Dodgers Simulation, September 14th
I used my simulator to simulate 25000 baseball games between the Pirates 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.
Today's Results... (Last simulation ran at 7:30AM)
| Visitors | Home | Pitching Matchup | Favorite | Vegas Win Prob | Simulator Win Prob | Over/Under | AccuScore |
| PIT | LAN | D.McCutchen vs J.Garland | LAN | 70.59% | 66.56% | 8.4 / 9.88 | 72% |
Skinny: Simulator Fun Facts... The Dodgers are rather large favorites to knock off the Pirates and rookie pitcher Daniel McCutchen. Vegas splits the middle a 70.59% win probability for the Dodgers, while AccuScore puts the Dodgers chances of winning at 72%. My simulator isn't sold on Garland as much as the other two sources, but is still giving the Dodgers a 66.56% chance of winning. I would expect the 70+% win probability for perhaps a Kershaw or Wolf start, but not a Garland start. Just like the two home games the Dodgers lost as heavy favorites against the Padres, the Dodgers should win tonight's game.
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Top 10 Most Likely Scores |
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| 1 | LAN 4-3 |
| 2 | LAN 5-4 |
| 3 | LAN 3-2 |
| 4 | LAN 6-5 |
| 5 | LAN 5-3 |
| 6 | LAN 4-2 |
| 7 | PIT 5-4 |
| 8 | LAN 7-6 |
| 9 | PIT 4-3 |
| 10 | LAN 2-1, LAN 6-3 |
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Pitching Stats |
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| Pitcher | WHIP | FIP |
| D.McCutchen | 1.637 | 5.171 |
| J.Garland | 1.297 | 4.043 |
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 | ||
| 1 | A.McCutchen | R.Furcal |
| 2 | D.Young | M.Kemp |
| 3 | G.Jones | A.Ethier |
| 4 | L.Milledge | M.Ramirez |
| 5 | R.Doumit | C.Blake |
| 6 | B.Moss | J.Loney |
| 7 | A.LaRoche | R.Martin |
| 8 | R.Cedeno | O.Hudson |
| 9 | D.McCutchen | J.Garland |
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Comments
Over 70% favorites. I think that’s an automatic bet for Pittsburgh. Will the ML come in around high 180 or even 200?
I have recently started to pay attention to your simulator...
Why are the most likely scores usually a one run difference?
Good question. For a couple of reasons.
1) The rules of baseball. The home team bats last and all walk off runs (except for some walk off HRs) give the home team a one run win. Also in games the home team wins in the top of the 9th inning, the visiting team is given one extra at-bat than the home team and often climbs to within one run.
2) Baseball games are pretty much crapshoots. Crapshoots with a slightly loaded pair of dice in most cases, but crapshoots nonetheless. Following from this is that the distribution of scoring differentials are going to have more close games. On top of this, when you look at the distribution of total runs scored in a game, there are more samples on the left side of the average than on the right hand side. You may have an over/under of 9 runs, but the most likely score would be something like 4-3 (seven total runs). There are a smattering of high scoring games throwing the average runs per game higher. So while you have “more” lower scoring games than the average, you have a few very high scoring games throwing the average up. Low scoring games are usually close games, thus even more one run games.
Hope this made a little sense.
vr, Xei

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