Showing posts with label Vegas. Show all posts
Showing posts with label Vegas. Show all posts

Monday, June 09, 2014

Vegas MLB Over/Under Recap


Here is a breakdown on how many times Vegas has set the over/under at each number during the baseball season so far. The breakdown also shows how many times the over, under or a push hit for each Vegas over/under. Though it still is a small sample size, more unders are hitting for the higher over/unders and more overs are hitting for the lower over/unders. I am not trying to claim any great revelations here, just reporting what the empirical data looks like so far.

Over/UnderCountOverUnderPushes
50000
5.51100
65320
6.57639370
7180896130
7.52311191120
815875767
8.514868800
98938456
9.53213190
1012660
10.514680
110000
11.51010
Total94745744743
.

Friday, November 22, 2013

2013 Vegas Park Factors


There are more than a few ways of calculating park factors.  The simplest system of all and the one that tells the best story of which park played as a hitter or pitchers park based on the empirical data (actual results) is the one where you simply divide runs per game at home scored by both teams by runs per game on the road scored by both teams.  ESPN does a great job of providing this data for previous seasons.

One problem with these year to year park factors (for runs scored) is that there is a ton of noise (variance) from year to year.  It is just very difficult to pin down what the true park factor should be for each park.  Some people like to take the previous two or three seasons and weight the more recent seasons heavier to come up with a number.  This is actually a safe way of doing it and one I usually prefer.

When it comes to betting on baseball run totals (over/unders) one needs a really good idea on what a stadiums' true park factor is.  From this base park factor number you can adjust up or down based off of weather or wind conditions if you like, but you need a good park factor number for each stadium first.  The Vegas sportsbooks obviously have their own numbers and if they don't you can easily reverse engineer the numbers that they used over the course of the season for each park.  All you need to do is take all of their run total numbers and adjust for juice to come up with an over/under number for each game.  Let's say you calculate that number as 7.25 runs scored.  You do this for all games and use this 7.25 (calculated number) as a substitute for the actual number of runs that were scored in that game and calculate each teams' park factor based off of this calculated number instead of the actual total number of runs scored.  In doing so, you can get a glimpse into what Vegas used as park factors for each team and then compare their park factors with the actual empirical number.  I calculate these Vegas park factors as the season progresses as kind of a sanity check against the park factors that I use in my day to day baseball game simulations.

Below is a look at each teams' Vegas park factor and Actual 2013 park factor and the difference between the two sorted by parks that Vegas had the run environment too low on.  Just because Vegas was off on a park factor may or may not mean they were dumb on selecting their park factor for that team as like I said above there is quite a bit of noise involved here.  But it would've obviously made for some good betting opportunities.

TeamVegas PFActual 2013 PF2013 Delta
Tigers1.0221.1390.1167
Cubs1.0831.1920.1091
Phillies1.0231.1070.0838
Blue Jays1.0441.1180.0743
Mariners0.9180.9910.0733
Marlins0.9591.0300.0715
Royals1.0161.0820.0661
Astros1.0091.0740.0652
Brewers1.0461.1100.0642
Yankees1.0281.0870.0590
Twins0.9751.0200.0446
Nationals0.9691.0130.0444
Rockies1.2391.2730.0343
Orioles1.0381.0570.0187
Angels0.9640.9680.0036
Braves0.9550.9560.0008
White Sox1.0030.998-0.0050
Rays0.9410.931-0.0103
Giants0.8890.869-0.0204
Dodgers0.8960.868-0.0279
Athletics0.9190.889-0.0295
Reds1.0320.989-0.0425
Indians0.9770.933-0.0442
Padres0.8770.831-0.0461
Pirates0.9610.907-0.0535
Mets0.9410.867-0.0736
Cardinals0.9790.892-0.0868
Red Sox1.0830.960-0.1227
Diamondbacks1.0980.974-0.1237
Rangers1.1210.985-0.1357

As a further exercise I computed the RMSE for the Vegas 2013 park factors against the actual park factors for the 2013, 2012 and 2011 seasons for the fun of it.

The RMSE (sum of the squares of the 32 park factor errors)... were.....
2013 = 0.1429
2012 = 0.4396
2011 = 0.2423
(these numbers are pre-square root)

You would expect to see the 2013 number be the lowest as that is what Vegas was predicting against.  The 2012 park factors had a lot of noise as there were a few crazy outliers bringing the error total up.  The 2011 park factors did pretty well, but about where you would expect it.


Friday, October 25, 2013

World Series Individual Game Odds Reverse Engineered


Here are the odds of each remaining World Series game based on the knowledge of the Vegas odds that each team wins the World Series and the Vegas odds for games 1,2 and 3.  The odds for games 1,2 and 3 give us a good approximation for the odds in games 5,6 and 7 and we can move the game four odds around in such a way that the chances for each team winning the series match the Vegas odds.

Here is a look at the table with the individual game odds.

Game #Red SoxCardinals
Game 1100.0%0.0%
Game 20.0%100.0%
Game 350.6%49.4%
Game 449.3%50.7%
Game 545.9%54.1%
Game 652.0%48.0%
Game 758.6%41.4%
Series52.4%47.6%

And here is a table with the chances of the series ending with one team winning in X number of games.

ResultChance %Odds
52.4%
Red Sox in 40.0%NA
Red Sox in 511.5%7.73
Red Sox in 619.0%4.28
Red Sox in 722.0%3.55
47.6%
Cardinals in 40.0%NA
Cardinals in 513.5%6.38
Cardinals in 618.5%4.40
Cardinals in 715.5%5.43

Notes
- HFA of 4% is assumed
- Data was computed with spreadsheet provided by one of my readers.

Friday, May 17, 2013

Vegas Top Favorites


DateAwayHomeAway SPHome SPVegas FaveML FaveML DogVegas Win ExpResult
5/15/2013HOUDETDan KeuchelMax ScherzerDET-36032577.40%HOU 7-5
5/14/2013HOUDETLucas HarrellDoug FisterDET-28526573.33%DET 6-2
5/13/2013HOUDETBud NorrisAnibal SanchezDET-27525772.68%DET 7-2
4/30/2013HOUNYAPhillip HumberHiroki KurodaNYA-27325672.57%NYA 7-4
4/27/2013HOUBOSBrad PeacockFelix DoubrontBOS-26525072.03%BOS 8-4
5/5/2013DETHOUJustin VerlanderPhillip HumberDET-26024571.63%DET 9-0
4/1/2013MIAWASRicky NolascoStephen StrasburgWAS-25824471.51%WAS 2-0
4/3/2013MIAWASKevin SloweyGio GonzalezWAS-25824471.51%WAS 3-0
4/25/2013HOUBOSPhillip HumberClay BuchlzBOS-25024071.01%BOS 7-2
4/30/2013MINDETVance WorleyJustin VerlanderDET-25024071.01%DET 6-1

Tuesday, February 12, 2013

2013 MLB Win Totals - Part I


Instead of just posting the current Vegas MLB odds to win the World Series, I am going to take things a step further and interpolate those W.S. odds out to 2013 win totals. There is no great scientific method that I am going to be using except for keeping consistent with the Vegas odds in the order I assign team wins.  I think I have a pretty good idea at what Vegas typically sets their highest and lowest over/under win totals at, so everything in between I can do an "eye ball" interpolation on to set the win total over/under for each team. Later in my Part II of this series, I will use a more scientific method for matching up the Vegas odds to win totals. But for now... here we go!

