest of the website shows a predilection for Basketball Prospectus, so perhaps we can assume he used efficiency ratings, but we just don't know. The second difference is that his is just 1,000 simulations. I'll admit that it doesn't seem obvious at first why having 1,000 times more simulations is necessarily better, other than the novelty of seeing Alabama State winning the tournament one or two times. I'm hoping to convince folks that the one million simulations really are better, because I can produce results like these: (click here to view the full spreadsheet)
The Most Likely Championship Game: Connecticut vs Pittsburgh
I searched my simulation output file for the winners of the initial final four matchups-- the championship game participants. There were 840 different matchups in the one million simulations. The championship games appearing in at least 1% (1,000) simulations, in order of decreasing likelihood:
Connecticut / Pittsburgh : 2.21%
Memphis / Pittsburgh : 1.86%
Louisville / Pittsburgh : 1.71%
Connecticut / Duke : 1.66%
Connecticut / North Carolina : 1.59%
Memphis / Duke : 1.43%
Memphis / North Carolina : 1.33%
Connecticut / Gonzaga : 1.31%
Louisville / Duke : 1.29%
Connecticut / Oklahoma : 1.28%
Connecticut / Syracuse : 1.27%
Louisville / North Carolina : 1.26%
Connecticut / Arizona St. : 1.22%
Connecticut / UCLA : 1.22%
Memphis / Gonzaga : 1.12%
West Virginia / Pittsburgh : 1.11%
Memphis / Syracuse : 1.09%
Memphis / Oklahoma : 1.09%
Louisville / Gonzaga : 1.02%
Memphis / UCLA : 1.02%
Memphis / Arizona St. : 1.02%
I'm fairly confident that a simulation of only 1,000 tournaments would be unable to separate the occurrence of one game versus another with any kind of power. As you can see, the first three most likely Championship Games include Pittsburgh. UCLA and Arizona St, both six seeds, are the lowest seeds commonly making an appearance in these most likely title game matchups. The left side of the bracket, representing the West/Midwest half of the tournament, appears a lot more stable than the right side; with one exception (WV), just three teams are represented: Louisville, Connecticut, and Memphis. The right side of the bracket, meanwhile, has a lot more variability, with three teams from the East and four from the South each making an appearance in the likely title games list.
In case you're worried about my arbitrary cutoff of 1%, the next three most common championship games all featured Louisville (vs Syracuse, Oklahoma, and UCLA), followed by a Michigan St-Pittsburgh matchup and yet another Louisville game (vs Arizona St). Following a unique matchup between Purdue and Pittsburgh at 0.90%, there is a sharp dropoff in the frequency. The first 25 or so matchups are clearly the most common, and therefore the most likely. I suppose it means that if you are looking for a sure thing, Pittsburgh is a good bet to make the title game. However, if you're looking for a sleeper (not a #1 or #2 seed) to make the title game, it would be better to replace Pittsburgh with UCLA, Arizona St, or Gonzaga, because low seeds making the title game out of the West and Midwest is just not likely.
The Most Likely Final Four: Connecticut, Louisville, Pittsburgh, Oklahoma
As a Duke fan, I was saddened that Duke did not represent the East region in the most likely final four. However, I am overjoyed that the only non-#1 seed to be there is North Carolina...
The power of the #1 seeds was actually quite strong-- the first five most likely brackets, representing nearly 1 percent of all simulations, featured UConn, Louisville, and Pittsburgh (one of which also included North Carolina). Anyway, there are 26,790 unique final fours in the simulation, 6,134 of which appear only once. Only 2,434 Final Fours occured more than 100 times (0.01 percent). The most likely final four, listed above, occured 2009 times (how's that for symmetry), or 0.2 percent.
Once again, the top heavy nature of the West region was clear; it was not until the 42nd most common final four that the West representative was not Connecticut or Memphis (it was Purdue). The first nine most common final fours list Louisville as the Midwest champ, and some sprinklings of West Virginia and Michigan State follow until the 37th most likely final four, which features Kanas. In the East, Pitt did capture those first five spots, and most of the top 20 (replaced by Duke in five of them, then UCLA in the 21st most likely final four). The first team to come out of the East that was not Pitt, Duke, or UCLA was Xavier in the 48th most likely Final Four. Finally, the South is just as wide open as we've been advertising, with five different teams in the first five most likely scenarios!
What does all of this mean for you, humble bracket filler? It means that under the most common bracket pool rules, (more points for late round games than early round) someone is going to win the pool by picking the correct South regional winner. The other regions are farily top-heavy with just a few likely options, but the South is where the money is at. These breakdowns don't really point to a favorite in the five-team cluster, although the initial simulation calls North Carolina the favorite.
