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NLCS Game 2 Projections: Giants @ Phillies

October 17, 2010
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Player wOBA rv600 ePA   Player wOBA rv600 ePA
Andres Torres .362 18.5 4.8   Shane Victorino .351 11.2 4.8
Freddy Sanchez .335 3.3 4.68   Placido Polanco .335 2.4 4.68
Aubrey Huff .370 20.3 4.54   Chase Utley .385 29.1 4.54
Buster Posey .376 26.5 4.46   Ryan Howard .370 21.1 4.46
Pat Burrell .343 4.6 4.34   Jayson Werth .384 28.5 4.34
Juan Uribe .335 2.3 4.23   Jimmy Rollins .328 -0.6 4.23
Mike Fontenot .334 2.7 4.1   Raul Ibanez .361 17.1 4.1
Cody Ross .331 0.8 3.98   Carlos Ruiz .343 5.6 3.98
Pitcher .216 -59.3 3.86   Pitcher .216 -59.3 3.86

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: 4.55

Expected Phillies RPG: 4.79

The Game 2 starters will be Jonathan Sanchez taking on Roy Oswalt. Both Oswalt and Sanchez have pitched really well lately, and Sanchez has done well against the Phillies and their left-handed bats.

  ERA FIP tRA IP
Jonathan Sanchez 3.95 4.06 4.16 5.6
Roy Oswalt 3.41 3.62 3.72 6.3

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 tRA). The Giants sit at 3.46 with the Phillies at 3.93.

  Starter IP Starter RA Bullpen IP Bullpen RA Total RA
Giants 5.6 2.60 3.4 1.30 3.90
Phillies 6.3 2.59 1.5 1.20 3.79

I exclude defense because of the volatility of it in a 7 game series, 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:

Team eRS eRA x-W% % Victory
Giants 4.55 3.90 .570 45.68%
Phillies 4.79 3.76 .609 54.32%

 

Here’s my method for factoring in home-field, which I implemented during the NLDS: Rather than applying the +5% in expected winning%, I’ll apply the expected runs scored and allowed to the NL runs scored averages in home ballparks, rather than the league average. By using runs scored and allowed rather than wins and losses, we of course get a more precise measurement of home-field advantages. This also gives me a way to predict a more accurate expected final score, which just makes this whole process more attractive. And on to the numbers:

NL Home Runs Per Game: 4.474

NL Road Runs Per Game: 4.175

NL Runs Per Game: 4.325

Here are the expected numbers when adjusting for home-field:

Team eRS eRA x-W% % Victory
Giants 4.48 3.97 .554 43.13%
Phillies 4.87 3.72 .621 56.87%

Expected Final Score: Phillies 4.42, Giants 4.1

As expected, the odds aren’t in the Giants favor so much tonight. However, we’ll see what happens, as there’s still a very reasonable chance for victory, especially if Sanchez has his control.

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