Friday, February 25, 2011

Angels vs Royals, Opening Day Simulation


Now let's look ahead for the Angels. It is March 31st, opening day and the Angels are on the road playing the Kansas City Royals. The opening day starters are likely to be Jered Weaver vs Luke Hochevar. Lineups and depth charts are taken from MLBDepthCharts.com and I know that some players (K.Morales) may not be ready by opening day. I ran the likely lineups through my baseball simulator for 100K games. Below are a detailed look at the results for us baseball starved fans.

PlayerPos PlayerPos
AngelsRoyals
Maicer Izturis3B Melky CabreraCF
Bobby AbreuDH Mike Aviles3B
Torii HunterRF Billy ButlerDH
Kendry Morales1B Kila Kaaihue1B
Vernon WellsLF Alex GordonLF
Howie Kendrick2B Jeff FrancoeurRF
Erick AybarSS Brayan PenaC
Jeff MathisC Chris Getz2B
Peter BourjosCF Alcides EscobarSS


... And now the results!

AwayHome  FavoriteWin ProbOver/Under
LAAKCJered WeaverLuke HochevarLAA59.07%8.55


No surprise as it looks like the Angels will be a solid favorite on the road in the season opener, but of course anything can happen.

Here is the hitters boxscore(s)
NameABHitsH1H2H3HRRBIBBSOwOBABABIP
Maicer Izturis4.5331.3290.7810.4120.0330.1020.4780.3630.7040.3530.329
Bobby Abreu4.2311.2640.7550.3290.0240.1560.5470.5920.9280.3850.352
Torii Hunter4.3431.2460.7750.3030.0070.160.6060.3590.8260.3520.323
Kendry Morales4.2081.2650.7510.3380.0170.1590.6570.3860.6810.3720.328
Vernon Wells4.1821.2020.680.3190.0250.1780.680.3040.6820.3590.308
Howie Kendrick4.1581.3110.8040.3730.0510.0820.5320.2140.70.3620.364
Erick Aybar4.0041.150.7610.2590.0790.0520.4460.2620.6370.3330.331
Jeff Mathis3.8890.9090.5840.2380.0150.0720.4170.2680.8250.2830.28
Peter Bourjos3.8661.0230.6470.2560.0610.060.4140.1850.7260.3070.313
            
Melky Cabrera4.2631.140.6980.3270.0570.0590.3580.3050.7560.3190.314
Mike Aviles4.2371.2440.8310.2970.0210.0950.4350.210.7270.3340.336
Billy Butler4.0491.1770.7160.3320.0040.1260.5050.330.7640.3530.333
Kila Kaaihue3.9630.9990.6780.2090.0140.0980.4290.3590.9170.310.306
Alex Gordon3.8061.0020.6270.2370.0140.1240.4720.4130.9280.3370.319
Jeff Francoeur3.8241.0170.6720.220.0150.110.4370.230.8250.3160.314
Brayan Pena3.6760.9070.650.2230.0050.0280.2880.2680.8220.2830.311
Chris Getz3.6070.9320.5970.2360.0480.0520.3470.2670.6930.3090.308
Alcides Escobar3.5490.9050.6160.1980.0530.0380.3230.1810.6810.2910.306


And the pitchers boxscore
NameIPSOBBHitsHRPCFIP
Jered Weaver6.3965.2741.6526.7380.54599.8643.434
Fernando Rodney0.4810.360.1810.490.037.6913.657
Scott Downs0.4040.2880.1040.4260.0256.2313.353
Kevin Jepsen0.6020.4840.2520.6140.0339.8123.565
Jordan Walden0.2970.2490.1290.310.0284.9014.058
Hisanori Takahashi0.4330.3160.1590.4770.0437.0034.141
Rich Thompson0.2160.1340.0790.2510.0233.4964.47
Bobby Cassevah0.0160.0080.0070.0180.0010.2614.256
        
Luke Hochevar5.94.0971.7557.0140.69694.6484.238
Joakim Soria0.390.4180.0730.3570.0235.9292.372
Blake Wood0.4510.3220.1440.5230.0517.2594.202
Robison Tejeda0.7590.6750.2720.8060.06912.3413.673
Tim Collins0.4530.3210.190.5340.0537.5474.568
Jeremy Jeffress0.9140.6410.3851.0530.0815.1434.203
Jesse Chavez0.3320.2320.1120.4050.0495.4354.749
Kanekoa Texeira0.0050.0030.0020.00600.0873.739


Friday, February 18, 2011

Giants vs Dodgers, Opening Day Simulated Preview


The 2011 season begins for the Dodgers on March 31st at home in a game against the defending champions the San Francisco Giants. The starters for the game have already been announced. The Giants will start their long haired hippy, Tim Lincecum - while the Dodgers will counter with their clean cut and wholesome ace Clayton Kershaw, in what will be a classic matchup of Evil vs Good. I have gone ahead and simulated this game, making a guess at the starting lineups 100K times. Below are the lineups used and the results.

PlayerPos PlayerPos
Giants  Dodgers 
Andres TorresCF Rafael FurcalSS
Freddy Sanchez2B Andre EthierRF
Aubrey Huff1B Matt KempCF
Buster PoseyC James Loney1B
Pat BurrellLF Juan Uribe2B
Miguel TejadaSS Jay GibbonsLF
Cody RossRF Casey Blake3B
Pablo Sandoval3B Rod BarajasC
Tim LincecumSP Clayton KershawSP


... And now the results

AwayHome  FavoriteWin ProbOver/Under
SFLANTim LincecumClayton KershawLAN53.9725.81217


So we see that the Dodgers will likely be a slight favorite to win on opening day, but a win probability of just under 54% is pretty much a toss up game.