It is a bit strange to note that Memphis is neither in the most likely title game, nor the most likely Final Four. They were a slight favorite to win the tournament in the initial simulation, just beating out UConn. I suppose you could say that whoever wins the West regional should be the odds-on favorite to capture the title!
Xenod and I are working on expanding the search through the simulation to incorporate the Elite Eight and Sweet Sixteen. I'm not sure if 1 million is enough to tease apart the variance at those levels, but we will try. I'll also take a look at first and second round matchups from a different perspective. Stay tuned to all the tourney simulations you can handle, right here at Immaculate Inning!
Labels:
Final Four,
NCAA Tourney,
predictions,
simulation
Sunday, March 15, 2009
NCAA Tournament Predictions Using Simulations
If you're looking for 2010 NCAA Tournament Simulations, you can find Immaculate Inning's One Million Simulations right here!
It's been a crazy Championship Week across the NCAA, and parity ruled supreme across the land, leaving many college basketball fans scratching their heads as they attempt to fill out their brackets. Well, we at the Immaculate Inning have a treat for you: a complete breakdown of the recently NCAA bracket based on the log5 prediction system and Ken Pomeroy's efficiency ratings. I did this for the ACC tournament by painstakingly filling out an Excel spreadsheet and running the numbers essentially by hand. This time was a bit different.
The Method. Briefly, this simulation takes in the "Expected Winning Percentage" calculated by taking the number of points a team scores and allows and transforming it into a win percentage. Instead of using raw scoring figures, I'm using the metrics invented by Ken Pomeroy, which take the tempo of a game out of the equation- we're dealing with how efficient a team's offense or defense is. Next, using the log5 prediction method (linked above), we can calculate how often a team with a given winning percentage is likely to beat another team with a given win percentage. For example, a team with a .600 win percentage is projected to beat a team with a .400 win percentage 69.2% of the time.
How well a team does in the NCAA tournament is affected by three things: how good a team is, how good their opponents are, and how likely it is to see a particular opponent. So while Louisiana State may salivate at the possibility of playing Radford in the second round of the tournament, it's just not likely to happen. For the ACC tournament, I calculated discrete probabilities for each matchup. This is where I've done things a bit different. I have created a computer simulation (a script in the Python language, thanks to Xenod for guidance and helpful tips) for the NCAA tournament, and then I run it a bunch of times. The outcome of each game is random, weighted by the expected winning percentage of each team. The result is not just another table of log5 projections, but is the result of 1 million simulated NCAA tournaments. It's how the tournament looks, "on paper."
So how did your favorite team fare in my simulations? Take a look at the spreadsheet below to find out! (It can also be accessed here for your sorting pleasure.)
The spreadsheet has tabs for each region; they are currently sorted by the "4" column, which is the chances that a given team will win "at least 4" games. That is, it is the chances that a team will win its region, advancing to the Final Four in Detroit. The other columns are similar, recording the percentage chance a team will win that many games. The difference is the "All Teams" tab, which is sorted by "Average Wins." This is the average number of wins a team accrued across the 1 million simulations. It ranges from Memphis (2.81 wins) to Chattanooga (0.02 wins).
Now that all the data is out there, what does it mean? I believe this data can tell us a great deal about how the tournament was set up by the committee, and who has the "hardest" and "easiest" roads to the Final Four and the national title. To begin, the finding that Memphis has not only the largest number of average wins, but also the highest chances of winning the title, is not surprising. Pomeroy's ratings place Memphis squarely atop the nation, led by an amazing team defense. John Calipari's team continues to get little respect nationally despite three straight regional final appearances. The statistics say there is a high probability they will make it four straight.
The South region has the most parity, with five teams winning four games (and the region) at least 10% of the time. Interestingly, top-seed North Carolina ranks third in Final Four appearances from this group, behind Oklahoma and Syracuse. However, if North Carolina does survive the region, they have by far the highest number of national titles (5.68%) from the South region.
Six teams made the national championship game in at least ten percent of the simulations: Connecticut, Louisville, Pittsburgh, Memphis, and Duke. Obviously, only one of the UConn-Memphis and Pitt-Duke pairs can make the title game, but I think it speaks to the lower overall level of performance from teams in the West and East regionals. Indeed, in those regions, the #1 and #2 seeds accounted for the regions' champion more than 40% of the time, while in the Midwest, Louisville and Michigan state came close (39.9%). The South, meanwhile, lags far behind- the champ was either UNC or OK just 32% of the time.
Among the lower seeds, three of the #6 seeds stand out as having higher than average chances of going to Detroit. West Virginia, ranked highly by Pomeroy all season, is the highest non-1-or-2 in terms of Final Four percentage, at 15.74%. Their first round matchup against Dayton ranks as one of the least upset prone games of the first round. How West Virginia fares in this tournament is perhaps a test case to the Pomeroy method-- how important are wins and losses, really, when you play pretty well in all those losses?
