Pitching Run Values for the 2010 SeasonPosted: September 21, 2010
Taking a break from my team-by-team review of what I consider to be the essential pitching stats — strikeout percentage, walk percentage, strikeout minus walk percentage, total batters faced — I’m going to bring out a run estimator. While looking at multiple statistics are the better way to go, it’s nice to have a handy singular number to give you an idea of a pitcher’s value to their team.
What I’ve done is pretty simple. I’ve used a Base Runs method to get an ERA estimate. Then, I found the league average for each year I have statistics (2008-2010, though I have team stats for the 2007 season, but have slacked on getting individual numbers for that year). From there, it’s a simple matter of subtracting the pitchers Base Runs ERA from the league average rate and multiple by innings pitched and divide by nine. Voila. Pretty simple. Then again, I did steal this from Patriot over at Walk Like a Sabermetrician. Below is the top 25 in runs saved in 2010.
K% – strikeouts divided by total batters faced
BB% – walks plus hit batters divided by total batters faced
BABIP – batting average on balls in play
TBF – Total Batters Faced
RAA – Runs Above Average via a Base Runs method
Well this certainly passes the smell test for me. The National Pitcher of the Year, Alex Wimmers, leading the pack and by a decent margin. Behind him, a couple of dominating starters in Golden Gopher Seth Rosin and Purdue’s Matt Bischoff.
Northwestern’s Paul Snieder and Minnesota’s Scott Matyas shows how valuable relievers can be in college. Both ranking in the top 25 in runs above average.
You can make a good case that Iowa’s Jarred Hippen or Indiana’s Drew Leininger as the best returning pitchers. If you want to include ‘upside’ due to youth, I’ll take TJ Oakes from Minnesota. As a freshman, he posted 18 runs above average — a solid seven runs better than any other freshman hurler in 2010 (fellow teammate Billy Soule was second at 11 RAA).
Now, I will say that these are very, very susceptible to a low average on balls in play. For instance, the aforementioned Paul Snieder only had a .221 BABIP. The league average is .345 — that’s .124 point difference! Because of this, more outs occurred with Snider on the mound than one would expect and, thus, he allowed less hits/baserunners which led to less runs. Because the Base Runs method is built on hits and walks and whatnot, low BABIP’s can give readings that are a bit “odd” for the lack of a better term. Because of this, I will virtually always post a pitcher’s BABIP next to their Base Runs.
I am working on a RAA statistic that will hopefully help rectify the low-BABIP problem, but I will have more on that later.