Here is the hitters boxscore
NameABHitsH1H2H3HRRBIBBSOwOBABABIP
Andres Torres4.271.0060.5760.3170.0250.0880.2820.3371.2870.2960.317
Freddy Sanchez4.2181.160.7720.3090.010.0690.3010.2811.0020.3180.347
Aubrey Huff4.0651.0280.6960.20.0120.120.3770.3780.9570.3150.304
Buster Posey4.0540.9970.6940.2360.0040.0630.3440.3041.0430.290.317
Pat Burrell3.8240.8810.5250.2260.0020.1280.4270.4331.290.3090.313
Miguel Tejada3.9411.0250.7130.2410.0060.0660.3480.1970.7050.2950.303
Cody Ross3.7380.8620.5570.2060.0050.0950.3460.2881.1650.2870.31
Pablo Sandoval3.4670.7180.4650.180.0060.0670.2890.4221.3750.2790.321
Tim Lincecum3.6570.3350.2650.0590.0010.0090.10.1472.2010.1150.225
            
Rafael Furcal4.0431.0250.6520.2640.0370.0720.240.3470.8670.310.307
Andre Ethier3.870.9710.5680.2490.0110.1440.3760.4481.0210.3330.306
Matt Kemp3.950.9470.6050.2020.030.110.370.2721.2050.2970.318
James Loney3.7840.9690.60.270.0150.0830.3810.3950.780.3220.303
Juan Uribe3.7710.8920.5440.2120.0190.1170.4210.2490.8620.2960.278
Jay Gibbons3.5780.8160.4730.20.0070.1370.40.3630.8380.3080.261
Casey Blake3.5080.8080.5040.2060.0090.0890.3250.2571.0310.2870.301
Rod Barajas3.4190.7450.4780.1760.0050.0860.3070.2240.8110.2710.261
Clayton Kershaw3.4240.3460.2790.0550.0020.010.0910.1251.8570.1220.216


Pitchers Boxscore
NameIPSOBBHitsHRPCFIP
Tim Lincecum6.4887.0571.8895.410.621100.5443.143
Brian Wilson0.4740.5820.1240.3380.0297.22.319
Sergio Romo0.4390.4850.1010.3590.0416.6512.891
Ramon Ramirez0.6250.4520.2120.6090.0669.7514.147
Santiago Casilla0.2880.2640.1160.2430.0234.5573.606
Chris Ray0.380.2760.1590.3760.0476.1044.59
Guillermo Mota0.1850.1440.0710.1750.0192.9284.167
Denny Bautista0.0130.0130.0070.010.0020.2084.38
        
Clayton Kershaw6.5247.6021.9395.6440.469102.812.696
Johnathan Broxton0.4820.720.1550.3180.0317.5932.021
HongZhi Kuo0.5080.6870.1320.3750.0237.851.854
Kenley Jansen0.7320.9590.2450.5550.04211.6022.339
Matt Guerrier0.3450.2790.0980.3480.0385.3753.875
Vicente Padilla0.6210.6220.1590.6020.0779.6953.567
Ron Mahay0.1610.150.0540.1620.0222.5874.131
Blake Hawksworth0.0070.0070.0020.0070.0010.1183.974


Thursday, February 17, 2011

2011 Wild and Crazy Baseball Predictions, AL Style


First a disclaimer. These team predictions are for entertainment purposes only. In some cases they may reflect my genuine sentiment of a team (or one or more of its players), but exaggerated to make them more entertaining. Hopefully at the end of the season, I can look back on these and see that more than one was close to being correct. Normally my posts are about probabilities, stats and are based in logic (well, hopefully they are) - but this is an escape from all of that for one day. Behold below, my 2011 wild and crazy baseball predictions for the American League (NL is next up)...

TeamPrediction
AL East
YankeesThe Yankees will finish near .500 due to bad injuries to both Alex Rodriguez and Derek Jeter. Russell Martin will get Madonna pregnant.
Red SoxThe Red Sox win over 100 games, easily winning the once mighty AL East. New comer Adrian Gonzalez is the AL MVP.
RaysThe 2011 Rays turn out to be a sham and finish below .500. Top Prospect Jeremy Hellickson blows out his elbow in June.
Blue JaysThe Blue Jays will find a sucker to unload Vernon Wells on. Oh wait…
OriolesThe Orioles who had the fourth best record in all of baseball from August 1st on, will make the playoffs as the AL wild-card team.
AL Central
TwinsThe Twins have their early struggles but Joe Mauer and the underrated Twins pitching staff carry the team past the finish line as they narrowly win the AL Central title.
White SoxHeads roll as the White Sox struggle and win only 78 games. Head coach Ozzie Guillen gets fired after making a profanity laced racist comment.
TigersThe Tigers are the first place team headed into September, lead by the AL Cy Young Max Scherzer. They falter down the stretch and end up in second place and out of the playoffs.
IndiansThe Indians finish comfortably ahead of the Royals, which is not saying much. Shin Soo Choo narrowly misses becoming the first Korean player to win an MVP.
RoyalsThe Royals have a terrible season winning only 57 games. Moustakas gets called up in late June and makes a run at ROY.
AL West
RangersLots of disappointment in Arlington where the Rangers get knocked out of playoff contention on the last day of the season.
AthleticsThe A's are the first team to 20 wins and hold off a late charge from the Rangers to win the NL West.
AngelsA major league worst 14 game losing streak in May drops the Angels out of contention early on. They finish with 75 wins.
MarinersA dead cat bounce and a great season from ROY Michael Pineda propel the Mariners to a last place tie with the Angels.


