One year ago, we had some fun with spreadsheets and used a number of different methods to predict the ACC Tournament. Unfortunately, the raw numbers had no way of knowing the status of Ty Lawson's ankle, so the team predicted to win about 30% of the time grabbed the title, while UNC rested for bigger fish. In the past year the number of Pomeroy Disciples has grown, and so traditional "log5" predictions of the conference tournaments can be found all across teh internets (although this one in particular, from Basketball Prospectus, is a must read).
I like to find my little niche here at the Immaculate Inning, and that means simulating the hell out of things. The method is the same as for last years' ACC tournament. This year, I used raw offensive and defensive efficiencies that were tabulated here. This means that a team did not have their stats adjusted for home games or for the strength of opponent: the only values in the stat is points scored (or allowed) per possession. Via the Pythagorean Expectation Formula (with KenPom's exponent for unadjusted efficiencies = 8.5), I calculated a team's "expected winning percentage."
To determine the chances that team A beats team B, a form of Bayes Formula is applied, which in the stat-head world has come to be known as "The log5 Method." The method could be applied to any scenario where the probability of a single outcome is desired, given the prior probability for each of two alternatives. Here, we have two teams, each with an expected winning percentage, and can calculate the probability of a .900 team beating an .800 team. If we assume that the result of each game is independent, then we can multiply probabilities together to get a team's overall probability of making a certain round.
Personally I find the method rather deterministic, in what essentially is a stochastic process. Instead, I run the tournament 1 million times and calculate the percentage of simulations n which each team makes it to each round. The results of my simulations for the 2010 ACC Tournament are below:
The spreadsheet has two tabs, one for a simulation done using stats from all games, while the other is for ACC games only. The way to read it is that each team (row) won a certain number of games (0,1,2,3, or 4) in a certain percentage of the 1 million ACC tournaments I simulated. For the top four seeds, the maximum number of wins is 3, while the other 12 teams could potentially win four games and the tournament.
Duke's chances of winning the tournament is severely if stats from the entire season are used, and they go from a near 2-to-1 favorite to not even winning a majority of simulations. Part of this has to do with the raw nature of the efficiencies; accounting for Duke's tough schedule (and it was one of the toughest in the country by most any measure: KenPom, Sagarin, RPI) would probably account for most of the discrepancy.
On the other end of the spectrum is Miami, which gained an incredibly high percentage (from 0.1% to 3.4%) because they had a highly positive efficiency margin for all games, while it was highly negative in ACC games only. The Canes played very very well against a bunch of schools I've barely heard of, followed by getting clobbered in ACC play. Their adjusted efficiency margin is still decent due to the ACC games they played, but it's hard to give the full season stats much regard in this instance.
The numbers for the ACC-only simulations differ from those seen at Basketball Prospectus; I imagine most of the differences here also have to do with using raw efficiencies rather than Pomeroy's adjusted numbers. The adjusted numbers, Pomeroy claims, are the best for predicting "the chance of beating an average D-1 team on a neutral floor." The raw numbers, then, are skewed based on home-court advantage, schedule (remember, the ACC is no longer "balanced"), and the overall strength of offenses and defenses a team faces. In particular the predictions differ in that Maryland's chances are reduced, at the expense of better chances for FSU and VPI. Both methods agree that fifth-seed Wake has one hellish path towards an ACC title; much worse than sixth-seeded Clemson's chances. Overall, it will be interesting to see whether raw or adjusted efficiencies do a better job predicting the ACC tournament.
Another advantage that these simulations have is the amount of fun I can have with the results. Below I present the "Fan Anxiety Matrix." Each cell in the Matrix represents the chances that a team (in the rows) loses in the ACC tournament to a specific team (in the columns):
So, Duke's "Fan Anxiety Matrix" says that, in the 37% of simulations when they didn't win the whole thing, the most common opponent taking down the Blue Devils was Maryland (Using the ACC stats here). Perhaps no surprise there, but then there were still 8.3% of the simulations in which the Blue Devils fell in the semi-finals to Virginia Tech. Duke's first round game is against either Boston College or Virgina, and the combined percentage of simulations in which the Blue Devils' ACC run ended against those two teams was six percent. It should be of some comfort that UNC's chances of taking down Duke (this would have to be in the finals) clocked in at a tiny 0.029%.