A similar case is UCLA, given a 6 seed in the East region despite having one of the best offenses in the country, statistically speaking. While their opening round game against VCU is no joke (and this Duke fan would know about that), they have the greatest chances of an Elite Eight appearance other than Duke and Pitt in this region. A third six-seed with high hopes could be Arizona State, in the apparently wide open South regional. Should ASU get past a tough Temple matchup in the first round, my simulator likes their chances against either Syracuse. Marquette is the odd six seed out in the simulations, with the lowest number of 1 win and 2 win simulations for six seeds.
I will have much more on these simulations in the coming days, eventually culminating in The Immaculate Inning Most Likely Bracket-- which of the 9 quadrillion possible baskets would Pomeroy's efficiency rating tell us to fill out?
If you have any suggestions on what kind of data analysis to do, how to improve the method, or if you'd like a copy of my Tournament Simulation script, comment here or shoot me an e-mail at mehmattski AT gmail DOT com. March Madness baby!
It's been a crazy Championship Week across the NCAA, and parity ruled supreme across the land, leaving many college basketball fans scratching their heads as they attempt to fill out their brackets. Well, we at the Immaculate Inning have a treat for you: a complete breakdown of the recently NCAA bracket based on the log5 prediction system and Ken Pomeroy's efficiency ratings. I did this for the ACC tournament by painstakingly filling out an Excel spreadsheet and running the numbers essentially by hand. This time was a bit different.
The Method. Briefly, this simulation takes in the "Expected Winning Percentage" calculated by taking the number of points a team scores and allows and transforming it into a win percentage. Instead of using raw scoring figures, I'm using the metrics invented by Ken Pomeroy, which take the tempo of a game out of the equation- we're dealing with how efficient a team's offense or defense is. Next, using the log5 prediction method (linked above), we can calculate how often a team with a given winning percentage is likely to beat another team with a given win percentage. For example, a team with a .600 win percentage is projected to beat a team with a .400 win percentage 69.2% of the time.
How well a team does in the NCAA tournament is affected by three things: how good a team is, how good their opponents are, and how likely it is to see a particular opponent. So while Louisiana State may salivate at the possibility of playing Radford in the second round of the tournament, it's just not likely to happen. For the ACC tournament, I calculated discrete probabilities for each matchup. This is where I've done things a bit different. I have created a computer simulation (a script in the Python language, thanks to Xenod for guidance and helpful tips) for the NCAA tournament, and then I run it a bunch of times. The outcome of each game is random, weighted by the expected winning percentage of each team. The result is not just another table of log5 projections, but is the result of 1 million simulated NCAA tournaments. It's how the tournament looks, "on paper."
So how did your favorite team fare in my simulations? Take a look at the spreadsheet below to find out! (It can also be accessed here for your sorting pleasure.)
The spreadsheet has tabs for each region; they are currently sorted by the "4" column, which is the chances that a given team will win "at least 4" games. That is, it is the chances that a team will win its region, advancing to the Final Four in Detroit. The other columns are similar, recording the percentage chance a team will win that many games. The difference is the "All Teams" tab, which is sorted by "Average Wins." This is the average number of wins a team accrued across the 1 million simulations. It ranges from Memphis (2.81 wins) to Chattanooga (0.02 wins).
Now that all the data is out there, what does it mean? I believe this data can tell us a great deal about how the tournament was set up by the committee, and who has the "hardest" and "easiest" roads to the Final Four and the national title. To begin, the finding that Memphis has not only the largest number of average wins, but also the highest chances of winning the title, is not surprising. Pomeroy's ratings place Memphis squarely atop the nation, led by an amazing team defense. John Calipari's team continues to get little respect nationally despite three straight regional final appearances. The statistics say there is a high probability they will make it four straight.
The South region has the most parity, with five teams winning four games (and the region) at least 10% of the time. Interestingly, top-seed North Carolina ranks third in Final Four appearances from this group, behind Oklahoma and Syracuse. However, if North Carolina does survive the region, they have by far the highest number of national titles (5.68%) from the South region.
Six teams made the national championship game in at least ten percent of the simulations: Connecticut, Louisville, Pittsburgh, Memphis, and Duke. Obviously, only one of the UConn-Memphis and Pitt-Duke pairs can make the title game, but I think it speaks to the lower overall level of performance from teams in the West and East regionals. Indeed, in those regions, the #1 and #2 seeds accounted for the regions' champion more than 40% of the time, while in the Midwest, Louisville and Michigan state came close (39.9%). The South, meanwhile, lags far behind- the champ was either UNC or OK just 32% of the time.