Post-Season
AL EastRed Sox
AL CentralTwins
AL WestAtheletics
Wild-CardOrioles
Cy YoungMax Scherzer
MVPAdrian Gonzalez
ROYMichael Pineda
AL ChampAtheletics


Monday, February 14, 2011

AL Zero to Three VS NL Zero to Three


In case you haven't been following the series over at FanGraphs, Jonah Keri has put together an AL and NL All-Star team from players with less than three years of major league service, who are making at or near league minimum. The NL Zero to Three team was posted first, followed by the AL Zero to Three team. I volunteered to run a simulation between the two rosters to see which was the stronger team.

Here are the results...

AwayHomeAway SPHome SPFavoriteWin Probability
NLALClayton KershawClay BuccholzAL50.509
ALNLClay BuchholzClayton KershawNL61.487
NLALTommy HansonJustin MastersonAL52.045
ALNLJustin MastersonTommy HansonNL58.186
NLALMat LatosKyle DrabekNL57.194
ALNLKyle DrabekMat LatosNL67.676
NLALTravis WoodGio GonzalezAL53.619
ALNLGio GonzalezTravis WoodNL55.999
NLALJaime GarciaDoug FisterAL52.062
ALNLDoug FisterJaime GarciaNL57.789


As expected the NL team dominates this simulation. Their average win probability over the 10 games is 55.01%. If you put that in per 162 games, the NL team would win 89.12 games.

Saturday, February 12, 2011

Minor League Contract Team vs NL Zero to Three Team


In my next series in pitting "theme" teams against one another comes a series of games between the "All Minor League Contract" team and the "NL Zero to Three" team. As you can probably figure out the MiLB Contract team is made up of the best players signed to minor league contracts in 2011. The NL 0-3 team is made up of the best NL players with less than or equal to three years of experience while making close to league minimum. These two themes were created at FanGraphs recently. The MiLB Contract team was created by Dave Cameron in a blog entry here. The NL 0-3 team was created by Jonah Keri and can be found here. Obviously the NL 0-3 team will dominate such a matchup. This is a warmup to the NL 0-3 vs AL 0-3 coming next week. Rosters and results are below.

Lineups
MiLB Contract NL Zero to Three
Pos Name Org Name Pos Org
CF Lastings Milledge CHA CF Andrew McCutchen PIT
LF Laynce Nix WAS LF Logan Morrison FLA
RF Jeremy Hermida CIN RF Jayson Heyward ATL
3B Felipe Lopez TB C Buster Posey SF
1B Casey Kotchman TB 1B Ike Davis NYN
C Gregg Zaun SD 3B Pedro Alvarez PIT
2B Adam Kennedy SEA 2B Neil Walker PIT
SS Adam Everett CLE SS Starlin Castro CHN
SP Pitchers Spot NA SP Pitchers Spot NA

Now let's take a look at the starting rotations...
MiLB Contracts NL Zero to Three
  Name Organization   Name Organization
#1 Freddy Garcia NYY vs Clayton Kershaw LAN
#2 Micah Owings ARI vs Tommy Hanson ATL
#3 J.D. Martin WAS vs Mat Latos SD
#4 Jeff Suppan SF vs Travis Wood CIN
#5 Rodrigo Lopez ATL vs Jaime Garcia STL


Next up... the results

Results
Away Away SP Home Home SP Favorite Win Prob Total Runs
MiLB Contracts Freddy Garcia NL Zero to Three Clayton Kershaw NL Zero to Three 72.75% 7.34
NL Zero to Three Clayton Kershaw MiLB Contracts Freddy Garcia NL Zero to Three 63.34% 7.48
MiLB Contracts Micah Owings NL Zero to Three Tommy Hanson NL Zero to Three 71.54% 7.83
NL Zero to Three Tommy Hanson MiLB Contracts Micah Owings NL Zero to Three 62.99% 7.92
MiLB Contracts J.D. Martin NL Zero to Three Mat Latos NL Zero to Three 73.20% 7.65
NL Zero to Three Mat Latos MiLB Contracts J.D. Martin NL Zero to Three 64.43% 7.78
MiLB Contracts Jeff Suppan NL Zero to Three Travis Wood NL Zero to Three 71.20% 7.92
NL Zero to Three Travis Wood MiLB Contracts Jeff Suppan NL Zero to Three 62.27% 8.01
MiLB Contracts Rodrigo Lopez NL Zero to Three Jaime Garcia NL Zero to Three 72.19% 7.81
NL Zero to Three Jaime Garcia MiLB Contracts Rodrigo Lopez NL Zero to Three 63.30% 7.91


Mean win percentage for the "NL Zero to Three" team is 67.72%. Extrapolated out to a make believe 162 game season of head to head games, the "NL Zero to Three" team would be expected to win an astounding 109.7 games and suffer only 52.3 losses.

Simulator Notes: My simulator takes into account (among other things) park factors, home field advantage, defense, splits, base running and uses a proprietary set of hitter and pitcher projections for MLB players.