Looking at the matrix, Clemson's path is an interesting one. The Tigers are seeded sixth and must at least pass through NCSU and FSU to get to the semifinals; the Matrix has them losing to these teams 22.5% and 37.1%, respectively. Maryland (22.4%) and Duke (10.1%) also appear in the double-digit percentages as Clemson's final ACC foe, with the remaining 3.2% speaking for Clemson's ACC title chances.
Virginia Tech's bubble position would certainly be helped with a win in their quarterfinal matchup; things are looking up according to the simulations, which have them falling to Duke in the semifinals 50% of the time. Wake Forest has a rough road to the ACC title, as they must win Thursday versus Miami (losing %: 30.5), Friday versus Virginia Tech (39.5%), Saturday versus (with 94% probability) Duke, who accounted for a further 25% of Wake's losses in the simulations.
For posterity's sake, here are the official Immaculate Inning ACC Tournament Predictions:
Thursday winners: Virginia, Wake Forest, Georgia Tech, Clemson
Friday winners: Duke, Virginia Tech, Maryland, Clemson
Saturday winners: Duke, Maryland
ACC Champion: Duke 75, Maryland 60
Showing posts with label predictions. Show all posts
Showing posts with label predictions. Show all posts
Thursday, March 11, 2010
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
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
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
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
Tuesday, July 24, 2007
Handicapping the Division Races, Part I
Despite being advertised as a "Sports blog," there has been whining that all of my content since March has been about the Yankees. This is true and I haven't paid as much attention to baseball outside of the Yankees as I would have liked to this season. In an effort to right both wrongs in one fell swoop, I'm going to take a look at each of the playoff chases. I'm starting with the NL Central, because I said so.
Following the 1997 season, acting commish and Milwaukee owner Bud Selig bit the bullet and offered that his team would switch leagues to accomodate the inclusion of the Arizona Diamondbacks in the National League (and prevent the scheduling nightmare of having an odd number of teams in each league). Since then, the Brewers have spent exactly zero days in first place in the six-team division past May 1. This season, they have had the pole position since April 21, with a lead that swelled to as much as 8.5 games on June 21.
There is little chance that anyone could have seen this coming. The World Series champs were in the division after all, and the Cardinals had dominated the NL Central for all but the final week of the 2006 regular season. The Brewers were in the back-seat as the Astros made an ultimately futile attempt to wrestle the division from the Cardinals- a 9 game winning streak ended when, on September 29, back-to-back homers by Edgar Renteria and Chipper Jones wasted the Astros' chance to take first place with two games to go. The Brewers, meanwhile, were wrapping up their season with fine performances from three players: 22-year old firstbaseman Prince Fielder (28 homers), 26 year-old shortsop Bill Hall (35 homers), and 30 year-old, free agent to-be Carlos Lee (28 homers).
Lee would stay within the division, signing a monstrous deal with the Astros. The Cubs, who finished fifth in the division, threw a ton of money at Alfonso Soriano, Aramis Ramirez, Ted Lilly, and Jason Marquis. The Astros lost Andy Pettitte and Roger Clemens but still had Roy Oswalt and a trio of young power-hitting outfielders. The Brewers, meanwhile, would be going into the season with an astounding four players aged 25 years or younger: Fielder, 2B Rickie Weeks, SS JJ Hardy, and RF Corey Hart. When 3B Ryan Braun was called up to replace Craig Counsell in late May, it assembled quite possibly the youngest infield of all time. Adding to that the loss of Carlos Lee and the addition of 31 year-old catcher Johnny Estrada (no matter what his Spring Training SLG), the Brewers looked to be headed to one of those bumpy rebuilding seasons.
It was not so; and the team in Milwaukee has been the surprise of the season. Fielder is putting up MVP numbers while Hardy and Braun are dominating the Rookie of the Year discussions. The pitching staff has been anchored by a healthy Ben Sheets (10-4, 3.39 ERA)- who has not missed a start and is on pace to top 200 IP for the first time since 2004. A rock-solid bullpen has made up for the league average (or worse) performance of the starters not named Sheets. Still, what was once an 8.5 game lead has shrunk to just 3 games after an extra-inning loss to the Reds last night.
