Adjusted Pitching Run Values for the 2010 SeasonPosted: September 22, 2010
I got some free time sooner than I thought, and really wanted to hammer out some Runs Above Average numbers for the 2010 season for individual pitcher. You can read a bit about it from my post on Monday. What I’ve done is used the same methodology, however, instead of the raw singles, doubles, triples, homers, sacrifice flies/hits numbers, I substituted league average rates. This gives a Defensive Independent Pitching Statistic-like (DiPS) element to the run valuations.
Basically, it is my attempt to neutralize things like batting average on balls in play and/or defensive impacts.
Below, you will find the top 25 pitchers sorted by my Adjusted BaseRuns Runs Above Average statistic.
|Name||Team||CL||Adj BR RAA||BR RAA||Delta|
Adj BR RAA – Adjusted BaseRuns Runs Above Average
BR RAA – Unadjusted BaseRuns Runs Above Average
Delta – Difference between the Adjusted and Unadjusted BR RAA statistics
Note: Any numbers in the Delta column that don’t add up (i.e.: Paul Snieder’s ‘delta’ being -11 when 8-20=-12) are due to rounding. I’ve rounded to the nearest whole number for aesthetic purposes.
What we see here is that once you essentially normalize for BABIP, you have less elite players. While the unadjusted BR RAA had 26 pitchers top the 10 runs and 7 above the 20 runs above average mark, the adjusted BR RAA only has 11 and just 3 above 20 runs.
This knocks Alex Wimmers down quite a bit — difference of 12 runs — but there’s a decent chunk of that due to homers. He surrendered zero long balls last year, and if you substitute league-average rates for his pitching line, he would be expected to give up 4-5. Wimmers was a great, great pitcher in the Big Ten, however, he’s not likely a “zero HR’s allowed” great (who is?), so it makes sense.
Indiana’s Drew Leininger and Michigan’s David Lutz drop down because of closer-to-average strikeout rates (which were left untouched in my adjustments). Minnesota’s Seth Rosin doesn’t drop far at all because of strong peripherals — great strikeout rates, even better walk rates, and a lot of innings pitched/batters faced — outweighing the adjustment to his low BABIP. The opposite end of the spectrum to Rosin is Paul Snieder. He dropped off from 20 runs above average to just 8. This is due to his .221 BABIP was so low, adjusting it towards the league average increases a lot of hits allowed. His great strikeout rates just couldn’t over come it.
The biggest beneficiary of this statistic is Northwestern’s Joe Muraski. Muraski was at -15 Runs Above Average using the unadjusted method, but once adjusted for league average rates, he clocks in at +4 — a 19 run swing.
Unfortunately, David Lutz, Alex Wimmers, Drew Leininger, and Alan Oakes all were affected the most; each losing 12 runs from their unadjusted RAA totals.
The best way I can describe the difference between these to metrics are this: The Unadjusted BR RAA numbers are descriptive. Paul Snieder’s .221 BABIP actually happened. Alex Wimmers actually didn’t allow a home run.
The Adjusted BR RAA numbers are more informative (I choose this because I hesitate to use “predictive”). They get more towards, in my opinion, a ‘truer’ talent level. I don’t think one is necessarily better than the other and both have very good value to look at. It just depends on what question you’re answering. If you want to know how Player A pitched, Unadjusted BR RAA is probably your better metric to look at. If you want to know if it’s sustainable, I’d venture to guess the Adjusted BR RAA is the better metric to look at.
Either way, both of these have, most likely, large error bars built in. This is good for a quick-look, singular number, but you’re better off looking at strikeout rates, walk/HBP rates, etc etc compared to the league average.