Thursday, February 10, 2011

Minor League All-Stars vs Dodgers



I've recently imported some minor league stats from ZIPS projections into my simulator and created a minor league All-Star team based off of the ZIPS projections (MLEs) of the best minor leaguers that have yet to crack the major leagues.  I then pit that team against a major league team to see how well they match up.  So far I have matched them up against the Royals and the Phillies.  The minor league All-Star team actually beat the Royals, winning an average of 51.72% of the time.  The Phillies on the other hand won 65.67% of the time.  Now I take a look at how the Dodgers did.  There are still a handful of teams that ZIPS does not have projections for at this time, so players from those teams are not eligible for the minor league All-Star team yet.  Jerry Sands is the only Dodgers to crack the minor league All-Star team (starting left fielder).

The methodology I used was to have each #1 starting pitcher face each other, both away and home. I then did the same thing for the #2 thru #5 pitchers, thus having a 10 game series. Each of the 10 games was simulated/played 100K times with the simulator spitting out a win probability for each game. I decided to use the same bullpens for each team (the Dodgers bullpen) and give all of the minor league players a league average defensive rating.

Here are the rosters of the two teams that I used.  Keep in mind that lineups don't matter much.

Lineups
AAA All-Stars Los Angeles Dodgers
Pos Name Org Name Pos
CF Charles Blackmon COL SS Rafael Furcal
C Devin Mesoraco CIN CF Matt Kemp
1B Brandon Belt SF RF Andre Ethier
3B Mike Moustakas KC 2B Juan Uribe
LF Jerry Sands
LAN 1B James Loney
RF J.D. Martinez
HOU LF Marcus Thames
2B Daniel Descalso
STL 3B Casey Blake
SS Grant Green
OAK C Rod Barajas
P Pitcher NA P Pitcher



Now let's take a look at the starting rotations.

AAA All-Stars Los Angeles Dodgers
  Name Organization   Name
#1 Michael Pineda SEA vs Clayton Kershaw
#2 Julian Teheran ATL vs Chad Billingsley
#3 Jake McGee TB vs Hiroki Kuroda
#4 Christian Freidrich COL vs Ted Lilly
#5 Mike Montgomery KC vs Jon Garland



Now let's take a look at the game results...

Results
Away Away SP Home Home SP Favorite Win Prob
Dodgers Clayton Kershaw
AAA All-Stars Michael Pineda
Dodgers 58.44%
AAA All-Stars Michael Pineda Dodgers Clayton Kershaw
Dodgers 70.65%
Dodgers Chad Billingsley
AAA All-Stars Julian Teheran Dodgers 56.59%
AAA All-Stars Julian Teheran Dodgers Chad Billingsley
Dodgers 69.43%
Dodgers Hiroki Kuroda
AAA All-Stars Jake McGee Dodgers 50.68%
AAA All-Stars Jake McGee Dodgers Hiroki Kuroda
Dodgers 63.65%
Dodgers Ted Lilly
AAA All-Stars Christian Freidrich Dodgers 52.91%
AAA All-Stars Christian Freidrich Dodgers Ted Lilly
Dodgers 64.83%
Dodgers Jon Garland
AAA All-Stars Mike Montgomery AAA All-Stars
52.67%
AAA All-Stars Mike Montgomery Dodgers Jon Garland
Dodgers 60.16%



Mean win percentage for the Dodgers is 59.47%. So using the ZIPS projections as input for the AAA All-Star team and my proprietary set of projections for the Dodgers, the AAA All-Star team, the Dodgers beat up the AAA All-Star team pretty bad, a little bit worse than how badly the Dodgers would beat up the Diamondbacks.


Simulator Notes: My simulator takes into account (among other things) park factors, home field advantage, defense, splits, base running and uses a proprietary set of hitter and pitcher projections for MLB players.

Wednesday, February 09, 2011

All-Star Prospect Team vs Phillies

In my previous post I looked at how a minor league All-Star team would do against a bad American League team like the Kansas City Royals. That previous post pointed out that using my baseball simulator, the minor league All-Star team was a slightly stronger team than the Royals. Now I have matched that same minor league All-Star team up against one of the juggernaughts from the National League, the Phillies. For details of how I selected the minor league All-Star team please see my previous post.

In this exercise I had each #1 starting pitcher face each other, both away and home. I then did the same thing for the #2 thru #5 pitchers, thus having a 10 game series. Each of the 10 games was simulated/played 100K times with the simulator spitting out a win probability for each game. I decided to use the same bullpens for each team (the Phillies bullpen) and give all of the minor league players a league average defensive rating.

Here are the rosters of the two teams that I used.

Lineups
AAA All-Stars Philadelphia Phillies
Pos Name Org Name Pos
CF Charles Blackmon COL SS Jimmy Rollins
C Devin Mesoraco CIN 3B Placido Polanco
1B Brandon Belt SF 2B Chase Utley
3B Mike Moustakas KC 1B Ryan Howard
LF Jerry Sands LAN LF Raul Ibanez
RF J.D. Martinez HOU CF Shane Victorino
2B Daniel Descalso STL RF Dominic Brown
SS Grant Green OAK C Carlos Ruiz
P Pitchers Spot NA P Pitchers Spot

Now let's take a look at the starting rotations.