Getting larger in the rearview mirror have been the spend-thrift Cubs. After Carlos Zambrano remembered he's in a contract year, the Cubs have gone 29-16 since June 1. Though their lineup has had a revolving door of rookies (with great names such as Felix Pie and Angel Pagan) finding various success, the trio of Soriano, Ramirez, and Derrek Lee have mashed. Inneffective bullpen vets (such as Scott Eyre) have been replaced with oustanding performances from Carlos Marmol (1.82 ERA and 42 K in 36 IP). And the other starters- Marquis, Lilly, and Rich Hill, have been joined by sophomore Sean Marshall to have a rotation well above league average.
With the Cardinals fading fast, the NL Central looks to be a two team race down the stretch. Coolstandings.com has the race as basically a coinflip (or AK v QQ), which reflects the dead-even Pythagorean records the two teams possess. The Brewers and Cubs have just three games left against each other, at Wrigley at the end of August. Each team has the bulk of their games against the Cardinals (11) and Reds (12). In fact, the only difference in the teams' remaining schedules is that the Brewers play eight versus the Braves and Padres, while the Cubs have eight against the Diamondbacks and Dodgers.
The difference, then, is going to be which team finds regression first. Neither team is playing above their heads with regards to their Pythagorean record (the Brewers slightly ahead, the Cubs slightly behind). The Brewers' starting pitchers are more or less performing to their career norms (Suppan and Bush are actually below their league average career ERA+), while the Cubs' starters are more likely to falter- Lilly and Marquis are performing quite a bit above their career norms. The lineup is a different story- the Cubs' top three sluggers are likely to keep it up for the rest of the season, while the rest of the lineup struggles to maintain league average. The Brewers, meanwhile, need to hope that the rest of the NL doesn't figure out how to pitch to all their youngsters, or that the phenoms don't tire during the pressure of a playoff push. Ryan Braun and Corey Hart aren't likely to keep up their hot streaks, and JJ Hardy has (predictably) cooled from his hot start to an OPS+ of just 107.
Each team is far from perfect, and both will look to improve in the final week before the waiver-free trade deadline- the Brewers looking for a starting pitcher (but who isn't), while the Cubs should be looking for an outfield bat. While it would be great for baseball for a very young, very cheap small market team like the Brewers to pull a division win out of nowhere, in the end it's probably best to trust the more expensive team. While there are no illusions that the Cubs are likely to end their 101 year World Series drought, they are a good bet to win the coin flip for the division.
Final Verdict: Cubs over the Brewers by 2 games.
Following the 1997 season, acting commish and Milwaukee owner Bud Selig bit the bullet and offered that his team would switch leagues to accomodate the inclusion of the Arizona Diamondbacks in the National League (and prevent the scheduling nightmare of having an odd number of teams in each league). Since then, the Brewers have spent exactly zero days in first place in the six-team division past May 1. This season, they have had the pole position since April 21, with a lead that swelled to as much as 8.5 games on June 21.
There is little chance that anyone could have seen this coming. The World Series champs were in the division after all, and the Cardinals had dominated the NL Central for all but the final week of the 2006 regular season. The Brewers were in the back-seat as the Astros made an ultimately futile attempt to wrestle the division from the Cardinals- a 9 game winning streak ended when, on September 29, back-to-back homers by Edgar Renteria and Chipper Jones wasted the Astros' chance to take first place with two games to go. The Brewers, meanwhile, were wrapping up their season with fine performances from three players: 22-year old firstbaseman Prince Fielder (28 homers), 26 year-old shortsop Bill Hall (35 homers), and 30 year-old, free agent to-be Carlos Lee (28 homers).
Lee would stay within the division, signing a monstrous deal with the Astros. The Cubs, who finished fifth in the division, threw a ton of money at Alfonso Soriano, Aramis Ramirez, Ted Lilly, and Jason Marquis. The Astros lost Andy Pettitte and Roger Clemens but still had Roy Oswalt and a trio of young power-hitting outfielders. The Brewers, meanwhile, would be going into the season with an astounding four players aged 25 years or younger: Fielder, 2B Rickie Weeks, SS JJ Hardy, and RF Corey Hart. When 3B Ryan Braun was called up to replace Craig Counsell in late May, it assembled quite possibly the youngest infield of all time. Adding to that the loss of Carlos Lee and the addition of 31 year-old catcher Johnny Estrada (no matter what his Spring Training SLG), the Brewers looked to be headed to one of those bumpy rebuilding seasons.
