World Series Game 2 Projections
After a very surprising offensive explosion in the Lincecum v. Lee match-up in Game 1, the Giants look to head to Arlington with a 2-0 lead in the World Series. We don’t have a recap (yet), and I’m not sure if there will be a post dedicated to it. I’m sure you’re well aware of what happened though, being the World Series and all. I won’t go into detail, but rather just post the Win Probability Graph:
Tonight’s match-up will be Matt Cain taking on C.J. Wilson, and it sounds as though the lineups will be practically the same. There’s a possibility Matt Treanor catches rather than Bengie Molina, but that change would be very insignificant.
|Andres Torres||.362||18.5||4.8||Elvis Andrus||.305||-15.2||4.8|
|Freddy Sanchez||.335||3.3||4.68||Michael Young||.348||5.73||4.68|
|Aubrey Huff||.370||20.3||4.54||Josh Hamilton||.388||23.07||4.54|
|Buster Posey||.376||26.5||4.46||Vladimir Guerrero||.362||13.22||4.46|
|Pat Burrell||.343||4.6||4.34||Nelson Cruz||.387||26.51||4.34|
|Cody Ross||.331||0.8||4.23||Ian Kinsler||.359||11.98||4.23|
|Juan Uribe||.335||2.3||4.1||Bengie Molina||.302||-14.86||4.1|
|Edgar Renteria||.309||-11.8||3.98||Mitch Moreland||.358||14.6||3.98|
wOBA – Weighted On Base Average
rv600 – Run Value (Above Average) per 600 PA
ePA – Expected PA per lineup slot in the NL
Expected Giants RPG: 4.44
Expected Rangers RPG: 4.51
Here’s how the Matt Cain v. C.J. Wilson match-up looks:
tRA comes from StatCorner.
Bullpens are a fickle thing, and trying to eliminate the inferior pitchers from each team, as well as adjusting for injuries and such would simply create more noise (and work!) than necessary. Instead, we’ll just finish off each starter’s expected line with the bullpen performance this season (again using tERA). The Giants sit at 3.46 with the Rangers at 3.97. However, when converting to the NL we get an adjusted tRA for the Rangers of 3.68.
|Starter IP||Starter RA||Bullpen IP||Bullpen RA||Total RA|
I exclude defense because of the volatility of it in a 7 game series (and simply one game in this scenario), especially with no huge difference between the two defenses.
Using the Odds Ratio combined with the pythagorean records from these expected numbers, we get these results:
Again, I’m changing home-field advantage adjustments. I completely undervalued the advantage by using the runs scored and allowed method. The issue isn’t just that the home team pitches and hits better, but rather, they play better altogether; runs, runs allowed and in the clutch and high leverage situations. Teams at home win more 1-run games than they lose. If you simply use the pythagorean formula to calculate expected home W% you get a team that wins around 53% of its home games. When in reality, the home team (this year, in both leagues), has a .5625 W%, or an extra 3.125% advantage. I’m simply going to apply these adjustments to the chance of victory and not go into expected final score, as there’s way too much noise there to predict (although I understand that it was just there for fun). As of now, extra work would have to be put into that with my limited information and resources.
Very similar to Game 1 in that two pitchers with almost identical expected performances (combined with very similar bullpens), and the advantage for the Rangers offense. And of course once again, in a neutral environment the expected result from this match-up would be virtually 50/50. However with the home-field advantage the Giants once again have odds hovering around 56%, a bit higher than yesterday’s 54% chance of victory. I’d say the Giants might even have a bigger advantage considering Matt Cain has historically out-performed his peripherals by over half a run – something that has been discussed a lot – especially at home. Going up 2-0 in this series would be tremendous for the Giants. And if it does happen, well, I’m not sure I’ll be able to contain myself for much longer.