AAA All-Stars Philadelphia Phillies
  Name Organization   Name
#1 Michael Pineda SEA vs Roy Halladay
#2 Julian Teheran ATL vs Cliff Lee
#3 Jake McGee TB vs Roy Oswalt
#4 Christian Freidrich COL vs Cole Hamels
#5 Mike Montgomery KC vs Kyle Kendrick

Now let's take a look at the game results...

Results
Away Away SP Home Home SP Favorite Win Prob
Phillies Roy Halladay AAA All-Stars Michael Pineda Phillies 61.27%
AAA All-Stars Michael Pineda Phillies Roy Halladay Phillies 72.80%
Phillies Cliff Lee AAA All-Stars Julian Teheran Phillies 63.94%
AAA All-Stars Julian Teheran Phillies Cliff Lee Phillies 74.93%
Phillies Roy Oswalt AAA All-Stars Jake McGee Phillies 56.58%
AAA All-Stars Jake McGee Phillies Roy Oswalt Phillies 68.64%
Phillies Cole Hamels AAA All-Stars Christian Freidrich Phillies 63.06%
AAA All-Stars Christian Freidrich Phillies Cole Hamels Phillies 74.70%
Phillies Kyle Kendrick AAA All-Stars Mike Montgomery Phillies 51.52%
AAA All-Stars Mike Montgomery Phillies Kyle Kendrick Phillies 63.42%

Mean win percentage for the Phillies is 65.09%. So using the ZIPS projections as input for the minor league All-Star team and my proprietary set of projections for the Philadelphia Phillies, the Phillies maul the minor league All-Star team. I may attempt to run this exercise against one more major league team.

Simulator Notes: My simulator takes into account (among other things) park factors, home field advantage, defense, splits, base running and uses a proprietary set of hitter and pitcher projections for MLB players.

Helpful Sources:
MLB Depth Charts
Fangraphs

All-Star Prospect Team vs KC Royals


A FanPost at the Beyond The Boxscore a few weeks ago got me thinking about how well a team pieced together from the minor leagues best prospects would do playing against major league teams. What a perfect exercise to use my simulator for. What I did is took the ZIPS projections of the best minor leaguers and used them as input into my baseball simulator and played this imaginary team against a real MLB team. I filtered these minor leaguers to only use players under the age of 25 with little or no MLB experience. There are still a handful of teams that ZIPS does not have projections for at this time, so players from those teams are not eligible yet.

After building my minor league All-Star team, the first team I decided to have them face was the Kansas City Royals, who are likely the American Leagues worst team. In this exercise I had each #1 starting pitcher face each other, both away and home. I then did the same thing for the #2 thru #5 pitchers, thus having a 10 game series. Each of the 10 games was simulated/played 100K times with the simulator spitting out a win probability for each game. I decided to use the same bullpens for each team (the Royals bullpen) and give all of the minor league players a league average defensive rating.

Here are the rosters of the two teams that I used.

Lineups
AAA All-Stars Kansas City Royals
Pos Name Org Name Pos
CF Charles Blackmon COL CF Melky Cabrera
C Devin Mesoraco CIN 2B Chris Getz
1B Brandon Belt SF LF Alex Gordon
3B Mike Moustakas KC DH Billy Butler
DH Freddie Freeman ATL RF Jeff Francoeur
LF Jerry Sands LAN 1B Kaile Kaaihue
RF J.D. Martinez HOU 3B Mike Aviles
2B Daniel Descalso STL C Jason Kendall
SS Grant Green OAK SS Alcides Escobar



Now let's take a look at the starting rotations.

AAA All-Stars Kansas City Royals
  Name Organization   Name
#1 Michael Pineda SEA vs Luke Hochevar
#2 Julian Teheran ATL vs Kyle Davies
#3 Jake McGee TB vs Bruce Chen
#4 Christian Freidrich COL vs Vinny Mazzaro
#5 Mike Montgomery KC vs Jeff Francis



Now let's take a look at the game results...

Results
Away Away SP Home Home SP Favorite Win Prob
Royals Luke Hochever AAA All-Stars Michael Pineda AAA All-Stars 56.57%
AAA All-Stars Michael Pineda Royals Luke Hochever Royals 52.55%
Royals Kyle Davies AAA All-Stars Julian Teheran AAA All-Stars 55.24%
AAA All-Stars Julian Teheran Royals Kyle Davies Royals 53.69%
Royals Bruce Chen AAA All-Stars Jake McGee AAA All-Stars 59.77%
AAA All-Stars Jake McGee Royals Bruce Chen AAA All-Stars 50.03%
Royals Vinny Mazzaro AAA All-Stars Christian Freidrich AAA All-Stars 55.71%
AAA All-Stars Christian Freidrich Royals Vinny Mazzaro Royals 53.04%
Royals Jeff Francis AAA All-Stars Mike Montgomery AAA All-Stars 53.99%
AAA All-Stars Mike Montgomery Royals Jeff Francis Royals 54.80%



Mean win percentage for the AAA All-Stars is 51.722%. So using the ZIPS projections as input for the AAA All-Star team and my proprietary set of projections for the Kansas City Royals, the AAA All-Star team is slightly stronger. Up next, I will attempt to run this same exercise with a National League team - probably a good one. I am thinking about doing it for the Phillies.


Simulator Notes: My simulator takes into account (among other things) park factors, home field advantage, defense, splits, base running and uses a proprietary set of hitter and pitcher projections for MLB players.



