Pitching Matchup: Dillon Gee (2-2, 4.50 ERA) vs. Cliff Lee (0-1, 1.96 ERA)
LV Money Line Open: PHI -195
LV Over / Under Open: 7.0
It has not been a particularly enjoyable week following Phillies baseball. Though the frustrating losses had nothing to do with my lack of posting, it was nice taking a break from blogging predictions. I spent some of the week making updates to the model, which hopefully will be improvements.
One of the benefits of simulation models over power ratings is that you can more easily adjust for injuries. Trying to back out a single individual's contribution to a team's power rating is very difficult if your rating is simply an opponent adjusted scoring margin calculated from points scored data. A model such as this allows for just such an adjustment, but how about when the opposite is true: How does the model account for players coming back from injury? The short answer is that it doesn't, not implicitly anyhow. The individual player statistical projections might account for them, but not typically in the case of a short DL stint. You might have realized what (rather whom) I'm referring to with this whole line of discussion: Clifton Phifer Lee. Tonight Cliff Lee is activated from the 15 day DL and will start against Dillon Gee. A big question is whether he will be his typically dominant self. Another question is whether he'll be on a diminshed pitch count. Regardless of what Charlie says prior to the game, do you really think he's pulling Cliff Lee if it's the 8th inning of a one run game because he's just over the 80 pitch limit he wanted to keep him to? After all the struggles of the bullpen, I don't think there is any way Charlie's pulling him in that situation. So back to the intial question: how is the model accounting for all this? I'll say again, it's not, though it could. I could manually (forgive the pun) adjust downward Cliff Lee's batters faced limit so that the model will pull him from the game earlier than normal. I could also attempt to analyze the first start off the DL of a pool of similar pitchers coming back from a similar injury. I could compare their performance in this first start versus their prior performance and use this change to adjust the outcome probabilities for Cliff Lee tonight. Unfortunately I don't have a data set readily available to do this, and even if I did it might be limited by a variety of factors.
All that being said, for my own purposes in evaluating this game I'm going to assume that Cliff Lee is going to be his normal self and Charlie is going to evaluate whether or not to keep him in the game as if he didn't just come off the DL. Those may be bad assumptions, especially with the model showing Cliff averaging 7+ limit on a supposed pitch limit, so if you think they are faulty feel free to ignore my following opinion on the game (go the other way on the game if you want for exactly those reasons). And my opinion is the Phillies are a good play tonight at -195, with an estimated ROI of between 5-6%. Some of the early betting at a few sports books I looked at indicates that there some crowd agreement that the Mets are a good play, though yesterday's line moved big toward the Phillies and we know how that turned out (you're going to have to trust me that the model thought Mets at +175 last night was an amazing play).
The model sees the O/U of 7.0 as pretty high, with 58% of simulations going under 7.0 (30% going over). Normally I would say that makes the under a really good play, but I'm going to say pass on it and instead take whatever you might have wagedered on the total and put it on PHI -195.
Go Phils!
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