Comments on: Pitcher Win Values Explained: Part One

By: Sky

Sky — Tue, 13 Jan 2009 20:04:12 +0000

It’s a good point, and I agree, that FIP/tRA/xFIP/etc are strongly correlated. And are better measures than ERA.

Graham has done some preliminary work with tRA/ERA/FIP correlations and they’re promising for tRA. He hasn’t published it or finished it, yet, though.

Any possibility of PZR for the site, David? You already have the UZR methodology implemented…

By: A.M.

A.M. — Tue, 13 Jan 2009 17:58:50 +0000

Great work on this.

Two quick questions:
1)Any chance you will be adding a 2009 projection for value? Using either Marcel or BJames, or combination of both?

2)Is there a “leaderboard” function that we can sort through values by position, by team, etc?

Combining 1 and 2, it would be interesting to see projections for teams, both in terms of wins and $ value.

By: David Appelman

David Appelman — Tue, 13 Jan 2009 17:17:08 +0000

It’s my understanding that tRA regresses LD%, so players aren’t getting fully docked for their LD% in tRA and they’re not getting docked for HRs at all.

Anwyay, upon further research, the 2008 tRA to FIP r^2 for “qualified players” is about .82, so in practice they’re still pretty close.

Maybe middle ground isn’t quite right. There are differences on both ends, but tRA for qualified players doing a straight average is about .4-.5 points higher than FIP, which does match up with ERA.

Out of curiosity, has anyone done a study on tRA that shows it to be more useful than FIP/DIPS/whatever else is out there? I’d be curious to see one.

By: Sky

Sky — Tue, 13 Jan 2009 15:30:00 +0000

David, isn’t tRA a middle-ground between ERA and FIP? FIP assumes all balls in play are the same. tERA gives different credit/blame for liners and fly balls for example. Now, there may not be much of a year-to-hear correlation for LD%, but if a pitcher gave them up, one could argue that’s part of his value. Taken a step further, you’d use PZR, which is the pitcher’s half of UZR. With the UZR methodology, you know the expected run value of each batted ball. Assign that to each pitcher. (Fielders get the difference of the expected run value of the batted ball given up by the pitcher and the actual outcome of the batted ball.)

By: David Appelman

David Appelman — Tue, 13 Jan 2009 08:33:55 +0000

I see FIP as sort of a middle ground between ERA and tRA. I think that works out nicely for a stat like this. Basically we’ll give a pitcher the benefit of the doubt on the LOB% and BABIP, but a home run problem (which is typically the main culprit for ERA), we’re not willing to ignore.

Last time I checked FIP and tRA were at least similar with about a .75 r^2, or something like that.

By: dan

dan — Tue, 13 Jan 2009 06:16:21 +0000

Also, why use FIP when looking at past value? Zito was a bad value because of the runs allowed, not the FIP runs allowed.

By: David

David — Tue, 13 Jan 2009 05:44:10 +0000

Why didn’t you guys use a more advanced stat like tRA? Sorry, but FIP is not by any stretch of the imagination the best pitching metric out there. So why did you stick with FIP?

By: Gen. Bonkers

Gen. Bonkers — Tue, 13 Jan 2009 04:06:32 +0000

Am I reading it right that Javier Vazquez was worth more $ in 2008 than in 2007???

By: Graham

Graham — Tue, 13 Jan 2009 02:52:19 +0000

Tim Lincecum is very good at baseball.

By: Evan

Evan — Tue, 13 Jan 2009 00:35:34 +0000

We’ve seen that, but does it make any sense? A win is a win is a win, right?

Though, I suppose that would impact the market for pitching vs. the market for hitting, so perhaps pitchers simply can’t be had for the same $/win rate.

Then again, the actual salaries paid to players suggest that no player can be had for the actual $/win rate – it’s just that some are grossly underpaid (like Halladay) and some are grossly overpaid (like Jose Guillen).

We’d need to measure it to be sure.