TeamOdds To Win W.S.% Chance to Win2013 Wins Over/Under
Angels8-18.3993
Dodgers8-18.3993
Blue Jays8-18.3993
Nationals8-18.3993
Tigers9-17.5592
Braves12-15.8190
Yankees12.5-15.5989
Reds13-15.4088
Rangers13.5-15.2188
Phillies17-14.2086
Giants17-14.2086
Red Sox20-13.6085
Cardinals20-13.6085
Rays22-13.2884
Athletics30-12.4482
Orioles40-11.8481
Diamondbacks45-11.6480
White Sox50-11.4879
Royals50-11.4879
Brewers50-11.4879
Pirates72-11.0377
Mets75-10.9975
Padres75-10.9975
Indians77.5-10.9675
Cubs100-10.7571
Rockies100-10.7571
Mariners110-10.6870
Twins125-10.6067
Marlins150-10.5063
Astros200-10.3861

Notes: 
Percent chance of winning W.S. has the Vegas juice removed.
American League has a 51.5% (Vegas) chance of winning the W.S.
National League has a 48.5% (Vegas) chance of winning the W.S.
Odds were taken from 5Dimes on 2/12/13.
In calculating the pecent chance to win the W.S., I removed the Vegas "juice".
The 2013 Over/Unders from the Atlantis came out the day after this post.

For the most part, I did a straight interpolation from (Vegas) World Series odds to an over/under on team wins.  There a couple of things that could be wrong with this.  The first comes from the possibility that the Vegas World Series odds have some bias to them.  Perhaps Vegas moved the odds up or down based on how popular a team is.  This of course has nothing to do with my methodology.  On the otherhand, something that does have to do with my methodology is that I am not controlling for the teams playing in divisions.  Divisions that may be stronger or weaker than others.  For example, the Royals might win a World Series out of every 50 times playing out of the AL Central, but what if they played out of the AL East?  Chances are that 50 number would climb.  A next step to this exercise would be to control for how hard or easy it is to win a division.  I'm not sure on the best way to do this yet, so if you have any ideas feel free to leave a comment or send me a tweet (@DodgerSims).

Wednesday, January 30, 2013

2013 World Series Odds


As of 1/30/2013...

Team12/15/12 Odds12/29/12 Odds1/30/13
Angels7-17-17-1
Tigers7-17-17-1
Dodgers7-17-17-1
Nationals8-18-18-1
Blue Jays10-110-110-1
Yankees10-112-114-1
Reds10-112-112-1
Rangers10-114-118-1
Cardinals14-114-114-1
Giants14-114-114-1
Phillies16-114-114-1
Braves16-116-114-1
Rays20-116-116-1
Brewers30-130-160-1
Red Sox30-130-130-1
Athletics40-130-130-1
Royals30-140-140-1
White Sox40-140-140-1
Diamdonbacks40-150-150-1
Orioles50-150-150-1
Pirates50-150-150-1
Cubs60-150-150-1
Mariners100-180-180-1
Indians100-180-180-1
Mets60-1100-1100-1
Padres100-1100-1100-1
Marlins100-1100-1100-1
Twins100-1100-1100-1
Astros100-1100-1100-1
Rockies100-1100-1100-1

Source: Sportsbook.com

Saturday, December 29, 2012

2013 World Series Odds


As of 12/29/2012...

Team12/15/12 Odds12/29/12 Odds
Angels7-17-1
Tigers7-17-1
Dodgers7-17-1
Nationals8-18-1
Blue Jays10-110-1
Yankees10-112-1
Reds10-112-1
Rangers10-114-1
Cardinals14-114-1
Giants14-114-1
Phillies16-114-1
Braves16-116-1
Rays20-116-1
Brewers30-130-1
Red Sox30-130-1
Athletics40-130-1
Royals30-140-1
White Sox40-140-1
Diamdonbacks40-150-1
Orioles50-150-1
Pirates50-150-1
Cubs60-150-1
Mariners100-180-1
Indians100-180-1
Mets60-1100-1
Padres100-1100-1
Marlins100-1100-1
Twins100-1100-1
Astros100-1100-1
Rockies100-1100-1

Source: Sportsbook.com



Sunday, December 16, 2012

2013 World Series Odds


as of 12/15/12....  2013 World Series Odds

Team12/15/12 Odds
Angels7-1
Tigers7-1
Dodgers7-1
Nationals8-1
Yankees10-1
Rangers10-1
Reds10-1
Blue Jays10-1
Cardinals14-1
Giants14-1
Phillies16-1
Braves16-1
Rays20-1
Brewers30-1
Royals30-1
Red Sox30-1
White Sox40-1
Diamdonbacks40-1
Athletics40-1
Orioles50-1
Pirates50-1
Mets60-1
Cubs60-1
Padres100-1
Marlins100-1
Mariners100-1
Indians100-1
Twins100-1
Astros100-1
Rockies100-1


Source: Sportsbook.com


Saturday, May 19, 2012

Most Surprising Teams




A quick comparison of actual MLB teams winning percentage with their expected wins from Vegas to show which teams are the most and least surprising in a good and bad way. Vegas expected wins are calculated by adding up the chances of a team winning each game based on the Vegas money line. If a team had a 55% chance of winning a game according to Vegas they got 0.55 wins and 0.45 losses for that game. The teams at the top of this chart are way outperforming their win totals according to Vegas odds and the teams at the bottom of the chart are way underperforming. Teams in the middle are doing what they were expected to do.