Among the lower seeds, three of the #6 seeds stand out as having higher than average chances of going to Detroit. West Virginia, ranked highly by Pomeroy all season, is the highest non-1-or-2 in terms of Final Four percentage, at 15.74%. Their first round matchup against Dayton ranks as one of the least upset prone games of the first round. How West Virginia fares in this tournament is perhaps a test case to the Pomeroy method-- how important are wins and losses, really, when you play pretty well in all those losses?
A similar case is UCLA, given a 6 seed in the East region despite having one of the best offenses in the country, statistically speaking. While their opening round game against VCU is no joke (and this Duke fan would know about that), they have the greatest chances of an Elite Eight appearance other than Duke and Pitt in this region. A third six-seed with high hopes could be Arizona State, in the apparently wide open South regional. Should ASU get past a tough Temple matchup in the first round, my simulator likes their chances against either Syracuse. Marquette is the odd six seed out in the simulations, with the lowest number of 1 win and 2 win simulations for six seeds.
I will have much more on these simulations in the coming days, eventually culminating in The Immaculate Inning Most Likely Bracket-- which of the 9 quadrillion possible baskets would Pomeroy's efficiency rating tell us to fill out?
If you have any suggestions on what kind of data analysis to do, how to improve the method, or if you'd like a copy of my Tournament Simulation script, comment here or shoot me an e-mail at mehmattski AT gmail DOT com. March Madness baby!
Labels:
NCAA Tourney,
predictions,
simulation
Friday, March 13, 2009
Updated ACC Tourney Probabilities
With the first six games in the ACC Tournament complete, let's revisit the log5 predictions, which are based on tempo-free efficiency ratings accrued in ACC games only:
These are up to date following FSU's escape of Georgia Tech in the second afternoon game. As you can see, North Carolina has increased their chances of winning the tournament to better than 50/50. Duke's tournament chances have actually gone down, caused by no longer having the possibility of playing Virginia. Both of tonight's quarterfinal games have a similar 4-to-1 advantage for favorites Duke and Wake Forest. Maryland doesn't have much of a chance of winning the tournament, but should they pull the upset tonight, would that be enough to get the ACC a seventh team in Teh Dance?
The other story lines remaining in the ACC tournament are all about seedings. Carolina probably locked up their #1 seed with a win, considering that they're actually still playing, unlike UConn, Pitt, and Oklahoma. The ACC results are not in a vaccuum, the seedings of Duke and Wake are heavily influenced by the results of the other tournaments. For example, someone upsetting Memphis or Louisville capturing the Big East tournament would have top-seeded implications.
Stay tuned to Immaculate Inning for all your March Madness projection needs. We've got a big project in the works to unveil late Sunday or early Monday. NCAA Hoops- Awesome!
These are up to date following FSU's escape of Georgia Tech in the second afternoon game. As you can see, North Carolina has increased their chances of winning the tournament to better than 50/50. Duke's tournament chances have actually gone down, caused by no longer having the possibility of playing Virginia. Both of tonight's quarterfinal games have a similar 4-to-1 advantage for favorites Duke and Wake Forest. Maryland doesn't have much of a chance of winning the tournament, but should they pull the upset tonight, would that be enough to get the ACC a seventh team in Teh Dance?
The other story lines remaining in the ACC tournament are all about seedings. Carolina probably locked up their #1 seed with a win, considering that they're actually still playing, unlike UConn, Pitt, and Oklahoma. The ACC results are not in a vaccuum, the seedings of Duke and Wake are heavily influenced by the results of the other tournaments. For example, someone upsetting Memphis or Louisville capturing the Big East tournament would have top-seeded implications.
Stay tuned to Immaculate Inning for all your March Madness projection needs. We've got a big project in the works to unveil late Sunday or early Monday. NCAA Hoops- Awesome!
Labels:
ACC Tournament,
predictions
Wednesday, March 11, 2009
ACC Conference Play: Devourer of Stats
A few weeks ago, I made a very critical post about the 2008-2009 Duke team. Having come off of a very poor stretch, the once promising Blue Devils seemed to be succumbing to conference play, with disastrous consequences. I concluded that Duke's pounding of non-conference foes was clouding our view of their standing, statistically speaking. Pomeroy's rankings simply cannot account for the evolution of a team throughout a season; they treat a November blowout win the same as a February blowout win. And conventional wisdom would treat the latter as more indicative of a team's chances in March.
With the ACC season complete I thought I'd take one final look at Duke's performance between conference and non-conference play. The result is not pretty:
In red are all the categories in which Duke is performing worse in ACC play compared to out of conference play (this includes 2009 games against Davidson, Georgetown, and St. John's). With the exception of turnovers on offense, Duke is not playing as well. But clearly, the level of play in the ACC must affect all teams. So I then tallied up every team's tempo-free performances. Rather than post another spreadsheet, the results can be found here. Some major points:
1) Nearly team saw both their offensive and defensive efficiencies drop when they were playing against ACC opponents. In fact, nearly every cell in the "Difference" part of my spreadsheet is colored red, meaning teams were also worse in other statistical categories. This probably makes sense, since the ACC is ranked the #1 conference by Pomeroy, and the #1 conference by Sagarin.