Friday, February 04, 2011

DBacks vs Dodgers, 2011 Pre-Season Simulations




In the previous days, I've looked at the Dodgers simulations against the Giants , Rockies and Padres, now it's time to look at the final NL West opponent, the Arizona Diamondbacks. In this exercise, each pitching matchup was simulated 100K times with each team taking a shot at being both the away and home team. Below are the lineups, starting rotations used as well as the results (50). A hit tip to Jim McLellan from AZ Snakepit for helping me out with the Diamondbacks batting lineups.

Diamondbacks Starting Lineup Dodgers Starting Lineup
Diamondbacks vs LHP Diamondbacks vs RHP   Dodgers vs LHP Dodgers vs RHP
Order Pos Name Pos Name   Pos Name Pos Name
1 SS S.Drew SS S.Drew   SS R.Furcal SS R.Furcal
2 CF C.Young RF J.Upton   CF M.Kemp CF M.Kemp
3 2B K.Johnson 2B K.Johnson   RF A.Ethier RF A.Ethier
4 RF J.Upton CF C.Young   3B C.Blake 1B J.Loney
5 C M.Montero C M.Montero   2B J.Uribe 3B C.Blake
6 LF X.Nady LF X.Nady   LF M.Thames 2B J.Uribe
7 3B M.Mora 1B J.Miranda   1B J.Loney LF J.Gibbons
8 1B J.Miranda 3B M.Mora   C R.Barajas C R.Barajas


Diamondbacks Rotation Dodgers Rotation
#1 Daniel Hudson #1 Clayton Kershaw
#2 Ian Kennedy #2 Chad Billingsley
#3 Joe Saunders #3 Hiroki Kuroda
#4 Zach Duke #4 Ted Lilly
#5 Armando Galarraga #5 Jon Garland


Simulation Results
Away Starter Home Starter Favorite Win Prob
Daniel Hudson Clayton Kershaw Dodgers 63.32%
Clayton Kershaw Daniel Hudson Dodgers 53.45%
Daniel Hudson Chad Billingsley Dodgers 64.59%
Chad Billingsley Daniel Hudson Dodgers 54.03%
Daniel Hudson Hiroki Kuroda Dodgers 62.27%
Hiroki Kuroda Daniel Hudson Dodgers 52.08%
Daniel Hudson Ted Lilly Dodgers 54.44%
Ted Lilly Daniel Hudson Diamondbacks 54.75%
Daniel Hudson Jon Garland Dodgers 55.13%
Jon Garland Daniel Hudson Diamondbacks 55.93%
Ian Kennedy Clayton Kershaw Dodgers 65.79%
Clayton Kershaw Ian Kennedy Dodgers 55.39%
Ian Kennedy Chad Billingsley Dodgers 66.93%
Chad Billingsley Ian Kennedy Dodgers 56.19%
Ian Kennedy Hiroki Kuroda Dodgers 64.73%
Hiroki Kuroda Ian Kennedy Dodgers 54.25%
Ian Kennedy Ted Lilly Dodgers 56.88%
Ted Lilly Ian Kennedy Diamondbacks 52.54%
Ian Kennedy Jon Garland Dodgers 52.18%
Jon Garland Ian Kennedy Diamondbacks 53.45%
Joe Saunders Clayton Kershaw Dodgers 67.00%
Clayton Kershaw Joe Saunders Dodgers 57.28%
Joe Saunders Chad Billingsley Dodgers 68.20%
Chad Billingsley Joe Saunders Dodgers 57.86%
Joe Saunders Hiroki Kuroda Dodgers 65.78%
Hiroki Kuroda Joe Saunders Dodgers 56.17%
Joe Saunders Ted Lilly Dodgers 58.32%
Ted Lilly Joe Saunders Diamondbacks 50.40%
Joe Saunders Jon Garland Dodgers 58.59%
Jon Garland Joe Saunders Diamondbacks 51.62%
Zach Duke Clayton Kershaw Dodgers 69.01%
Clayton Kershaw Zach Duke Dodgers 58.97%
Zach Duke Chad Billingsley Dodgers 69.91%
Chad Billingsley Zach Duke Dodgers 59.55%
Zach Duke Hiroki Kuroda Dodgers 67.66%
Hiroki Kuroda Zach Duke Dodgers 57.76%
Zach Duke Ted Lilly Dodgers 59.83%
Ted Lilly Zach Duke Dodgers 50.99%
Zach Duke Jon Garland Dodgers 60.73%
Jon Garland Zach Duke Dodgers 50.26%
Armando Galarraga Clayton Kershaw Dodgers 70.65%
Clayton Kershaw Armando Galarraga Dodgers 61.77%
Armando Galarraga Chad Billingsley Dodgers 71.93%
Chad Billingsley Armando Galarraga Dodgers 62.22%
Armando Galarraga Hiroki Kuroda Dodgers 69.74%
Hiroki Kuroda Armando Galarraga Dodgers 60.46%
Armando Galarraga Ted Lilly Dodgers 62.30%
Ted Lilly Armando Galarraga Dodgers 54.05%
Armando Galarraga Jon Garland Dodgers 62.82%
Jon Garland Armando Galarraga Dodgers 52.93%


When you average the combined win probability of all fifty games, the Dodgers have an average win probability of 58.42%. Extrapolated out over a 162 game season the Dodgers would win 94.65 games and the Diamondbacks would win 67.35. The Diamondbacks will likely struggle this year.