TeamWinsLossesWPctVegas Exp WinsVegas Exp LossesVegas Exp WPctDiff Win Exp
Orioles27140.65918.24822.7520.4450.213
Dodgers27130.67521.73618.2640.5430.132
Indians23170.57519.70220.2980.4930.082
Braves25160.61021.69319.3070.5290.081
Rays24170.58521.26319.7370.5190.067
Pirates19210.47516.94023.0600.4240.051
Athletics20210.48817.93023.0700.4370.050
Astros18220.45016.29323.7070.4070.043
Mets20200.50018.43821.5620.4610.039
Nationals23170.57521.69018.3100.5420.033
Blue Jays23180.56121.70519.2950.5290.032
Rangers25160.61024.08516.9150.5870.022
Reds21180.53820.13518.8650.5160.022
Giants21190.52520.75719.2430.5190.006
Marlins21190.52521.16418.8360.529-0.004
White Sox20210.48820.26320.7370.494-0.006
Mariners18240.42918.31623.6840.436-0.008
Cardinals21190.52521.78018.2200.545-0.020
Royals16230.41017.25921.7410.443-0.032
Red Sox20200.50021.45618.5440.536-0.036
Phillies21200.51222.71918.2810.554-0.042
Yankees21190.52522.69317.3070.567-0.042
Diamondbacks18230.43920.03720.9630.489-0.050
Twins14260.35016.01423.9860.400-0.050
Cubs15250.37517.58722.4130.440-0.065
Tigers19210.47522.26217.7380.557-0.082
Brewers17230.42521.32718.6730.533-0.108
Padres14270.34118.53922.4610.452-0.111
Rockies15240.38519.62819.3720.503-0.119
Angels18230.43923.34017.6600.569-0.130

Tuesday, May 08, 2012

Las Vegas MLB Park Factors



Having compiled all of the MLB run total lines from Vegas Odds (5Dimes, Opening Lines) I decided to reverse engineer (Runs) park factors from the Vegas lines. What I did is substituted total runs scored for each game with the Vegas run totals, then added up the expected run totals for the home games and away games for each team and plugged this in to the basic park factors equation of...

PF: ((homeRS + homeRA)/(homeG)) / ((roadRS + roadRA)/(roadG))

Along with the Vegas park factors, I am listing and sorting by 2012 empirical park factors with the Vegas park factor listed to the right side. I am aware that this is a really small sample size for anything dealing with the empirical park factors, but it should give you a glimpse in to how the oddsmakers judge each park. As more games are played and the schedules even out, I will revisit this to see how things shake out. The table below lists the current "runs" park factor and Vegas park factor along with the average number of runs scored away stadium/home stadium for each of the two methods.

TeamAway Stadium RunsHome Stadium RunsPFVegas Away Stadium RunsVegas Home Stadium RunsVegas PF
Rockies7.2012.941.807.739.391.21
Blue Jays7.1410.401.468.168.651.06
Cardinals7.6510.581.387.917.440.94
Twins7.8810.671.358.348.170.98
Marlins6.398.451.327.077.231.02
Royals7.7710.131.307.858.611.10
Diamondbacks7.639.791.287.328.611.18
Tigers7.409.111.238.688.240.95
Red Sox10.3612.211.188.429.201.09
White Sox7.258.431.167.798.211.05
Nationals5.836.751.166.976.920.99
Braves9.5310.851.148.117.370.91
Brewers8.569.621.127.137.951.12
Reds7.217.931.107.518.061.07
Yankees9.809.460.979.159.501.04
Phillies7.797.090.916.797.201.06
Cubs8.177.410.917.537.651.02
Astros9.388.310.897.477.791.04
Orioles8.947.850.888.748.801.01
Angels8.086.880.858.167.520.92
Mariners8.396.920.838.037.010.87
Dodgers8.507.000.827.596.710.88
Padres8.566.670.787.696.280.82
Athletics8.006.230.787.487.020.94
Rays10.007.750.788.667.580.88
Indians10.427.940.767.687.981.04
Rangers10.137.690.768.649.451.09
Pirates7.565.080.677.317.441.02
Mets11.006.500.597.927.240.92
Giants9.865.600.578.066.480.80

Thursday, December 01, 2011

How To Handicap Defense In Baseball



Hitting and pitching, they both play a big role in how you should handicap a baseball game. The often forgotten and important piece of the puzzle is defense. Just how much does the removal or addition of a good defensive player effect the likely outcome (think win probability) of a single baseball game?

I am sure there are many ways of solving this problem. The method I am going to use is a theoretical one. First let's take a swag at how many runs per season a good defensive player saves over an average defensive player. I think 20 runs per season is a good conservative number for a good (think Brett Gardner) and a bad one (think Raul Ibanez) costing his team 20 runs per season.

20 runs over a 162 games averages out to around 0.123 runs per game. If we set our run environment to 9 runs per game, which is fairly accurate but the round number makes the math easier, we get a 50/50 game having 4.5 runs for both Team A and Team B. On Vegas with no juice this would be a -100/+100 game on the Money Line (ML). Now let's assume an average defensive player on Team A is replaced with a player who the only difference is, is that he is a +20 (runs saved per season) player. Team A now scores 4.5 runs per 27 outs but Team B now only scores (4.5 - 0.123) 4.377 runs per 27. Using the pythagorean formula for a quick and dirty win probability calculation Team A now has a win probability of 51.3853%. So his glove is worth approximately 1.39% win expectancy. On the Vegas ML the -100/+100 (no juice) line would now look like -106/+106.

This would mean that if we instead put a -20 run defensive player in, instead of the +20 player. We would see Team A get a 48.6147% win probability and be on the other side of the -106/+106 line, for a whopping drop in win expectancy of 2.46% in this example. Of course things are effected a little bit differently based on the run environment and type of pitcher pitching. An infielder in a low run environment game playing behind a ground ball pitcher will have a bigger effect on the game outcome than he would in a game being played in a higher run environment with a strikeout pitcher who sees very few balls put in play.

These are all things to take into consideration and each defensive replacement must be looked at on a case by case basis, but for a rough calculation replacing a great fielder with an average one will cost your team a little over 1% in win probability and replacing a great fielder with a very bad one will cost you around 2.5% in win probability, looking at defense only.

Sunday, November 20, 2011

How Did Vegas Do Predicting MLB Games?



A good way to tell how well Vegas (and my simulator) did at predicting winners during the season is to compare blocks of games that had similar odds to each other. For example, I took the 100 games that had the highest favorite to win and calculated the average Vegas win expectancy of those games and compared across the board to my simulator and the actual results. I did this for all 100 blocks of games as well as blocks of 300 and blocks of 600. The smaller the block size the more noise you will have but the more interesting trends you will see. Below are tables of those three types of blocks of games.