It was not so; and the team in Milwaukee has been the surprise of the season. Fielder is putting up MVP numbers while Hardy and Braun are dominating the Rookie of the Year discussions. The pitching staff has been anchored by a healthy Ben Sheets (10-4, 3.39 ERA)- who has not missed a start and is on pace to top 200 IP for the first time since 2004. A rock-solid bullpen has made up for the league average (or worse) performance of the starters not named Sheets. Still, what was once an 8.5 game lead has shrunk to just 3 games after an extra-inning loss to the Reds last night.
Getting larger in the rearview mirror have been the spend-thrift Cubs. After Carlos Zambrano remembered he's in a contract year, the Cubs have gone 29-16 since June 1. Though their lineup has had a revolving door of rookies (with great names such as Felix Pie and Angel Pagan) finding various success, the trio of Soriano, Ramirez, and Derrek Lee have mashed. Inneffective bullpen vets (such as Scott Eyre) have been replaced with oustanding performances from Carlos Marmol (1.82 ERA and 42 K in 36 IP). And the other starters- Marquis, Lilly, and Rich Hill, have been joined by sophomore Sean Marshall to have a rotation well above league average.
With the Cardinals fading fast, the NL Central looks to be a two team race down the stretch. Coolstandings.com has the race as basically a coinflip (or AK v QQ), which reflects the dead-even Pythagorean records the two teams possess. The Brewers and Cubs have just three games left against each other, at Wrigley at the end of August. Each team has the bulk of their games against the Cardinals (11) and Reds (12). In fact, the only difference in the teams' remaining schedules is that the Brewers play eight versus the Braves and Padres, while the Cubs have eight against the Diamondbacks and Dodgers.
The difference, then, is going to be which team finds regression first. Neither team is playing above their heads with regards to their Pythagorean record (the Brewers slightly ahead, the Cubs slightly behind). The Brewers' starting pitchers are more or less performing to their career norms (Suppan and Bush are actually below their league average career ERA+), while the Cubs' starters are more likely to falter- Lilly and Marquis are performing quite a bit above their career norms. The lineup is a different story- the Cubs' top three sluggers are likely to keep it up for the rest of the season, while the rest of the lineup struggles to maintain league average. The Brewers, meanwhile, need to hope that the rest of the NL doesn't figure out how to pitch to all their youngsters, or that the phenoms don't tire during the pressure of a playoff push. Ryan Braun and Corey Hart aren't likely to keep up their hot streaks, and JJ Hardy has (predictably) cooled from his hot start to an OPS+ of just 107.
Each team is far from perfect, and both will look to improve in the final week before the waiver-free trade deadline- the Brewers looking for a starting pitcher (but who isn't), while the Cubs should be looking for an outfield bat. While it would be great for baseball for a very young, very cheap small market team like the Brewers to pull a division win out of nowhere, in the end it's probably best to trust the more expensive team. While there are no illusions that the Cubs are likely to end their 101 year World Series drought, they are a good bet to win the coin flip for the division.
Final Verdict: Cubs over the Brewers by 2 games.
Labels:
baseball,
NL Central,
predictions
Tuesday, March 27, 2007
Marlins Season Preview
Perhaps we're a little Marlin heavy recently, and that's just fine by me. I was really looking forward to the Deadspin Marlins season preview, but they got a damn bitter Mets fan to write it. There are certainly some negative things about the Marlins organization but I feel that the good far outweighs the bad.
The Marlins don't have typical baseball fans. We don't pack the stadium but we do watch and listen to the games. I don't want to turn this into a Defend the Marlins Fans post, but here's why actual stadium attendance is low.
1) 1997 firesale
2) 2005 firesale
3) Florida's summer weather consists of really hot broken up by thunderstorms
4) Dolphins Stadium has bad sitelines down the third and first base lines
5) Lack of a strong city identity
The Marlins are an exciting team because they're modern baseball on steroids(pun intended). They can start young, develop, win a World Series, sell off the players, rebuild, and win another World Series in the span of 6 years. It's like following a college team. The most important players for the Marlins in the past 10 years have been their scouts and Larry Beinfest. Despite all the heart-rending trades, they keep coming up with gold. The most notable example is of course that Dontrelle Willis was a "player to be named later" when they traded away then-ace Matt Clement. More recently, they got both Anibal Sanchez and 2006 Rookie of the Year Hanley Ramirez in exchange for Mike Lowell and Josh Beckett.