2) Overall, offense was less affected than defense. During ACC play, the conference teams averaged an efficiency of 104.5. Compared to the national average (100.1), it means that the ACC has an offense-heavy atmosphere. It would take further analysis to prove this point, but I believe this could have an effect similar to the "ballpark effect" in baseball; if the Oakland A's hit 300 home runs as a team, it would be more impressive than if the Colorado Rockies did it. By analogy I am suggesting that having a good offense in the ACC is not as impressive as having a good defense. This points a praising finger squarely at teams like FSU and Duke, the only teams to have defensive efficiency ratings below 100 during conference play.
3) Florida State is a major exception. While everyone elses' offensive efficiency was dropping, Florida State actually improved their offensive efficiency in conference play. A large part of this comes from another category-- turnover rate. Along with Duke, the Seminoles are one of two teams to improve their turnover rate on offense against ACC foes. Their effective field goal percentage and offensive rebounding rate were not as affected by conference play as well.
4) NC State is probably the biggest culprit of Cupcake Syndrome. The Wolfpack's offensive efficiency dropped by 8.4 points in ACC play (the worst drop the conference), and their defensive efficiency also dropped, by 18.0 points. They were an average team until January, and simply not a very good team in conference play.
5) There is no evidence for the conception "The ACC refs call more fouls than the rest of the nation." Collectively, the ACC teams went to the charity stripe during 35.4% of their possessions during league play, compared to 41.4% of possessions in non-conference play. While free throw rate is not a perfect proxy for the number of fouls called, it is obvious that the the ACC refs aren't as whistle happy as some would have you believe. On the other hand, during non-conference play, the opponents of ACC teams went to the free throw line in just 30.0% of possessions. There is certainly a connection between level of play and the number of fouls called; bad teams have bad defensive positioning and would tend to be whistled more often.
6) Continuing on the foul theme, Duke was near the top of free throw rate in conference (39.9%, 4th) and out of conference (46.2%, 3rd), but by no means any fuel for the DukeGetsAllTheCalls morons. In fact, every team (including Duke) saw their opponents go to the free throw line more frequently during ACC play, except one. That would be the Carolina Tar Heels, who inexplicably allowed free throws on 4% fewer possessions, compared to out of conference play. I'm not suggesting conspiracy, it's probably due to their Swiss cheese approach to half-court defense...
7) Wake Forest's defensive woes may be a bit misleading. Sure, they saw the biggest drop in defensive efficiency (19 points) of any team in the league. But, during league play they still have the best defensive effective field goal percentage, and the best defensive rebounding rate, of any team in the ACC. In this case, I'm guessing the problem was a cupcake pre-conference schedule (ranked 275th by Pomeroy), rather than some exposure by better competition.
8) Finally, we return to the most overanalyzed team in the country: Duke. It's amusing to me that any casual college basketball fan in the country right now can point to seven different reasons why the Blue Devils are not poised for greatness: they lack depth, they can't stop quick guards, they can't stop an inside presence, they don't play enough zone, they don't adapt in-game, ad nauseum. I wonder if those fans can note weaknesses so easily in other top 10 teams? Still, even I was receptive to this line of thinking a few weeks ago. But my comparison is clear: Duke is in the middle of the pack when it comes to their statistics being "affected" somehow by non-conference play.
In fact, contrary to my conclusions a few weeks ago, Duke's defense is one of the least affected by ACC play. On offense, Duke turns the ball over less frequently than any ACC team, and have respectable rebounding numbers for a team with "no inside presence." The lesson: stop making judgments in a vaccum; statistics can be misleading if they are not in a relative context.
With the ACC season complete I thought I'd take one final look at Duke's performance between conference and non-conference play. The result is not pretty:
In red are all the categories in which Duke is performing worse in ACC play compared to out of conference play (this includes 2009 games against Davidson, Georgetown, and St. John's). With the exception of turnovers on offense, Duke is not playing as well. But clearly, the level of play in the ACC must affect all teams. So I then tallied up every team's tempo-free performances. Rather than post another spreadsheet, the results can be found here. Some major points:
1) Nearly team saw both their offensive and defensive efficiencies drop when they were playing against ACC opponents. In fact, nearly every cell in the "Difference" part of my spreadsheet is colored red, meaning teams were also worse in other statistical categories. This probably makes sense, since the ACC is ranked the #1 conference by Pomeroy, and the #1 conference by Sagarin.