100 Blocks of Games 300 Blocks of Games 600 Blocks of Games
BlocksVegSimActual  VegasSimActual  VegasSimActual
1-1000.69100.67230.6700 1-3000.66150.64760.6267 1-6000.63960.63010.6450
101-2000.65490.64080.6100 301-6000.61770.61260.6633 601-12000.58310.57620.5867
201-3000.63870.62970.6000 601-9000.59260.58580.5700 1201-18000.54860.54100.5517
301-4000.62720.62170.6500 901-12000.57360.56660.6033 1801-24140.51710.51380.5220
401-5000.61770.60590.6400 1201-15000.55690.55040.6033     
501-6000.60810.61010.7000 1501-18000.54040.53170.5000     
601-7000.59930.59430.6900 1801-21000.52510.51960.5033     
701-8000.59270.58210.5100 2101-24140.50950.50830.5399     
801-9000.58580.58100.5100          
901-10000.57880.57840.5900          
1000-11000.57340.55950.6100          
1100-12000.56850.56200.6100          
1201-13000.56290.55280.6500          
1301-14000.55700.55190.6000          
1401-15000.55070.54660.5600          
1501-16000.54610.53600.5500
1601-17000.54020.52930.5400
1701-18000.53480.52980.4100
1801-19000.53030.53220.4600
1901-20000.52520.52300.5300
2001-21000.51990.50340.5200
2101-22000.51420.51110.5000
2201-23000.50980.51100.5400
2301-24140.50500.50350.5702


Monday, November 07, 2011

Dodgers Season, Against The Odds



Here is the compiled list of all 161 Dodgers games this season. The list is sorted by the games the Dodgers were the largest favorites in. The game in which the Dodgers were the biggest favorites was an August 13th game at Dodger Stadium against the Houston Astros. Wandy Rodriguez was on the mound for the Astros and Clayton Kershaw for the Dodgers. The Dodgers were 67.213% favorites to win that game in Vegas and did end up winning 6-1. If you add up the Vegas win expectancy of all 161 Dodgers games, they should have won 49.94% of their games or won 80.4 games. The Dodgers ended the season with an 82-79 record, so they slightly outperformed their Vegas expectations. Below is the entire list...

