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.

Player	Pos		Player	Pos
Angels			Royals
Maicer Izturis	3B		Melky Cabrera	CF
Bobby Abreu	DH		Mike Aviles	3B
Torii Hunter	RF		Billy Butler	DH
Kendry Morales	1B		Kila Kaaihue	1B
Vernon Wells	LF		Alex Gordon	LF
Howie Kendrick	2B		Jeff Francoeur	RF
Erick Aybar	SS		Brayan Pena	C
Jeff Mathis	C		Chris Getz	2B
Peter Bourjos	CF		Alcides Escobar	SS

... And now the results!

Away	Home			Favorite	Win Prob	Over/Under
LAA	KC	Jered Weaver	Luke Hochevar	LAA	59.07%	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)

Name	AB	Hits	H1	H2	H3	HR	RBI	BB	SO	wOBA	BABIP
Maicer Izturis	4.533	1.329	0.781	0.412	0.033	0.102	0.478	0.363	0.704	0.353	0.329
Bobby Abreu	4.231	1.264	0.755	0.329	0.024	0.156	0.547	0.592	0.928	0.385	0.352
Torii Hunter	4.343	1.246	0.775	0.303	0.007	0.16	0.606	0.359	0.826	0.352	0.323
Kendry Morales	4.208	1.265	0.751	0.338	0.017	0.159	0.657	0.386	0.681	0.372	0.328
Vernon Wells	4.182	1.202	0.68	0.319	0.025	0.178	0.68	0.304	0.682	0.359	0.308
Howie Kendrick	4.158	1.311	0.804	0.373	0.051	0.082	0.532	0.214	0.7	0.362	0.364
Erick Aybar	4.004	1.15	0.761	0.259	0.079	0.052	0.446	0.262	0.637	0.333	0.331
Jeff Mathis	3.889	0.909	0.584	0.238	0.015	0.072	0.417	0.268	0.825	0.283	0.28
Peter Bourjos	3.866	1.023	0.647	0.256	0.061	0.06	0.414	0.185	0.726	0.307	0.313
Melky Cabrera	4.263	1.14	0.698	0.327	0.057	0.059	0.358	0.305	0.756	0.319	0.314
Mike Aviles	4.237	1.244	0.831	0.297	0.021	0.095	0.435	0.21	0.727	0.334	0.336
Billy Butler	4.049	1.177	0.716	0.332	0.004	0.126	0.505	0.33	0.764	0.353	0.333
Kila Kaaihue	3.963	0.999	0.678	0.209	0.014	0.098	0.429	0.359	0.917	0.31	0.306
Alex Gordon	3.806	1.002	0.627	0.237	0.014	0.124	0.472	0.413	0.928	0.337	0.319
Jeff Francoeur	3.824	1.017	0.672	0.22	0.015	0.11	0.437	0.23	0.825	0.316	0.314
Brayan Pena	3.676	0.907	0.65	0.223	0.005	0.028	0.288	0.268	0.822	0.283	0.311
Chris Getz	3.607	0.932	0.597	0.236	0.048	0.052	0.347	0.267	0.693	0.309	0.308
Alcides Escobar	3.549	0.905	0.616	0.198	0.053	0.038	0.323	0.181	0.681	0.291	0.306

