## Phillies vs Dodgers, Game #2 Simulation

I used my simulator to simulate 100000 baseball games between the Phillies and Dodgers using what to the best of my knowledge will be close to today's starting lineups.  The simulator outputs a win probability for each team, along with the average total runs scored, a distribution matrix of all the final scores and how often they occurred, and an averaged box score tally of all games combined.  You may find it strange that there are so many one run games listed as the most likely score, and that the home team is always favored to win in the top couple of scores.  This is due to basic math and the way that baseball rules play out of having the home team bat last.  Here is a great article explaining this phenomenon.

Today's Results... (Last simulation ran on Thursday at 9:30PM)

 Visitors Home Pitching Matchup Favorite Vegas Win Prob Simulator Win Prob AccuScore PHI LAN P.Martinez vs V.Padilla LAN 57.63% 56.70% TBD

Skinny:  Simulator Fun Facts... My simulator and Vegas are in very good agreement on the Game #2 win probabilities.  The Game #1 loss dropped the Dodgers 'Series Win Probability' down to 38.1%.  A win tomorrow will raise it back up to 51.9%, while a loss would drop it to a depressing 19.9%.

 Top 50 Most Likely Scores 1 LAN 4-3 2 LAN 5-4 3 LAN 3-2 4 LAN 6-5 5 PHI 4-3 6 LAN 2-1 7 PHI 3-2 8 LAN 4-2 9 LAN 5-3 10 PHI 5-4 11 LAN 3-1 12 LAN 5-2 13 PHI 5-3 14 LAN 7-6 15 PHI 4-2 16 LAN 6-3 17 PHI 6-5 18 PHI 5-2 19 LAN 6-4 20 PHI 6-4 21 LAN 6-2 22 PHI 3-1 23 LAN 4-1 24 PHI 2-1 25 PHI 6-3 26 LAN 8-7 27 PHI 4-1 28 LAN 5-1 29 PHI 6-2 30 LAN 7-5 31 LAN 7-4 32 LAN 7-3 33 PHI 7-5 34 LAN 7-2 35 PHI 7-6 36 PHI 7-4 37 PHI 7-3 38 PHI 5-1 39 LAN 1-0 40 LAN 3-0 41 PHI 7-2 42 LAN 6-1 43 PHI 6-1 44 LAN 8-4 45 LAN 7-1 46 LAN 8-3 47 LAN 2-0 48 LAN 8-5 49 PHI 8-7 50 PHI 8-3

 Game Pitching Results Pitcher IP SO BB HR WHIP FIP P.Martinez 6.5 4.910 2.096 0.850 1.458 4.365 V.Padilla 6.6 5.056 2.514 0.858 1.381 4.491

Note: Keep in mind I did this simulation before knowing the actual starting lineups, so some of the players I used may not be starting.   Many of the "Players Most Likely To" stats depend on having the correct lineup.  The lineups  I used are listed below.  Chances are you won't see a big difference in win probability from having the lineup order slightly off.  Picking the correct starters is more important, especially if one of the better players is taking the day off.  But you still won't see a big change in win probability if the starter and backup are interchangeable.

 Simulation Lineups Name wOBA Name wOBA 1 J.Rollins .3267 R.Furcal .3336 2 S.Victorino .3361 M.Kemp .3526 3 C.Utley .3694 A.Ethier .3829 4 R.Howard .3769 M.Ramirez .4070 5 J.Werth .3446 C.Blake .3521 6 R.Ibanez .3513 J.Loney .3626 7 P.Feliz .2927 R.Belliard .3401 8 C.Ruiz .3046 R.Martin .3369 9 P.Martinez .1486 V.Padilla .1625

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