Sources:
MLB Depth Charts
Fangraphs
AZ Snakepit


Thursday, February 03, 2011

Padres vs Dodgers, 2011 Pre-Season Simulations




On the heels of the Giants/Dodgers and Rockies/Dodgers 2011 simulated matchups that didn't look all that good for the Dodgers, I present to you the Padres/Dodgers 2011 simulated matchups. This time the good guys come out on top. In this exercise, each pitching matchup was simulated 100K times with each team taking a shot at being both the away and home team. Below are the lineups, starting rotations used as well as the results (50).

Padres Starting Lineup Dodgers Starting Lineup
Padres vs LHP Padres vs RHP   Dodgers vs LHP Dodgers vs RHP
Order Pos Name Pos Name   Pos Name Pos Name
1 SS J.Bartlett SS J.Bartlett   SS R.Furcal SS R.Furcal
2 2B O.Hudson 2B O.Hudson   CF M.Kemp CF M.Kemp
3 3B C.Headley 3B C.Headley   RF A.Ethier RF A.Ethier
4 RF R.Ludwick RF R.Ludwick   3B C.Blake 1B J.Loney
5 1B J.Cantu 1B B.Hawpe   2B J.Uribe 3B C.Blake
6 LF C.Denorfia LF W.Venable   LF M.Thames 2B J.Uribe
7 CF C.Maybin CF C.Maybin   1B J.Loney LF J.Gibbons
8 C G.Zaun C N.Hundley   C R.Barajas C R.Barajas


Padres Rotation Dodgers Rotation
#1 Mat Latos #1 Clayton Kershaw
#2 Clayton Richard #2 Chad Billingsley
#3 Wade LeBlanc #3 Hiroki Kuroda
#4 Aaron Harang #4 Ted Lilly
#5 Tim Stauffer #5 Jon Garland


Simulation Results
Away Starter Home Starter Favorite Win Prob
Mat Latos Clayton Kershaw Dodgers 55.54%
Clayton Kershaw Mat Latos Padres 53.87%
Mat Latos Chad Billingsley Dodgers 53.87%
Chad Billingsley Mat Latos Padres 56.37%
Mat Latos Hiroki Kuroda Dodgers 52.50%
Hiroki Kuroda Mat Latos Padres 58.18%
Mat Latos Ted Lilly Padres 52.84%
Ted Lilly Mat Latos Padres 61.37%
Mat Latos Jon Garland Padres 55.76%
Jon Garland Mat Latos Padres 65.06%
Clayton Richard Clayton Kershaw Dodgers 60.58%
Clayton Kershaw Clayton Richard Padres 50.86%
Clayton Richard Chad Billingsley Dodgers 58.18%
Chad Billingsley Clayton Richard Padres 53.01%
Clayton Richard Hiroki Kuroda Dodgers 54.62%
Hiroki Kuroda Clayton Richard Padres 53.81%
Clayton Richard Ted Lilly Dodgers 51.41%
Ted Lilly Clayton Richard Padres 56.19%
Clayton Richard Jon Garland Padres 52.18%
Jon Garland Clayton Richard Padres 61.25%
Wade LeBlanc Clayton Kershaw Dodgers 67.23%
Clayton Kershaw Wade LeBlanc Dodgers 56.64%
Wade LeBlanc Chad Billingsley Dodgers 64.88%
Chad Billingsley Wade LeBlanc Dodgers 54.41%
Wade LeBlanc Hiroki Kuroda Dodgers 62.80%
Hiroki Kuroda Wade LeBlanc Dodgers 52.81%
Wade LeBlanc Ted Lilly Dodgers 58.72%
Ted Lilly Wade LeBlanc Dodgers 50.17%
Wade LeBlanc Jon Garland Dodgers 55.13%
Jon Garland Wade LeBlanc Padres 54.33%
Aaron Harang Clayton Kershaw Dodgers 67.06%
Clayton Kershaw Aaron Harang Dodgers 55.69%
Aaron Harang Chad Billingsley Dodgers 64.89%
Chad Billingsley Aaron Harang Dodgers 53.94%
Aaron Harang Hiroki Kuroda Dodgers 61.68%
Hiroki Kuroda Aaron Harang Dodgers 53.26%
Aaron Harang Ted Lilly Dodgers 58.50%
Ted Lilly Aaron Harang Dodgers 50.36%
Aaron Harang Jon Garland Dodgers 55.95%
Jon Garland Aaron Harang Padres 55.36%
Tim Stauffer Clayton Kershaw Dodgers 60.32%
Clayton Kershaw Tim Stauffer Dodgers 50.38%
Tim Stauffer Chad Billingsley Dodgers 59.55%
Chad Billingsley Tim Stauffer Padres 52.37%
Tim Stauffer Hiroki Kuroda Dodgers 57.23%
Hiroki Kuroda Tim Stauffer Padres 52.45%
Tim Stauffer Ted Lilly Dodgers 51.89%
Ted Lilly Tim Stauffer Padres 55.39%
Tim Stauffer Jon Garland Padres 51.32%
Jon Garland Tim Stauffer Padres 60.23%


When you average the combined win probability of all fifty games, the Dodgers have an average win probability of 51.96%. Extrapolated out over a 162 game season the Dodgers would win 84.17 games and the Padres would win 77.83. The simulator is showing the Dodgers as the stronger of the two teams, but it is fairly close.