And the pitchers boxscore

Name	IP	SO	BB	Hits	HR	PC	FIP
Jered Weaver	6.396	5.274	1.652	6.738	0.545	99.864	3.434
Fernando Rodney	0.481	0.36	0.181	0.49	0.03	7.691	3.657
Scott Downs	0.404	0.288	0.104	0.426	0.025	6.231	3.353
Kevin Jepsen	0.602	0.484	0.252	0.614	0.033	9.812	3.565
Jordan Walden	0.297	0.249	0.129	0.31	0.028	4.901	4.058
Hisanori Takahashi	0.433	0.316	0.159	0.477	0.043	7.003	4.141
Rich Thompson	0.216	0.134	0.079	0.251	0.023	3.496	4.47
Bobby Cassevah	0.016	0.008	0.007	0.018	0.001	0.261	4.256
Luke Hochevar	5.9	4.097	1.755	7.014	0.696	94.648	4.238
Joakim Soria	0.39	0.418	0.073	0.357	0.023	5.929	2.372
Blake Wood	0.451	0.322	0.144	0.523	0.051	7.259	4.202
Robison Tejeda	0.759	0.675	0.272	0.806	0.069	12.341	3.673
Tim Collins	0.453	0.321	0.19	0.534	0.053	7.547	4.568
Jeremy Jeffress	0.914	0.641	0.385	1.053	0.08	15.143	4.203
Jesse Chavez	0.332	0.232	0.112	0.405	0.049	5.435	4.749
Kanekoa Texeira	0.005	0.003	0.002	0.006	0	0.087	3.739

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.

Player	Pos		Player	Pos
Giants			Dodgers
Andres Torres	CF		Rafael Furcal	SS
Freddy Sanchez	2B		Andre Ethier	RF
Aubrey Huff	1B		Matt Kemp	CF
Buster Posey	C		James Loney	1B
Pat Burrell	LF		Juan Uribe	2B
Miguel Tejada	SS		Jay Gibbons	LF
Cody Ross	RF		Casey Blake	3B
Pablo Sandoval	3B		Rod Barajas	C
Tim Lincecum	SP		Clayton Kershaw	SP

... And now the results

Away	Home			Favorite	Win Prob	Over/Under
SF	LAN	Tim Lincecum	Clayton Kershaw	LAN	53.972	5.81217

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

Name	AB	Hits	H1	H2	H3	HR	RBI	BB	SO	wOBA	BABIP
Andres Torres	4.27	1.006	0.576	0.317	0.025	0.088	0.282	0.337	1.287	0.296	0.317
Freddy Sanchez	4.218	1.16	0.772	0.309	0.01	0.069	0.301	0.281	1.002	0.318	0.347
Aubrey Huff	4.065	1.028	0.696	0.2	0.012	0.12	0.377	0.378	0.957	0.315	0.304
Buster Posey	4.054	0.997	0.694	0.236	0.004	0.063	0.344	0.304	1.043	0.29	0.317
Pat Burrell	3.824	0.881	0.525	0.226	0.002	0.128	0.427	0.433	1.29	0.309	0.313
Miguel Tejada	3.941	1.025	0.713	0.241	0.006	0.066	0.348	0.197	0.705	0.295	0.303
Cody Ross	3.738	0.862	0.557	0.206	0.005	0.095	0.346	0.288	1.165	0.287	0.31
Pablo Sandoval	3.467	0.718	0.465	0.18	0.006	0.067	0.289	0.422	1.375	0.279	0.321
Tim Lincecum	3.657	0.335	0.265	0.059	0.001	0.009	0.1	0.147	2.201	0.115	0.225
Rafael Furcal	4.043	1.025	0.652	0.264	0.037	0.072	0.24	0.347	0.867	0.31	0.307
Andre Ethier	3.87	0.971	0.568	0.249	0.011	0.144	0.376	0.448	1.021	0.333	0.306
Matt Kemp	3.95	0.947	0.605	0.202	0.03	0.11	0.37	0.272	1.205	0.297	0.318
James Loney	3.784	0.969	0.6	0.27	0.015	0.083	0.381	0.395	0.78	0.322	0.303
Juan Uribe	3.771	0.892	0.544	0.212	0.019	0.117	0.421	0.249	0.862	0.296	0.278
Jay Gibbons	3.578	0.816	0.473	0.2	0.007	0.137	0.4	0.363	0.838	0.308	0.261
Casey Blake	3.508	0.808	0.504	0.206	0.009	0.089	0.325	0.257	1.031	0.287	0.301
Rod Barajas	3.419	0.745	0.478	0.176	0.005	0.086	0.307	0.224	0.811	0.271	0.261
Clayton Kershaw	3.424	0.346	0.279	0.055	0.002	0.01	0.091	0.125	1.857	0.122	0.216

