Using pythag W/L%, if we spread all the runs saved over all 162 games, we can get a very different value than spreading them out just over the 35 starts. As an example, say FIP leads us (I think this is what Fangraphs uses for WAR, right?) to believe that Halladay has saved the Phillies 56 runs over a replacement pitcher in 27 starts, and the Phillies have played a total of 130 games.

We could say that an average NL team scores about 578 runs in 130 games (9-inning games for simplicity’s sake) and then check the difference in Pyth W/L when those runs are taken away from the Runs against part of the formula. My math gives me a WAR of 6.6.

Now instead, say we only focus on those 27 starts. Halladay averages 7 2/3 innings per start. So I set his team’s Runs Scored to the average, or about 4.45 R/9, and then set his team’s Runs Against to the weighted average of his FIP and an average bullpen’s FIP. Halladay pitches 85% of every 9 innings when he starts, so I would weight the RA accordingly. Now we’ll get a difference in pyth W/L based only on those 27 games. I can’t finish the example very well because I’m not sure where all the replacement levels are, but I hope my point is understood. I have found in a few examples using my own R/9 formulas that the difference between the two methodologies can be as much as a full win or two.

Does this defeat the simplicity and “presentability” of WAR? Have I botched the methodology? I just think 10 runs = 1 win is a little too simple to use for both hitters and pitchers (especially relievers).

Thanks again for all the work you do :-)

Adam Dunn’s bUZR, 2005 to 2008: -16, -12, -15, -23
Adam Dunn’s sUZR, 2005 to 2007: -7, -19, -29
Adam Dunn’s +/-, 2006 to 2008: -18, -28, -23

You keep acting like we have one data point that says Dunn’s bad and one data point that says Dunn is okay. We don’t – we have about 4,000 data points that say Dunn is a horrible fielder and one that says he isn’t. PMR is the outlier. There’s no reason to give it 50% weight here. It’s wrong.

Using PMR’s estimate, Dunn was worth about $18M in ’08. Using fangraph’s UZR estimate, he was worth about $8M.

Like I said, this isn’t meant to be argumentative and maybe even picking out Dunn happens to be a case of highlighting a fairly rare case, but that’s a large enough gap for even Bavasi’s moving van to drive through.

In the end, it’s really about estimating what his value will be next season…

I think Tango is exactly right, we’re missing a “brackets”.

I wouldn’t call a 10-run difference “dramatically different”. What to say of STATS-based UZR and BIS-based UZR having a 112 run difference for Andruw Jones over six years? Super-duper dramatic?

I could buy into averaging BIS-based UZR and BIS-based PMR, because they have different methodologies (even though they have very similar inputs). UZR and PMR and everyone else agrees on the number of outs Adam Dunn made. The question is understanding the context under which he made those outs (who the batter, pitcher, park, runners, and outs were, and exactly where and how hard did the ball go?), and how many outs would an average player have made under that same context.

If for example Adam Dunn made 235 outs in LF/RF, and MGL/UZR says that an average OF would have made 260, and Pinto/PMR says 255 (or whatever he is saying), and Dewan/PM says 250, is that so different?

This is really the chief issue here. There’s an uncertainty level, and that’s what’s really missing.

If you want to average in a system that uses STATS data, or some other data source, then I’d buy into that, though unfortunately that won’t be happening anytime soon.

I would suggest that, in your Glossary, you guys make a list of these blog entries, along with a list of blog entries that cover the details in more depth. I really think we need a central place that includes all the links to all the details, in a reader-friendly layout, in order to gain acceptance for your new stats.

Anyway, UZR hated Dunn in ’08 (using either data set) but really UZR was much more down on Dunn’s glove last season than other systems. For instance, Dewan’s +/- agreed that Dunn was a bad defender but suggested he was roughly -10 runs bad (or maybe a little worse). JinAz’s system using a different approach pretty much agreed that Dunn was bad to the tune of roughly -10 runs. However, PMR basically thought Dunn was roughly a neutral defender in -08. The CHONE projection for Dunn in ’09 is that of a -13 run defender (I’m going on memory here). It seems reasonable looking at such a survey to suggest Dunn’s true defensive value in ’08 was something closer to -15 runs at the worst and maybe as high as -10 runs (still no great shakes but dramatically different than -22).

Assuming that argument is at least plausable, then the fangraph’s win value for Dunn’s ’08 could be off by something close to a win just from the way it handled Dunn’s defense (even applying a +/- 5 run margin of error to his UZR at best might still significantly low ball him and at worst lead to dramatically undervaluing him). Basically the disparity would be the difference between concluding the Reds paid Dunn roughly exactly what they should’ve to concluding they dramatically overpaid him.

To me that’s a little more than griping that a triple wasn’t a homer.

Once again, a million kudos to win values now being so easily and readily accessible-I think it’s the gold standard approach (and BTW, thank you Tango for being so unbeleivable generous with your work).Win values are now in the mainstream baseball fan converasation and that in and of itself is a huge step forward. It’s just that I think we should double check the defensive part of the equation when relying only on a single metric before quoting the figure verbatim. That’s all I’m saying.

There is uncertainty in ALL sample measures, without exception. The only thing that you can complain about is that Fangraphs doesn’t publish the uncertainty level.

But, given the choice between what Fangraphs is showing, and what anyone anywhere is publicly showing, it’s no contest.

You’ve got yourself a triple, and you are complaining that it’s not a Homerun, when the alternative is a single, or worse, talk-radio strikeouts.