One of the benefits of having a program that can accurately simulate a baseball game is that you can pretty much model anything and you can use the law of large numbers (or samples) to do the dirty work for you. In my latest exercise, I decided to take the 2013 Gold Glove winners from both the National and American leagues and have them play against each other. In order to make it fair, I ran sets of the simulation with each team being away/home and facing both a LH and RH starting pitcher. I gave both teams the exact identical starting pitcher, bench and bullpen so that the only difference were the starting players. I played by NL rules with no DH and gave both teams the same hitting skill for their pitcher. And afterwards, I did the same thing but this time made all the players league average fielders to see which side was better solely on offense.
The simulator also allows me to determine the most efficient lineup for both teams (facing RHP and LHP). The lineups that you see for both teams were the highest scoring lineups according to the simulator. I put in a limitation of not batting any left handed hitters back to back as this seems to be something that most MLB managers follow and I always batted the pitcher ninth.
Here are the lineups
vs RHP | GGNL | GGAL | vs LHP | GGNL | GGAL | |
---|---|---|---|---|---|---|
1 | G.Parra | D.Pedroia | 1 | G.Parra | D.Pedroia | |
2 | Y.Molina | A.Gordon | 2 | Y.Molina | S.Victorino | |
3 | P.Goldschmidt | S.Victorino | 3 | P.Goldschmidt | E.Hosmer | |
4 | C.Gonzalez | E.Hosmer | 4 | C.Gonzalez | A.Jones | |
5 | N.Arenado | A.Jones | 5 | N.Arenado | A.Gordon | |
6 | C.Gomez | S.Perez | 6 | A.Simmons | S.Perez | |
7 | A.Simmons | M.Machado | 7 | B.Phillips | M.Machado | |
8 | B.Phillips | J.Hardy | 8 | C.Gomez | J.Hardy | |
9 | Pitcher | Pitcher | 9 | Pitcher | Pitcher |
And here are the results
This table has all the players set to their defensive values.
Description | Away | Home | Winner | Away RS | Home RS | Win % | Total Runs |
---|---|---|---|---|---|---|---|
vs RHP | GGNL | GGAL | GGAL | 3.43 | 3.32 | 50.42 | 6.75 |
vs RHP | GGAL | GGNL | GGNL | 3.14 | 3.61 | 57.72 | 6.75 |
vs LHP | GGNL | GGAL | GGAL | 3.48 | 3.36 | 50.37 | 6.84 |
vs LHP | GGAL | GGNL | GGNL | 3.16 | 3.67 | 58.13 | 6.83 |
... and this table has all the players set to league average defensive values.
Description | Away | Home | Winner | Away RS | Home RS | Win % | Total Runs |
---|---|---|---|---|---|---|---|
vs RHP | GGNL | GGAL | GGAL | 3.77 | 3.80 | 52.19 | 7.57 |
vs RHP | GGAL | GGNL | GGNL | 3.60 | 3.97 | 56.33 | 7.57 |
vs LHP | GGNL | GGAL | GGAL | 3.82 | 3.84 | 52.10 | 7.66 |
vs LHP | GGAL | GGNL | GGNL | 3.63 | 4.04 | 56.69 | 7.67 |
Back Napkin Analysis:
It looks like the National League team is better both defensively and offensively. Now keep in mind that the results will reflect the input data or player projections both offensively and defensively. Not wanting to be biased, I used 2014 Steamer projections for the offense and I eye-balled the defensive values for each player from a mixture of UZR, FSR and Zips (if available). I tended not to go above 15 runs saved per 150 games for any player. Below are the defensive numbers I used for each player.
NL | AL | |
---|---|---|
C | Y.Molina (15) | S.Perez (13) |
1B | P.Goldschmidt (4) | E.Hosmer (3) |
2B | B.Phillips (8) | D.Pedroia (10) |
3B | N.Arenado (12) | M.Machado (15) |
SS | A.Simmons (15) | J.Hardy (10) |
LF | C.Gonzalez (10) | A.Gordon (7) |
CF | C.Gomez (13) | A.Jones (-3) |
RF | G.Parra (12) | S.Victorino (15) |
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