Pitchers Boxscore

Name	IP	SO	BB	Hits	HR	PC	FIP
Tim Lincecum	6.488	7.057	1.889	5.41	0.621	100.544	3.143
Brian Wilson	0.474	0.582	0.124	0.338	0.029	7.2	2.319
Sergio Romo	0.439	0.485	0.101	0.359	0.041	6.651	2.891
Ramon Ramirez	0.625	0.452	0.212	0.609	0.066	9.751	4.147
Santiago Casilla	0.288	0.264	0.116	0.243	0.023	4.557	3.606
Chris Ray	0.38	0.276	0.159	0.376	0.047	6.104	4.59
Guillermo Mota	0.185	0.144	0.071	0.175	0.019	2.928	4.167
Denny Bautista	0.013	0.013	0.007	0.01	0.002	0.208	4.38
Clayton Kershaw	6.524	7.602	1.939	5.644	0.469	102.81	2.696
Johnathan Broxton	0.482	0.72	0.155	0.318	0.031	7.593	2.021
HongZhi Kuo	0.508	0.687	0.132	0.375	0.023	7.85	1.854
Kenley Jansen	0.732	0.959	0.245	0.555	0.042	11.602	2.339
Matt Guerrier	0.345	0.279	0.098	0.348	0.038	5.375	3.875
Vicente Padilla	0.621	0.622	0.159	0.602	0.077	9.695	3.567
Ron Mahay	0.161	0.15	0.054	0.162	0.022	2.587	4.131
Blake Hawksworth	0.007	0.007	0.002	0.007	0.001	0.118	3.974

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)...

Team	Prediction
AL East
Yankees	The Yankees will finish near .500 due to bad injuries to both Alex Rodriguez and Derek Jeter. Russell Martin will get Madonna pregnant.
Red Sox	The Red Sox win over 100 games, easily winning the once mighty AL East. New comer Adrian Gonzalez is the AL MVP.
Rays	The 2011 Rays turn out to be a sham and finish below .500. Top Prospect Jeremy Hellickson blows out his elbow in June.
Blue Jays	The Blue Jays will find a sucker to unload Vernon Wells on. Oh wait…
Orioles	The 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
Twins	The 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 Sox	Heads roll as the White Sox struggle and win only 78 games. Head coach Ozzie Guillen gets fired after making a profanity laced racist comment.
Tigers	The 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.
Indians	The 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.
Royals	The Royals have a terrible season winning only 57 games. Moustakas gets called up in late June and makes a run at ROY.
AL West
Rangers	Lots of disappointment in Arlington where the Rangers get knocked out of playoff contention on the last day of the season.
Athletics	The A's are the first team to 20 wins and hold off a late charge from the Rangers to win the NL West.
Angels	A major league worst 14 game losing streak in May drops the Angels out of contention early on. They finish with 75 wins.
Mariners	A 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 East	Red Sox
AL Central	Twins
AL West	Atheletics
Wild-Card	Orioles
Cy Young	Max Scherzer
MVP	Adrian Gonzalez
ROY	Michael Pineda
AL Champ	Atheletics

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...

Away	Home	Away SP	Home SP	Favorite	Win Probability
NL	AL	Clayton Kershaw	Clay Buccholz	AL	50.509
AL	NL	Clay Buchholz	Clayton Kershaw	NL	61.487
NL	AL	Tommy Hanson	Justin Masterson	AL	52.045
AL	NL	Justin Masterson	Tommy Hanson	NL	58.186
NL	AL	Mat Latos	Kyle Drabek	NL	57.194
AL	NL	Kyle Drabek	Mat Latos	NL	67.676
NL	AL	Travis Wood	Gio Gonzalez	AL	53.619
AL	NL	Gio Gonzalez	Travis Wood	NL	55.999
NL	AL	Jaime Garcia	Doug Fister	AL	52.062
AL	NL	Doug Fister	Jaime Garcia	NL	57.789

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.

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.

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.

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.

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

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

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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