2) Overall, offense was less affected than defense. During ACC play, the conference teams averaged an efficiency of 104.5. Compared to the national average (100.1), it means that the ACC has an offense-heavy atmosphere. It would take further analysis to prove this point, but I believe this could have an effect similar to the "ballpark effect" in baseball; if the Oakland A's hit 300 home runs as a team, it would be more impressive than if the Colorado Rockies did it. By analogy I am suggesting that having a good offense in the ACC is not as impressive as having a good defense. This points a praising finger squarely at teams like FSU and Duke, the only teams to have defensive efficiency ratings below 100 during conference play.
3) Florida State is a major exception. While everyone elses' offensive efficiency was dropping, Florida State actually improved their offensive efficiency in conference play. A large part of this comes from another category-- turnover rate. Along with Duke, the Seminoles are one of two teams to improve their turnover rate on offense against ACC foes. Their effective field goal percentage and offensive rebounding rate were not as affected by conference play as well.
4) NC State is probably the biggest culprit of Cupcake Syndrome. The Wolfpack's offensive efficiency dropped by 8.4 points in ACC play (the worst drop the conference), and their defensive efficiency also dropped, by 18.0 points. They were an average team until January, and simply not a very good team in conference play.
5) There is no evidence for the conception "The ACC refs call more fouls than the rest of the nation." Collectively, the ACC teams went to the charity stripe during 35.4% of their possessions during league play, compared to 41.4% of possessions in non-conference play. While free throw rate is not a perfect proxy for the number of fouls called, it is obvious that the the ACC refs aren't as whistle happy as some would have you believe. On the other hand, during non-conference play, the opponents of ACC teams went to the free throw line in just 30.0% of possessions. There is certainly a connection between level of play and the number of fouls called; bad teams have bad defensive positioning and would tend to be whistled more often.
6) Continuing on the foul theme, Duke was near the top of free throw rate in conference (39.9%, 4th) and out of conference (46.2%, 3rd), but by no means any fuel for the DukeGetsAllTheCalls morons. In fact, every team (including Duke) saw their opponents go to the free throw line more frequently during ACC play, except one. That would be the Carolina Tar Heels, who inexplicably allowed free throws on 4% fewer possessions, compared to out of conference play. I'm not suggesting conspiracy, it's probably due to their Swiss cheese approach to half-court defense...
7) Wake Forest's defensive woes may be a bit misleading. Sure, they saw the biggest drop in defensive efficiency (19 points) of any team in the league. But, during league play they still have the best defensive effective field goal percentage, and the best defensive rebounding rate, of any team in the ACC. In this case, I'm guessing the problem was a cupcake pre-conference schedule (ranked 275th by Pomeroy), rather than some exposure by better competition.
8) Finally, we return to the most overanalyzed team in the country: Duke. It's amusing to me that any casual college basketball fan in the country right now can point to seven different reasons why the Blue Devils are not poised for greatness: they lack depth, they can't stop quick guards, they can't stop an inside presence, they don't play enough zone, they don't adapt in-game, ad nauseum. I wonder if those fans can note weaknesses so easily in other top 10 teams? Still, even I was receptive to this line of thinking a few weeks ago. But my comparison is clear: Duke is in the middle of the pack when it comes to their statistics being "affected" somehow by non-conference play.
In fact, contrary to my conclusions a few weeks ago, Duke's defense is one of the least affected by ACC play. On offense, Duke turns the ball over less frequently than any ACC team, and have respectable rebounding numbers for a team with "no inside presence." The lesson: stop making judgments in a vaccum; statistics can be misleading if they are not in a relative context.
Labels:
ACC Tournament,
Duke,
Pomeroy Stats
Monday, March 09, 2009
2009 ACC Tournament Predictions
Some of the hardest days as a sports fan come during early March; the worst of all are the four days between Selection Sunday and the first full day of NCAA tournament games. For this ACC fan, it is equally hard to bear the four days between the Duke-Carolina rematch and the start of the ACC tournament. Sure, there are plenty of actual games between now and then, but few of them actually matter, save the random upset of a top 25 mid-major and the corresponding bubble implications. To pass the time, I repeated an exercise I completed two years ago this week: predictions for the ACC tournament using the log5 method.
There will no doubt be predictions using Ken Pomeroy's rating system, all over the internet. (Here's one simple example.) I want to do something different; how do the predictions change, based on whether I use:
1) Winning Percentage
2) Raw Points Scored/Allowed
3) Pomeroy's Rankings (Full Season)
4) Raw Efficiency (ACC Games Only)
What follows are four Google spreadsheets tallying the information. Each sheet has three tabs: the calcuated winning percentage for each team. For tests 2 through 4, my formula follows Ken Pomeroy's: PF^11.5/(PF^11.5+PA^11.5). The next tab shows the chances that the team in a given column will beat the team listed in a row, using the "log5" formula, discussed here. Finally, mindful of the ACC Tournament Bracket, I predict each team's chances to advance to the Quarterfinals, Semifinals, Finals, and their chances of being 2009 ACC Champion. Let's start with raw winning percentage.