RankDateAway SPHome SPAwayHomeFaveFave Win PercLAN Win PercWinning TeamAway RunsHome RunsTotal Runs
108-13-2011Wandy RodriguezClayton KershawHOULANLAN67.21367.213LAN167
205-02-11James RussellClayton KershawCHNLANLAN65.21765.217LAN257
308-14-2011Jordan LylesHiroki KurodaHOULANLAN64.85164.851LAN077
409-15-2011Ross OhlendorfDana EvelandPITLANLAN64.28664.286PIT628
509-16-2011Jeff LockeHiroki KurodaPITLANLAN64.09364.093LAN279
605-13-2011Joe SaundersClayton KershawARILANLAN63.30363.303LAN347
708-29-2011Mat LatosClayton KershawSDLANLAN61.01461.014LAN145
806-20-2011Brad PennyClayton KershawDETLANLAN59.43259.432LAN044
907-26-2011Jhoulys ChacinClayton KershawCOLLANLAN59.43259.432LAN235
1009-18-2011Brad LincolnChad BillingsleyPITLANLAN59.43259.432LAN11516
1106-19-2011Bud NorrisHiroki KurodaHOULANLAN59.26759.267LAN011
1209-17-2011James McDonaldTed LillyPITLANLAN59.26759.267LAN167
1305-03-11Ryan DempsterChad BillingsleyCHNLANLAN59.18459.184CHN415
1406-17-2011Brett MyersTed LillyHOULANLAN59.18459.184HOU7310
1507-07-11Dillon GeeClayton KershawNYNLANLAN58.76358.763LAN066
1608-30-2011Tim StaufferHiroki KurodaSDLANLAN58.76358.763LAN5813
1704-16-2011Kyle McClellanClayton KershawSTLLANLAN58.4258.42STL9211
1808-31-2011Wade LeBlancTed LillySDLANLAN58.4258.42LAN246
1907-27-2011Aaron CookHiroki KurodaCOLLANLAN58.33358.333COL314
2008-12-11Bud NorrisNathan EovaldiHOULANLAN57.89557.895LAN011
2105-14-2011Josh CollmenterChad BillingsleyARILANLAN57.35657.356ARI101
2207-22-2011John LannanHiroki KurodaWASLANLAN57.35657.356WAS729
2304-03-11Barry ZitoHiroki KurodaSFLANLAN57.26557.265LAN5712
2409-25-2011Clayton KershawCory LuebkeLANSDLAN57.17357.173LAN628
2504-30-2011Tim StaufferHiroki KurodaSDLANLAN56.89756.897SD527
2609-14-2011Daniel HudsonClayton KershawARILANLAN56.80356.803LAN235
2704-26-2011Clayton KershawChris VolstadLANFLALAN56.61656.616FLA246
2806-25-2011Tyler ChatwoodHiroki KurodaLAALANLAN56.61656.616LAA617
2908-27-2011Kevin MillwoodChad BillingsleyCOLLANLAN56.61656.616LAN6713
3009-04-11Clayton KershawRandall DelgadoLANATLLAN56.42756.427ATL347
3105-01-11Dustin MoseleyJon GarlandSDLANLAN56.1456.14SD707
3207-23-2011Tom GorzelannyTed LillyWASLANLAN56.04456.044LAN6713
3308-26-2011Esmil RogersTed LillyCOLLANLAN56.04456.044LAN167
3404-21-2011Jair JurrjensClayton KershawATLLANLAN55.8555.85LAN358
3505-29-2011Ricky NolascoClayton KershawFLALANLAN55.8555.85LAN088
3607-24-2011Jason MarquisChad BillingsleyWASLANLAN55.8555.85LAN134
3707-30-2011Micah OwingsChad BillingsleyARILANLAN55.65455.654ARI6410
3808-01-11Clayton KershawCory LuebkeLANSDLAN55.55655.556LAN628
3905-23-2011Clayton KershawBud NorrisLANHOULAN55.45755.457HOU347
4005-17-2011Randy WolfHiroki KurodaMILLANLAN55.15755.157LAN033
4106-18-2011Wandy RodriguezRubby DeLaRosaHOULANLAN55.15755.157HOU707
4205-28-2011Brian SanchesHiroki KurodaFLALANLAN54.85354.853FLA617
4306-14-2011Johnny CuetoClayton KershawCINLANLAN54.85354.853CIN325
4407-09-11Aaron HarangRubby DeLaRosaSDLANLAN54.64954.649LAN011
4507-15-2011Clayton KershawJoe SaundersLANARILAN54.64954.649LAN6410
4607-05-11Mike PelfreyTed LillyNYNLANLAN54.44254.442NYN606
4705-24-2011Chad BillingsleyJ.A. HappLANHOULAN54.44254.442LAN549
4807-06-11John NieseHiroki KurodaNYNLANLAN54.23354.233NYN538
4907-08-11Mat LatosChad BillingsleySDLANLAN54.23354.233LAN011
5005-18-2011Matt CainClayton KershawSFLANLAN54.23354.233SF8513
5107-04-11Chris CapuanoRubby DeLaRosaNYNLANLAN54.02354.023NYN527
5205-09-11Chad BillingsleyJeff KarstensLANPITLAN54.02354.023PIT145
5305-19-2011Madison BumgarnerChad BillingsleySFLANLAN54.02354.023SF314
5404-29-2011Clayton RichardTed LillySDLANLAN53.81153.811LAN235
5505-25-2011Ted LillyAneury RodriguezLANHOULAN53.81153.811HOU123
5606-15-2011Travis WoodChad BillingsleyCINLANLAN53.81153.811CIN729
5708-28-2011Jhoulys ChacinNathan EovaldiCOLLANLAN53.81153.811COL7613
5809-20-2011Tim LincecumClayton KershawSFLANLAN53.59653.596LAN123
5904-01-11Jonathan SanchezChad BillingsleySFLANLAN53.48853.488LAN347
6009-12-11Joe SaundersTed LillyARILANLAN53.3853.38ARI729
6106-13-2011Bronson ArroyoHiroki KurodaCINLANLAN53.3853.38CIN6410
6207-31-2011Joe SaundersRubby DeLaRosaARILANLAN53.3853.38ARI639
6305-31-2011Clay MortensenTed LillyCOLLANLAN53.16253.162LAN2810
6404-14-2011Jaime GarciaHiroki KurodaSTLLANLAN52.8352.83STL9514
6505-04-11Carlos ZambranoTed LillyCHNLANLAN52.71952.719CHN516
6608-18-2011Clayton KershawMarco EstradaLANMILLAN52.71952.719LAN516
6704-09-11Hiroki KurodaDustin MoseleyLANSDLAN52.49452.494LAN404
6804-15-2011Kyle LOhseJon GarlandSTLLANLAN52.49452.494STL11213
6905-27-2011Javier VazquezJon GarlandFLALANLAN52.49452.494LAN347
7007-25-2011Juan NicasioRubby DeLaRosaCOLLANLAN52.49452.494LAN5813
7105-30-2011Jason HammelChad BillingsleyCOLLANLAN52.38152.381LAN178
7204-19-2011Brandon BeachyHiroki KurodaATLLANLAN52.03852.038ATL10111
7309-05-11Hiroki KurodaJohn LannanLANWASLAN51.80751.807WAS279
7409-24-2011Chad BillingsleyAaron HarangLANSDLAN51.2251.22SD033
7506-26-2011Jered WeaverClayton KershawLAALANLAN51.151.1LAN235
7607-10-11Tim StaufferTed LillySDLANLAN50.9850.98LAN145
7706-22-2011Rick PorcelloTed LillyDETLANLAN50.61750.617DET7512
7803-31-2011Tim LincecumClayton KershawSFLANLAN50.49550.495LAN123
7909-23-2011Ted LillyWade LeBlancLANSDLAN50.49550.495LAN202
8004-22-2011Chad BillingsleyCasey ColemanLANCHNLAN50.24950.249LAN12214