I think they have a reasonable shot of making the playoffs this season. Dontrelle Willis leads the rotation, followed by Scott Olson, Anibal Sanchez, Ricky Nolasco...and some guy who will probably turn out to be awesome, because that's how these things work. If Josh Johnson is able to successfuly return by mid-season, they will have one of the best rotations in the NL. In the bullpen they have Randy Messenger and Taylor Tankersley as the always underrated Middle Relievers(or "set up men"). Tankersley was very solid last season and Messenger did well too. As mehmattski touched on, they aquired Jorge Julio to close, which I'm sure will work out fine.
On the other side of the equation, the offense is lead by Miguel Cabrera. So much has been written about how special a player he is, so I'll only add a little more. He had an off year for home runs last year and "only" hit 26, but that didn't stop him from batting in 114 runs. Also, he hit for .339. The joke at the beginning of last season was that the best hitter after Cabrera was Dontrelle Willis(who hit a disappointing .172, but still hit 3 HRs including a grand slam against the Mets). By the end of the season that was certainly not the case as Hanley Ramirez(.292 119 R 17 HRs), Dan Uggla (.282 27 HR, 90 RBI), Josh Willingham (.277 26 HRs), and Mike Jacobs (.262 20 HRs 77 RBIs) stepped it up.
Everyone is talking about a sophomore slump for the rookies, but if the Marlins keep improving they are certainly a threat to make the playoffs. I predict they'll win around 87 games and flirt with a Wild Card spot. If they make the playoffs, it'll be from their pitching and you do NOT want to bet against the Marlins in the playoffs.
The Marlins don't have typical baseball fans. We don't pack the stadium but we do watch and listen to the games. I don't want to turn this into a Defend the Marlins Fans post, but here's why actual stadium attendance is low.
1) 1997 firesale
2) 2005 firesale
3) Florida's summer weather consists of really hot broken up by thunderstorms
4) Dolphins Stadium has bad sitelines down the third and first base lines
5) Lack of a strong city identity
The Marlins are an exciting team because they're modern baseball on steroids(pun intended). They can start young, develop, win a World Series, sell off the players, rebuild, and win another World Series in the span of 6 years. It's like following a college team. The most important players for the Marlins in the past 10 years have been their scouts and Larry Beinfest. Despite all the heart-rending trades, they keep coming up with gold. The most notable example is of course that Dontrelle Willis was a "player to be named later" when they traded away then-ace Matt Clement. More recently, they got both Anibal Sanchez and 2006 Rookie of the Year Hanley Ramirez in exchange for Mike Lowell and Josh Beckett.
I think they have a reasonable shot of making the playoffs this season. Dontrelle Willis leads the rotation, followed by Scott Olson, Anibal Sanchez, Ricky Nolasco...and some guy who will probably turn out to be awesome, because that's how these things work. If Josh Johnson is able to successfuly return by mid-season, they will have one of the best rotations in the NL. In the bullpen they have Randy Messenger and Taylor Tankersley as the always underrated Middle Relievers(or "set up men"). Tankersley was very solid last season and Messenger did well too. As mehmattski touched on, they aquired Jorge Julio to close, which I'm sure will work out fine.
On the other side of the equation, the offense is lead by Miguel Cabrera. So much has been written about how special a player he is, so I'll only add a little more. He had an off year for home runs last year and "only" hit 26, but that didn't stop him from batting in 114 runs. Also, he hit for .339. The joke at the beginning of last season was that the best hitter after Cabrera was Dontrelle Willis(who hit a disappointing .172, but still hit 3 HRs including a grand slam against the Mets). By the end of the season that was certainly not the case as Hanley Ramirez(.292 119 R 17 HRs), Dan Uggla (.282 27 HR, 90 RBI), Josh Willingham (.277 26 HRs), and Mike Jacobs (.262 20 HRs 77 RBIs) stepped it up.
Everyone is talking about a sophomore slump for the rookies, but if the Marlins keep improving they are certainly a threat to make the playoffs. I predict they'll win around 87 games and flirt with a Wild Card spot. If they make the playoffs, it'll be from their pitching and you do NOT want to bet against the Marlins in the playoffs.
Labels:
baseball,
marlins,
predictions
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