So you can see that Duke has an .806 winning percentage, a 31.6% chance of beating UNC, and a 15. 6% chance of winning the ACC tournament. Of course, winning percentage is kind of silly, because blowouts and squeakers count exactly the same. For this reason many baseball stat-heads turned to Pythagorean Win Percentage, which calculates a team's likely winning percentage given how much they score and how much they allow. This can be applied to basketball as well, with the following result:
Some pretty big changes already. First off, Duke has vaulted above Wake and is now favored to make the finals against a still-overwhelmingly-favored UNC team. The middle of the pack has changed considerably; Miami has doubled their chances, while Clemson has had theirs halved. We know that the Pythagorean Winning Percentage is flawed, Baseball Prospectus also follows what they call "Third Order Wins." By this they mean that how much offense/defense is not as important as the context in which the points were scored.To put it in 2009 terms, which team has the better offense:
VMI-- Points/Game: 93.8 Possessions/Game: 81.2
Duke- Points/Game: 78.7 Possessions/Game: 70.1
It is true that VMI scores 15 more points per contest than the Blue Devils; they are the most prolific scorers in the nation. However, VMI plays at the fastest tempo in the country, getting over 11 possessions more per game than Duke. Teams play different opponents every game, which could have a wide variance in the number of possessions. So, a fair comparison of offenses requires looking not at a team's raw scoring numbers, but at how efficiently a team scores in the possessions it gets. With this, it is clear that Duke has the better offense.
So what if we were to predict the results of the ACC tournament using Offensive and Defensive Efficiency, as provided by Ken Pomeroy? For this run I will also take each team's schedule into account by using Pomeroy's "Adjusted" efficiency ratings; teams are penalized if they run up high efficiencies against bottom feeding teams. The results are provided in an earlier link, but I'm showing my work:
While the chances of favorite UNC have remained largely the same, the effect of tempo-free statistics and the schedule have boosted Duke's chances by 5%. Most of this comes from an ever-increasing chance of beating Wake Forest on a neutral court: from 46% using just win percentage to 56% with Pythagoras to 62% tempo-free.
Frequently, when I use these tempo-free statistics, some folks are not convinced. They think that the adjustments for schedule made by Pomeroy are not enough, and that teams are different in league play than they were playing non-league foes before the new year. In addition, the ACC tournament is taking place between only ACC teams, so shouldn't statistics within the ACC matter more? On the other hand, the ACC no longer has a balanced schedule; for example, Boston College played Duke once (at home) while they played #12 seed Georgia Tech twice. I have not attempted to adjust for schedule here, so these are raw efficiency numbers:
The most striking result is that the top three teams (UNC, Duke, Wake) have had their chances all go down, relative to the full-season Pomeroy ratings. These extra chances have been split among a few teams. Clemson's title chances went up by 3 percentage points. Florida State, whose defense has improved tremendously since the clock ticked to 2009, have doubled their title chances (as have Boston College).
NCAA Tournament Implications:
1) The 8-9 game is not the closest of the first round. That distinction belongs to NCSU vs Maryland, according to all four metrics. That is not a good matchup for anyone who thinks that Maryland is still on the bubble.
2) Virginia Tech is pretty screwed. Like Maryland, they are a 7-9 ACC team, and the committee doesn't usually take kindly to a sub-.500 conference record. They are probably out of the tournament picture unless they make it deep, and the statistics say it's not probable at all.
3) The final 7-9 team, Miami, has to avoid a collapse against Virginia Tech, and then they face 2-to-1 odds against in the matchup with Wake Forest. Should they prevail, would the committee consider what then would be a 20-win ACC team?
4) Statistically, the top three seeds are very heavy favorites for the semifinals, with Duke and UNC more likely to be there than Wake. Should Duke win the two games as expected, would they still have to beat Wake Forest to get a #2 seed in the NCAAT? Certainly, the Deacons probably need to win the ACC tournament to get their own #2 seed.
5) Clemson and Florida State should both be solidly into the NCAA tourament, but they are playing for favorable seedings. By the ACC numbers and the overall Pomeroy ratings, Clemson is favored in a matchup with Florida State, and the Tigers are more likely to knock off UNC.
6) Spreadsheets are fun!