8104-02-11Matt CainTed LillySFLANSF5050SF10010
8209-08-11Chad BillingsleyChien-Ming WangLANWASWAS5050LAN7411
8308-21-2011Chad BillingsleyKevin MillwoodLANCOLCOL50.24949.751COL358
8404-05-11Clayton KershawJhoulys ChacinLANCOLCOL50.49549.505COL033
8505-11-11Hiroki KurodaPaul MaholmLANPITPIT50.73949.261LAN202
8608-19-2011Hiroki KurodaJason HammelLANCOLCOL50.8649.14LAN8210
8708-02-11Hiroki KurodaMat LatosLANSDSD51.148.9LAN101
8808-07-11Clayton KershawIan KennedyLANARIARI51.2248.78ARI347
8904-11-11Clayton KershawMadison BumgarnerLANSFSF51.2248.78LAN617
9005-15-2011Ian KennedyTed LillyARILANARI51.2248.78ARI415
9109-27-2011Hiroki KurodaJarrod ParkerLANARIARI51.45648.544ARI6713
9207-01-11Hiroki KurodaTyler ChatwoodLANLAALAA51.57448.426LAN505
9306-28-2011Ted LillyBrian DuensingLANMINMIN51.57448.426MIN4610
9408-23-2011Clayton KershawKyle LohseLANSTLSTL52.15347.847LAN13215
9506-21-2011Max ScherzerChad BillingsleyDETLANDET52.26747.733LAN167
9607-29-2011Josh CollmenterTed LillyARILANARI52.26747.733LAN9514
9706-27-2011Chad BillingsleyNick BlackburnLANMINMIN52.49447.506LAN15015
9804-06-11Chad BillingsleyJason HammelLANCOLCOL52.60747.393COL5712
9906-01-11Ubaldo JimenezJon GarlandCOLLANCOL52.71947.281COL303
10004-08-11Ted LillyClayton RichardLANSDSD52.71947.281LAN426
10105-16-2011Shaun MarcumJon GarlandMILLANMIL52.71947.281MIL213
10206-04-11Clayton KershawJohnny CuetoLANCINCIN52.94147.059LAN11819
10309-28-2011Ted LillyJoe SaundersLANARIARI52.94147.059LAN7512
10406-05-11Chad BillingsleyTravis WoodLANCINCIN53.16246.838LAN9615
10505-10-11Ted LillyKevin CorreiaLANPITPIT53.27146.729LAN10313
10604-27-2011Chad BillingsleyAnibal SanchezLANFLAFLA53.3846.62LAN549
10709-21-2011Ryan VogelsongDana EvelandSFLANSF53.3846.62SF8513
10809-13-2011Ian KennedyChad BillingsleyARILANARI53.59646.404ARI549
10905-08-11Clayton KershawR.A. DickeyLANNYNNYN53.70446.296LAN426
11008-03-11Ted LillyTim StaufferLANSDSD53.81146.189SD033
11105-06-11Hiroki KurodaJohn NieseLANNYNNYN53.81146.189NYN369
11204-10-11John ElyAaron HarangLANSDSD53.81146.189SD279
11308-20-2011Ted LillyEsmil RogersLANCOLCOL53.81146.189COL6713
11409-09-11Clayton KershawTim LincecumLANSFSF54.02345.977LAN213
11504-23-2011Ted LillyRyan DempsterLANCHNCHN54.02345.977CHN81018
11604-24-2011Hiroki KurodaCarlos ZambranoLANCHNCHN54.02345.977LAN7310
11709-11-11Hiroki KurodaMadison BumgarnerLANSFSF54.44245.558SF189
11806-09-11Clayton KershawJuan NicasioLANCOLCOL54.64945.351COL7916
11904-17-2011Chris CarpenterChad BillingsleySTLLANSTL54.64945.351LAN123
12009-01-11Dana EvelandBrad LincolnLANPITPIT54.75145.249LAN6410
12108-10-11Vance WorleyChad BillingsleyPHILANPHI54.85345.147PHI9817
12207-02-11Clayton KershawJered WeaverLANLAALAA55.05644.944LAA178
12306-03-11Hiroki KurodaBronson ArroyoLANCINCIN55.05644.944CIN123
12405-07-11Jon GarlandChris YoungLANNYNNYN55.45744.543NYN246
12507-18-2011Chad BillingsleyRyan VogelsongLANSFSF55.45744.543SF055
12604-18-2011Tim HudsonTed LillyATLLANATL55.65444.346LAN246
12707-16-2011Hiroki KurodaIan KennedyLANARIARI55.65444.346ARI235
12804-20-2011Derek LoweJon GarlandATLLANATL55.75244.248LAN167
12907-20-2011Clayton KershawTim LincecumLANSFSF55.8544.15LAN101
13009-22-2011Madison BumgarnerHiroki KurodaSFLANSF55.94744.053LAN2810
13106-24-2011Dan HarenRubby DeLaRosaLAALANLAA56.04443.956LAA8311
13205-22-2011Hiroki KurodaEdwin JacksonLANCHACHA56.80343.197CHA3811
13308-05-11Chad BillingsleyJosh CollmenterLANARIARI56.98943.011LAN7411
13404-25-2011Jon GarlandRicky NolascoLANFLAFLA57.17342.827FLA459
13507-19-2011Rubby DeLaRosaMadison BumgarnerLANSFSF57.35642.644SF358
13606-29-2011Rubby DeLaRosaScott BakerLANMINMIN57.71742.283MIN011
13707-03-11Chad BillingsleyErvin SantanaLANLAALAA57.98342.017LAA134
13808-06-11Nathan EovaldiJoe SaundersLANARIARI58.33341.667LAN538
13909-10-11Dana EvelandRyan VogelsongLANSFSF58.33341.667LAN303
14004-13-2011Ted LillyJonathan SanchezLANSFSF58.4241.58SF347
14105-20-2011Ted LillyPhil HumberLANCHACHA58.4241.58LAN6410
14208-24-2011Hiroki KurodaJaime GarciaLANSTLSTL58.59241.408LAN9413
14306-10-11Chad BillingsleyJhoulys ChacinLANCOLCOL58.93241.068COL5611
14409-06-11Ted LillyStephen StrasburgLANWASWAS59.140.9LAN7310
14509-03-11Nathan EovaldiMike MinorLANATLATL59.18440.816LAN213
14606-11-11Ted LillyJason HammelLANCOLCOL59.18440.816LAN11718
14705-21-2011Jon GarlandMark BuehrleLANCHACHA59.51440.486CHA2911
14807-17-2011Ted LillyDaniel HudsonLANARIARI60.15939.841ARI145
14909-02-11Chad BillingsleyBrandon BeachyLANATLATL60.86139.139LAN8614
15008-08-11Roy HalladayHiroki KurodaPHILANPHI61.01438.986PHI538
15108-15-2011Ted LillyRandy WolfLANMILMIL61.16538.835MIL033
15204-12-11Chad BillingsleyTim LincecumLANSFSF62.04937.951SF459
15309-26-2011Dana EvelandDaniel HudsonLANARIARI62.04937.951LAN426
15408-09-11Cliff LeeTed LillyPHILANPHI62.47737.523PHI213
15508-16-2011Chad BillingsleyYovanni GallardoLANMILMIL62.61737.383MIL123
15606-07-11Rubby DeLaRosaRoy OswaltLANPHIPHI62.89437.106LAN628
15706-08-11Hiroki KurodaCole HamelsLANPHIPHI63.83436.166PHI022
15806-06-11Ted LillyCliff LeeLANPHIPHI64.22235.778PHI134
15908-22-2011Nathan EovaldiChris CarpenterLANSTLSTL64.34935.651LAN213
16008-17-2011Nathan EovaldiZach GreinkeLANMILMIL65.45834.542MIL134
16106-12-11Rubby DeLaRosaUbaldo JimenezLANCOLCOL65.81234.188LAN10818


