Comments on: Pitcher Win Values Explained: Part Five

By: ????o??p??pa?

????o??p??pa? — Fri, 10 Apr 2009 05:47:55 +0000

? ??????? ? ???? ?? ????? ??????????, ?? ????? ????? ?????? ???? ??????? ?????? ????????. ??????? :)

By: Samg

Samg — Sun, 18 Jan 2009 19:42:00 +0000

The thing is, it almost always evens out for hitters.

By: shoewizard

shoewizard — Fri, 16 Jan 2009 16:25:35 +0000

Colin,

can you take a look at my question two posts above Nick’s.

It seems to me that if pitchers are going to receive credit (or blame) for creating their own positive or negative run environment, there needs to be some strength of competition adjustment added to the hitters win value formula.

If Stephen Drew smacks a 2 run double off of Jake Peavy, it’s more “valuable” than hitting a 2 run double off of Livan Hernandez, because of the different run environments each pitcher creates.

Conceptually, I realize this is all in the realm of WPA, however since the personal run environment factor is being introduced into the win values calculation for pitchers, it seems a counterbalance is needed for the hitters. Rather than that be a personal run environment for hitters, as Nick suggested, it seems some sort of strength of competition would be more appropriate.

I don’t know how this works, (or doesn’t) mathematically. I’m just conceptualizing. Thanks for taking the time to respond, and I’m sorry if my question is born out of some fundamental lack of understanding whats going on here. I’m trying my best to keep up. !

Thanks to everyone involved in the projects going on, and the efforts to increase baseball understanding.

By: tangotiger

tangotiger — Fri, 16 Jan 2009 03:19:45 +0000

KJOK: I enjoyed rechecking that anyway, and Patriot is going to do a bit more on this, so I think we’ll all be better off for this.

By: Colin Wyers

Colin Wyers — Fri, 16 Jan 2009 02:57:57 +0000

It is, but not a lot – there’s eight other players in the lineup that determine a lot of the run environment. You can measure that value using theoretical team BaseRuns, but the difference isn’t that bad.

By: KJOK

KJOK — Fri, 16 Jan 2009 02:04:52 +0000

I should have known Tango was right all along. I was using Pete Palmer’s numbers as my ‘standard’ as I thought they were ‘empirical’ Runs to Wins factors (from Total Baseball), but Palmer was apparently using the equation RPW = 10*sqrt(RPG/9), which I guess just happens to come a little closer to my equation than to Tango’s at lower run levels.

I stand corrected.

By: Samg

Samg — Fri, 16 Jan 2009 02:03:29 +0000

I dare you guys to make the site more awesome and make me more obsessed. (Good luck with that)

By: TangoTiger

TangoTiger — Thu, 15 Jan 2009 21:29:13 +0000

Good job. So, that pretty much settles it then, that the “+3″ is indeed the best-fit for Patriot’s time period, and close enough for my time period.

By: Patriot

Patriot — Thu, 15 Jan 2009 20:31:32 +0000

For 1961-2003 (excluding ’81 and ’84), the RMSE for W% times 162 are:

Pythagenpat (x = .29) 3.950
Pythagenpat RPW (2*RPG^.71) 3.952
“+2.75″ 3.951
“+3″ 3.949

The “+2.75″ version is the tangent line to the Pythagenpat RPW function at the point RPG = 9 (i.e. near the long-term average RPG). The actual average for that time frame is 8.74 RPG, and at that point the tangent line is .757*RPG + 2.70, which has a RMSE of 3.951.

By: TangoTiger

TangoTiger — Thu, 15 Jan 2009 20:30:51 +0000

Ah, what the heck. Taking the 1908 teams since 1919, and using games played rather than innings played, here we go.

If I force the .75 to stick, then I get an average error of .0202 wins, if the second parameter in the Patriot equation is anywhere from 2.66 to 3.09. That is, the error goes up to .02025 at those two extreme points. The absolute minimum point is at 2.86, where you get an error of .020198.

If I force it to stick to .80, then I get an average error of .02021 if the other parameter is 2.41.

If I force it to stick to .70, then I get an average error of .020194, with the other parameter as 3.31.

As you can see, at the team-level, where so many teams are stuck at the .500 level, and all at similar run environments, it doesn’t matter what you use, since you will get an average error of .0202 wins.

The binning as I do in the earlier link highlights the extreme run environments, and so makes the equation more sensitive. I have no problem if David wants to use anything he wants along these lines. But, I cannot see how a non-linear equation improves anything, other than possibly a smidge.