Fantasy Baseball Mock Draft Software

Tuesday, February 01, 2011

Rockies vs Dodgers, 2011 Pre-Season Simulations




On the heels of the Giants/Dodgers 2011 simulated matchups, I present to you the Rockies/Dodgers 2011 simulated matchups. Each pitching matchup was simulated 100K times with each team taking a shot at being both the away and home team. Below are the lineups, starting rotations used as well as the results (50).

Rockies Starting Lineup Dodgers Starting Lineup
Rockies vs LHP Rockies vs RHP   Dodgers vs LHP Dodgers vs RHP
Order Pos Name Pos Name   Pos Name Pos Name
1 CF D.Fowler CF D.Fowler   SS R.Furcal SS R.Furcal
2 2B J.Lopez RF S.Smith   CF M.Kemp CF M.Kemp
3 RF C.Gonzalez LF C.Gonzalez   RF A.Ethier RF A.Ethier
4 SS T.Tulowitzki SS T.Tulowitzki   3B C.Blake 1B J.Loney
5 LF R.Spilborghs 3B I.Stewart   2B J.Uribe 3B C.Blake
6 1B T.Wigginton 1B T.Helton   LF M.Thames 2B J.Uribe
7 3B I.Stewart 2B J.Lopez   1B J.Loney LF J.Gibbons
8 C C.Iannetta C C.Iannetta   C R.Barajas C R.Barajas


Rockies Rotation Dodgers Rotation
#1 Ubaldo Jimenez #1 Clayton Kershaw
#2 Jorge de la Rosa #2 Chad Billingsley
#3 Jason Hammel #3 Hiroki Kuroda
#4 Jhoulys Chacin #4 Ted Lilly
#5 Aaron Cook #5 Jon Garland


Simulation Results
Away Starter Home Starter Favorite Win Prob
Ubaldo Jimenez Clayton Kershaw Dodgers 53.81%
Clayton Kershaw Ubaldo Jimenez Rockies 58.17%
Ubaldo Jimenez Chad Billingsley Dodgers 51.40%
Chad Billingsley Ubaldo Jimenez Rockies 61.09%
Ubaldo Jimenez Hiroki Kuroda Rockies 50.81%
Hiroki Kuroda Ubaldo Jimenez Rockies 62.88%
Ubaldo Jimenez Ted Lilly Rockies 55.18%
Ted Lilly Ubaldo Jimenez Rockies 66.35%
Ubaldo Jimenez Jon Garland Rockies 58.51%
Jon Garland Ubaldo Jimenez Rockies 70.16%
Jorge de la Rosa Clayton Kershaw Dodgers 59.47%
Clayton Kershaw Jorge de la Rosa Rockies 52.54%
Jorge de la Rosa Chad Billingsley Dodgers 57.12%
Chad Billingsley Jorge de la Rosa Rockies 55.36%
Jorge de la Rosa Hiroki Kuroda Dodgers 55.16%
Hiroki Kuroda Jorge de la Rosa Rockies 57.18%
Jorge de la Rosa Ted Lilly Dodgers 50.59%
Ted Lilly Jorge de la Rosa Rockies 60.82%
Jorge de la Rosa Jon Garland Rockies 52.03%
Jon Garland Jorge de la Rosa Rockies 64.87%
Jason Hammel Clayton Kershaw Dodgers 58.40%
Clayton Kershaw Jason Hammel Rockies 52.78%
Jason Hammel Chad Billingsley Dodgers 56.26%
Chad Billingsley Jason Hammel Rockies 55.44%
Jason Hammel Hiroki Kuroda Dodgers 53.75%
Hiroki Kuroda Jason Hammel Rockies 57.65%
Jason Hammel Ted Lilly Rockies 51.08%
Ted Lilly Jason Hammel Rockies 61.29%
Jason Hammel Jon Garland Rockies 53.77%
Jon Garland Jason Hammel Rockies 65.41%
Jhoulys Chacin Clayton Kershaw Dodgers 56.28%
Clayton Kershaw Jhoulys Chacin Rockies 55.41%
Jhoulys Chacin Chad Billingsley Dodgers 53.64%
Chad Billingsley Jhoulys Chacin Rockies 58.53%
Jhoulys Chacin Hiroki Kuroda Dodgers 51.34%
Hiroki Kuroda Jhoulys Chacin Rockies 60.18%
Jhoulys Chacin Ted Lilly Rockies 52.95%
Ted Lilly Jhoulys Chacin Rockies 63.90%
Jhoulys Chacin Jon Garland Rockies 55.94%
Jon Garland Jhoulys Chacin Rockies 67.62%
Aaron Cook Clayton Kershaw Dodgers 61.99%
Clayton Kershaw Aaron Cook Dodgers 51.81%
Aaron Cook Chad Billingsley Dodgers 59.82%
Chad Billingsley Aaron Cook Rockies 51.60%
Aaron Cook Hiroki Kuroda Dodgers 57.61%
Hiroki Kuroda Aaron Cook Rockies 53.40%
Aaron Cook Ted Lilly Dodgers 53.33%
Ted Lilly Aaron Cook Rockies 56.79%
Aaron Cook Jon Garland Dodgers 50.20%
Jon Garland Aaron Cook Rockies 61.21%


When you average the combined win probability of all fifty games, the Rockies have an average win probability of 53.38%. Extrapolated out over a 162 game season the Rockies would win 86.47 games and the Dodgers would win 75.53. The simulator is showing the Rockies as the stronger of the two teams, but it is close enough that the Dodgers could reasonably finish with a better record than the Rockies due to randomness.

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