Saturday, November 05, 2011

Better Than Expected



... Or not enough respect!?



I have taken all the Vegas odds along with empirical 2011 results to tally up which MLB starting pitchers helped their team garner better than expected results. The methodology was to take the win percentage of the games each starting pitcher pitched in, then comparing that to the expected win percentage of those same games based on the win expectancy provided by Vegas odds. If a team was a 60% Vegas favorite to win a game then that pitcher was credited with 0.6 expected wins and 0.4 expected losses. I weighted the difference between actual and expected wins based off of games started. Below are the results...

RankPitcherTeam StartsWinsLossesWins(E)Losses(E)Win PercExp Win Perc
1Ian KennedyARI35251017.8917.1171.4351.12
2Clayton KershawLAN33231017.8315.1769.754.03
3Jason MarquisWAS2416810.9013.1066.6745.43
4Justin VerlanderDET37271022.1114.8972.9759.76
5Vance WorleyPHI2116511.549.4676.1954.96
6Rick PorcelloDET33211217.0315.9763.6451.6
7Zach GreinkeMIL3122918.0312.9770.9758.17
8Aaron HarangSD28171113.2314.7760.7147.25
9Mark BuehrleCHA30191115.2314.7763.3350.78
10Luke HochevarKC31181314.2416.7658.0645.92
11Dillon GeeNYN26161012.3013.7061.5447.31
12Matt HarrisonTEX34221218.3815.6264.7154.06
13Bruce ChenKC25151011.3913.616045.55
14Randy WolfMIL35211417.7617.246050.73
15Jeff NiemannTB2415911.8012.2062.549.18
16Javier VazquezFLA32181414.8517.1556.2546.42
17Jair JurrjensATL2316712.9110.0969.5756.15
18Justin MastersonCLE33201316.9616.0460.6151.39
19Roy HalladayPHI3425921.9612.0473.5364.59
20James ShieldsTB34211317.9816.0261.7652.87
21Jeff KarstensPIT28151312.0515.9553.5743.05
22Kyle DrabekTOR13946.166.8469.2347.41
23Tommy MiloneWAS5502.252.7510044.95
24Max ScherzerDET36221419.2716.7361.1153.53
25Derek HollandTEX35221319.2815.7262.8655.09
26Andrew MillerBOS12936.365.647552.96
27Ivan NovaNYA29191016.4212.5865.5256.63
28Jeanmar GomezCLE10734.605.417045.95
29Kevin CorreiaPIT26141211.7214.2853.8545.07
30Micah OwingsARI4401.782.2210044.55
31Johnny CuetoCIN2415912.8111.1962.553.38
32Jered WeaverLAA33211218.8814.1263.6457.21
33Josh BeckettBOS30201017.8912.1166.6759.62
34Mike MinorATL151058.026.9866.6753.47
35Yovanni GallardoMIL36221420.1515.8561.1155.98
36Phil HughesNYA151058.226.7866.6754.81
37Jake WestbrookSTL34191517.2216.7855.8850.66
38Wandy RodriguezHOU33161714.2318.7748.4843.12
39C.J. WilsonTEX40241622.2717.736055.67
40Jerome WilliamsLAA6513.272.7383.3354.49
41Tommy HunterBAL11654.316.6954.5539.15
42Wade DavisTB28161214.3213.6857.1451.15
43Kevin MillwoodCOL9634.334.6766.6748.11
44Chris YoungNYN5412.342.668046.77
45Eric SurkampSF5412.502.508049.91
46Wade MileyARI7523.513.4971.4350.1
47Brandon MorrowTOR30171315.5414.4656.6751.8
48Greg ReynoldsCOL3301.581.4210052.81
49Joe SaundersARI33171615.6117.3951.5247.29
50Ryan DempsterCHN34181616.6417.3652.9448.93
51Chris NarvesonMIL28161214.6413.3657.1452.29
52Nathan EovaldiLAN6422.643.3666.6744.06
53Cliff LeePHI33221120.6412.3666.6762.56
54Alex WhiteCLE10644.655.366046.45
55Zach BrittonBAL27141312.7214.2851.8547.11
56Carlos ZambranoCHN24131111.7212.2854.1748.84
57Ryan VogelsongSF28161214.7313.2757.1452.6
58Clay BuchholzBOS14957.756.2564.2955.39
59Brad PeacockWAS2200.791.2110039.73
60Jake ArrietaBAL2111109.8111.1952.3846.7
61Mike LeakeCIN26151113.8612.1457.6953.3
62Matt GarzaCHN30161414.8715.1453.3349.55
63Edwin JacksonCHA35191617.9117.0954.2951.16
64Daniel HudsonARI34191517.9116.0955.8852.67
65Randall DelgadoATL6422.923.0866.6748.62
66C.C. SabathiaNYA34221220.9213.0864.7161.53
67Miguel BatistaNYN4311.932.077548.14
68Gio GonzalezOAK32181416.9315.0756.2552.9
69Matt MooreTB2200.951.0610047.25
70Luis MendozaKC2200.951.0510047.37
71John NieseNYN26131311.9614.045046
72John LannanWAS33161714.9718.0348.4845.37
73Carlos VillanuevaTOR13766.026.9853.8546.28
74Ricky RomeroTOR33181517.0315.9754.5551.62
75Ross DetwilerWAS11655.045.9654.5545.84
76Josh JohnsonFLA9635.123.8866.6756.88
77Kyle LohseSTL33181517.1315.8754.5551.92
78Jo-Jo ReyesTOR26121411.1414.8646.1542.83
79Randy WellsCHN23111210.1412.8647.8344.08
80Tommy HansonATL2314913.179.8360.8757.27
81Brad LincolnPIT7433.213.7957.1445.8
82Jason VargasSEA32151714.2117.7946.8844.41
83Anthony BassSD3211.281.7266.6742.77
84Chien-Ming WangWAS10554.305.705042.97
85Matt PalmerLAA3211.301.7066.6743.35
86Dana EvelandLAN5322.362.646047.15
87Brandon DicksonSTL1100.370.6310036.83
88Josh CollmenterARI24131112.3711.6354.1751.56
89Dallas BradenOAK3211.391.6166.6746.4
90Aaron ThompsonPIT1100.440.5610043.57
91Josh TomlinCLE26131312.4413.565047.84
92Kyle KendrickPHI14867.456.5557.1453.21
93Brian GordonNYA1100.470.5310046.51
94Jesse LitschTOR8443.484.525043.49
95Kyle McClellanSTL181089.508.5055.5652.77
96Juan NicasioCOL13766.506.5053.8550.02
97Everett TeafordKC3211.511.4966.6750.3
98Jarrod ParkerARI1100.510.4910051.22
99Sergio MitreMIL1100.510.4910051.22
100Dan RunzlerSF1100.520.4810052.04
101Alan JohnsonCOL1100.540.4610053.6
102Matt BeavenSEA1100.540.4610053.6
103Joel PineiroLAA25131212.5512.465250.18
104Graham GodfreyOAK4221.562.445039.07
105Brian BurresPIT1100.570.4310056.99
106Andrew CashnerCHN1100.580.4210057.63
107James McDonaldPIT32151714.5917.4146.8845.58
108Chris JakubauskasBAL6332.583.425043.08
109Dylan AxelrodCHA3211.601.4066.6753.18
110Vin MazzaroKC4221.602.405039.92
111Freddy GarciaNYA27151214.6312.3755.5654.17
112Jordan ZimmermanWAS26131312.6413.365048.61
113Henderson AlvarezTOR10554.655.355046.54
114Rick VandenHurkBAL2110.681.325033.94
115Jeremy HellicksonTB30161415.7114.2953.3352.36
116Ross OhlendorfPIT9453.745.2644.4441.58
117Barry ZitoSF8443.784.225047.3
118Chris CapuanoNYN31151614.7916.2148.3947.7
119Nathan AdcockKC2110.791.215039.47
120Luis PerezTOR4221.832.175045.82
121Drew PomeranzCOL4221.862.145046.58
122Brian DuensingMIN27121511.9015.1044.4444.08
123Esmil RogersCOL13675.907.1046.1545.42
124Dave BushTEX2110.911.095045.43
125Jorge de la RosaCOL9544.924.0855.5654.64
126Guillermo MoscosoOAK2110119.9411.0647.6247.34
127Brian SanchesFLA2110.951.055047.45
128Alexi OgandoTEX30171316.9713.0456.6756.55