There will no doubt be predictions using Ken Pomeroy's rating system, all over the internet. (Here's one simple example.) I want to do something different; how do the predictions change, based on whether I use:
1) Winning Percentage
2) Raw Points Scored/Allowed
3) Pomeroy's Rankings (Full Season)
4) Raw Efficiency (ACC Games Only)
What follows are four Google spreadsheets tallying the information. Each sheet has three tabs: the calcuated winning percentage for each team. For tests 2 through 4, my formula follows Ken Pomeroy's: PF^11.5/(PF^11.5+PA^11.5). The next tab shows the chances that the team in a given column will beat the team listed in a row, using the "log5" formula, discussed here. Finally, mindful of the ACC Tournament Bracket, I predict each team's chances to advance to the Quarterfinals, Semifinals, Finals, and their chances of being 2009 ACC Champion. Let's start with raw winning percentage.
So you can see that Duke has an .806 winning percentage, a 31.6% chance of beating UNC, and a 15. 6% chance of winning the ACC tournament. Of course, winning percentage is kind of silly, because blowouts and squeakers count exactly the same. For this reason many baseball stat-heads turned to Pythagorean Win Percentage, which calculates a team's likely winning percentage given how much they score and how much they allow. This can be applied to basketball as well, with the following result:
Some pretty big changes already. First off, Duke has vaulted above Wake and is now favored to make the finals against a still-overwhelmingly-favored UNC team. The middle of the pack has changed considerably; Miami has doubled their chances, while Clemson has had theirs halved. We know that the Pythagorean Winning Percentage is flawed, Baseball Prospectus also follows what they call "Third Order Wins." By this they mean that how much offense/defense is not as important as the context in which the points were scored.To put it in 2009 terms, which team has the better offense:
VMI-- Points/Game: 93.8 Possessions/Game: 81.2
Duke- Points/Game: 78.7 Possessions/Game: 70.1
It is true that VMI scores 15 more points per contest than the Blue Devils; they are the most prolific scorers in the nation. However, VMI plays at the fastest tempo in the country, getting over 11 possessions more per game than Duke. Teams play different opponents every game, which could have a wide variance in the number of possessions. So, a fair comparison of offenses requires looking not at a team's raw scoring numbers, but at how efficiently a team scores in the possessions it gets. With this, it is clear that Duke has the better offense.
So what if we were to predict the results of the ACC tournament using Offensive and Defensive Efficiency, as provided by Ken Pomeroy? For this run I will also take each team's schedule into account by using Pomeroy's "Adjusted" efficiency ratings; teams are penalized if they run up high efficiencies against bottom feeding teams. The results are provided in an earlier link, but I'm showing my work:
While the chances of favorite UNC have remained largely the same, the effect of tempo-free statistics and the schedule have boosted Duke's chances by 5%. Most of this comes from an ever-increasing chance of beating Wake Forest on a neutral court: from 46% using just win percentage to 56% with Pythagoras to 62% tempo-free.
Frequently, when I use these tempo-free statistics, some folks are not convinced. They think that the adjustments for schedule made by Pomeroy are not enough, and that teams are different in league play than they were playing non-league foes before the new year. In addition, the ACC tournament is taking place between only ACC teams, so shouldn't statistics within the ACC matter more? On the other hand, the ACC no longer has a balanced schedule; for example, Boston College played Duke once (at home) while they played #12 seed Georgia Tech twice. I have not attempted to adjust for schedule here, so these are raw efficiency numbers:
The most striking result is that the top three teams (UNC, Duke, Wake) have had their chances all go down, relative to the full-season Pomeroy ratings. These extra chances have been split among a few teams. Clemson's title chances went up by 3 percentage points. Florida State, whose defense has improved tremendously since the clock ticked to 2009, have doubled their title chances (as have Boston College).
NCAA Tournament Implications:
1) The 8-9 game is not the closest of the first round. That distinction belongs to NCSU vs Maryland, according to all four metrics. That is not a good matchup for anyone who thinks that Maryland is still on the bubble.
2) Virginia Tech is pretty screwed. Like Maryland, they are a 7-9 ACC team, and the committee doesn't usually take kindly to a sub-.500 conference record. They are probably out of the tournament picture unless they make it deep, and the statistics say it's not probable at all.
3) The final 7-9 team, Miami, has to avoid a collapse against Virginia Tech, and then they face 2-to-1 odds against in the matchup with Wake Forest. Should they prevail, would the committee consider what then would be a 20-win ACC team?
4) Statistically, the top three seeds are very heavy favorites for the semifinals, with Duke and UNC more likely to be there than Wake. Should Duke win the two games as expected, would they still have to beat Wake Forest to get a #2 seed in the NCAAT? Certainly, the Deacons probably need to win the ACC tournament to get their own #2 seed.
5) Clemson and Florida State should both be solidly into the NCAA tourament, but they are playing for favorable seedings. By the ACC numbers and the overall Pomeroy ratings, Clemson is favored in a matchup with Florida State, and the Tigers are more likely to knock off UNC.
6) Spreadsheets are fun!
Labels:
ACC Tournament,
Duke,
predictions
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