129Anthony SwarzakMIN11564.976.0345.4545.17
130Chad ReinekeCIN2111.010.995050.59
131Wade LeBlancSD14686.027.9842.8643.01
132Cory LuebkeSD17898.038.9747.0647.23
133Scott FeldmanTEX2111.030.975051.48
134Marco EstradaMIL6333.032.975050.52
135Brad MillsTOR4222.051.955051.16
136Lance LynnSTL2111.060.945052.82
137Alfredo SimonBAL15696.068.944040.4
138Cole HamelsPHI32191319.0612.9459.3859.57
139Zach DukeARI9454.064.9444.4445.14
140Mitch TalbotCLE12575.076.9341.6742.21
141Bartolo ColonNYA26141214.0911.9153.8554.19
142Daisuke MatsuzakaBOS7434.172.8357.1459.52
143Chris TillmanBAL14686.177.8342.8644.07
144Felix HernandezSEA33171617.2715.7351.5252.33
145Mitch AtkinsBAL3121.281.7233.3342.69
146Brad PennyDET31151615.3015.7048.3949.35
147Charlie MortonPIT28121612.3015.7042.8643.94
148Matt CainSF34181618.3215.6852.9453.87
149Dan HarenLAA33181518.3414.6654.5555.57
150D.J. CarrascoNYN1010.360.64036.1
151Tim WakefieldBOS23121112.3710.6352.1753.8
152Elih VillanuevaFLA1010.400.60039.76
153Jay BuenteFLA1010.420.58042.46
154Joe BlantonPHI9454.434.5744.4449.2
155Jake PeavyCHA18999.438.575052.41
156Nick BlackburnMIN26111511.4514.5542.3144.03
157Dustin McGowanTOR3121.451.5533.3348.47
158John ElyLAN1010.460.54046.19
159Felipe PaulinoKC219129.4611.5442.8645.06
160Alex CobbTB9454.474.5344.4449.67
161Homer BaileyCIN22111111.4710.535052.14
162Armando GalarragaARI8353.484.5237.543.52
163Carl PavanoMIN33141914.4818.5242.4243.88
164Sean O'SullivanKC10464.495.514044.87
165Scott KazmirLAA1010.490.51048.78
166Tyson RossOAK7343.493.5142.8649.89
167Julio TeheranATL3121.501.5033.3349.94
168Clay HensleyFLA8353.514.4937.543.88
169Jeff LockePIT4131.512.492537.87
170Doug FisterSEA33151815.5217.4845.4547.02
171Ervin SantanaLAA34171717.5216.485051.54
172Sam LeCureCIN5232.542.464050.8
173Brandon McCarthyOAK24111311.5612.4445.8348.17
174Alex SanabiaFLA2020.591.41029.27
175Tim HudsonATL33181518.6014.4054.5556.35
176Jaime GarciaSTL37201720.6116.3954.0555.69
177Madison BumgarnerSF33171617.6215.3851.5253.38
178Erik BedardSEA24121212.6211.385052.57
179Rodrigo LopezCHN177107.669.3441.1845.04
180Yunesky MayaWAS4131.662.342541.59
181Bud NorrisHOU31131813.6817.3241.9444.14
182Rubby DeLaRosaLAN10464.705.304046.99
183Liam HendriksMIN4131.732.272543.3
184R.A. DickeyNYN32151715.7416.2646.8849.19
185Jonathan SanchezSF199109.749.2647.3751.28
186Charles FurbushSEA10373.766.243037.57
187Brett MyersHOU33132013.7619.2439.3941.69
188Henry SosaHOU9363.785.2233.3342.05
189Francisco LirianoMIN24111311.7912.2145.8349.12
190Trevor CahillOAK33151815.7917.2145.4547.85
191Chad BillingsleyLAN32151715.8016.2046.8849.37
192Lucas HarrellHOU2020.841.16041.92
193Andy SonnanstineTB4131.842.162546.03
194Clay MortensenCOL6242.843.1633.3347.39
195Brett AndersonOAK13676.876.1346.1552.82
196Ramon OrtizCHN2020.901.10044.83
197Andrew OliverDET2020.901.10045.13
198Blake BeavanSEA14595.908.1035.7142.17
199Hector NoesiNYA2020.911.09045.32
200Bronson ArroyoCIN32151715.9216.0846.8849.74
201Colby LewisTEX35181718.9216.0851.4354.07
202Charlie FurbushDET2020.931.07046.73
203Scott BakerMIN219129.9511.0542.8647.37
204Zachary McAllisterCLE4131.962.042548.96
205Ted LillyLAN33151815.9717.0345.4548.39
206Neslon FigueroaHOU5141.993.012039.8
207Chris VolstadFLA29121712.9916.0141.3844.81
208Stephen StrasburgWAS5233.002.004060.08
209A.J. BurnettNYA32171518.0113.9953.1356.27
210Rich HardenOAK166107.048.9637.543.99
211Carlos CarrascoCLE2191210.0510.9542.8647.86
212John LackeyBOS28141415.0512.955053.76
213Garrett RichardsLAA3031.101.90036.69
214Tyler ChatwoodLAA24101411.1312.8741.6746.37
215Jeremy GuthrieBAL33141915.1317.8742.4245.85
216Brad HandFLA12485.196.8133.3343.21
217Jacob TurnerDET2021.200.80060.06
218Barry EnrightARI7253.213.7928.5745.88
219Travis WoodCIN16798.217.7943.7551.34
220Alfredo AcevesBOS4132.221.782555.59
221Tim StaufferSD31131814.3816.6241.9446.38
222Duane BelowDET3031.421.58047.48
223Mat LatosSD31141715.4715.5345.1649.9
224Aneury RodriguezHOU6152.513.4916.6741.88
225Jason HammelCOL27121513.5513.4544.4450.19
226Anthony VasquezSEA7162.624.3814.2937.36
227Phil HumberCHA26111512.6613.3442.3148.71
228Kyle DaviesKC144105.678.3328.5740.49
229Kyle WeilandBOS5142.672.332053.44
230David PriceTB35181719.7015.3051.4356.28
231Derek LoweATL34161817.7216.2847.0652.12
232Chris SchwindenNYN4041.762.24044.07
233Chris CarpenterSTL39201921.7917.2151.2855.86
234Scott DiamondMIN7162.804.2014.2940.03
235John DanksCHA27121513.9013.1044.4451.49
236Michael PinedaSEA28121613.9614.0442.8649.87
237David HuffCLE9273.975.0322.2244.06
238Gavin FloydCHA31141715.9915.0145.1651.59
239Tom GorzelannyWAS155107.017.9933.3346.76
240James RussellCHN5052.082.92041.56
241Fausto CarmonaCLE32131915.1316.8740.6347.27
242Ricky NolascoFLA33141916.1816.8242.4249.04
243Edinson VolquezCIN2081210.209.804050.99
244Josh OutmanOAK9274.204.8022.2246.65
245Clayton RichardSD186128.269.7433.3345.89
246Jon GarlandLAN9274.284.7222.2247.53
247Anibal SanchezFLA33141916.3316.6742.4249.49
248Hiroki KurodaLAN32141816.3615.6443.7551.12
249Zach StewartTOR11385.365.6427.2748.74
250Shaun MarcumMIL36171919.4716.5347.2254.08
251Tim LincecumSF34171719.6014.405057.64
252Mike PelfreyNYN33122114.6118.3936.3644.27
253Brett CecilTOR217149.7211.2833.3346.28
254Danny DuffyKC195147.7311.2726.3240.67
255Phil CokeDET144106.787.2228.5748.4
256Livan HernandezWAS29101912.7816.2234.4844.06
257Doug DavisCHN9183.815.1911.1142.3
258Aaron CookCOL175128.009.0029.4147.07
259Jordan LylesHOU153126.018.992040.07
260Casey ColemanCHN174137.029.9823.5341.27
261Jon LesterBOS31161519.0711.9351.6161.52
262Brad BergesenBAL122105.106.9016.6742.53
263Kevin SloweyMIN8083.444.56043.06
264Dontrelle WillisCIN154117.507.5026.6750.03
265Brandon BeachyATL25101513.6011.404054.39
266Roy OswaltPHI24101413.6510.3541.6756.88
267Brian MatuszBAL111104.806.209.0943.63
268Jhoulys ChacinCOL30121815.9414.064053.14
269Dustin MoseleySD205159.0310.972545.15
270Jeff FrancisKC31102114.1016.9032.2645.48
271Ubaldo JimenezCOL32131917.4614.5440.6354.55
272J.A. HappHOU2872111.8516.152542.31
273Paul MaholmPIT2671912.0113.9926.9246.18