(this was posted on the Chicago Sports Review site a few years ago but as far as I can tell, alot of my articles there have been taken down. Someone at Joe Posnanski's site mentioned that Reuschel was very under rated. So I have been wanting to post some of my old CSR articles, so this seems like a good time) First, some highlights:
-His strike-out-to-walk ratio was 31% better than the league average
-He gave up 21.6% fewer HRs than average
Yes, I’m crazy. But not because I think Reuschel deserves to be in the Hall of Fame. What makes me crazy is that I was doing a lot ridiculously time-consuming analysis that opened my eyes. As of now, I don’t know how he has done in the voting or if he is still eligible for induction based on the writer’s vote or if he has to wait for the Veterans Committee.
Before I get into explaining the actual analysis, lets review a few things. A pitcher needs to prevent the other team from scoring and, in this endeavor, he can be aided or hindered by his fielders. So one thing to look at are his defense-independent pitching stats. Many of you probably know that I am taking a page out of Voros McCracken’s book on this. Readers who have not heard of him, Google his name. He came up with the idea a few years ago that on balls in play (not HRs, walks or strikeouts), the batting average that most pitchers allow is not too much different from other pitchers and that it appears to be mainly influenced by the fielders and hitters. Analysts Tom Tippett and Mike Emeigh, to name just two, have challenged McCracken’s thesis. But it is still pretty good.
So we should look at the things a pitcher controls, like HRs, walks and strikeouts (and even if the pitcher has some influence on the batting average on balls in play, the fielders and hitters still play a role, so we are still isolating just what the pitcher does and so it is a legitimate analysis). But how a pitcher does in HRs, walks or strikeouts must be put into context. They should be adjusted for the league average and for park effects.
So using the linear regression technique, I came up with a formula for estimating a pitcher’s ERA. I looked at all pitching seasons from 1920-2000 with 150+ IP. Here is the formula that I got
ERA = .44*HR + .4*BB - .3*K
The intercept or constant term was less than .0001. The r-squared was .422 and the standard error was .75. But for each pitcher I used not his ERA, but how much he differed from the league average in the given year (actually how many standard deviations from the mean he was). Same thing for the HRs, walks and strikeouts. Using standard deviations, since they measure dispersion, does a better job of placing a pitcher in the context of his season than what percent above or below the mean they are in some stat (or the absolute difference) since we see where a pitcher fits in the statistical distribution of the given year.
Once I had this equation, I plugged in each pitcher's data on HRs, BBs and Ks and ranked them all (2000+ IP minimum during the 1920-2000 period) in terms of how many standard deviations below the mean they were in their careers (using only seasons when they pitched 150+ IP-data came from the Sean Lahman data base). Each pitcher’s HRs were adjusted for park effects before their HRs were plugged into the formula. I used park effect data from fellow economist and SABR member Ron Selter. So if a pitcher was 1 standard deviation below the mean, he got a -.44. If he were, say, half a standard deviation better on walks and strikeouts, he gets a -.2 and a -.15. So he would come out -.79. How I used the park data is explained below in technical notes (I don’t have any data on how parks affect strikeouts and walks so those were not adjusted).
Rick Reuschel was 14th! Yes. That seems to be a high enough ranking in an 80-year period to merit the Hall of Fame. Here are the top 20 in terms of how many standard deviations below the average ERA they were for their careers:
Dazzy Vance –1.25
Lefty Grove –1.21
Roger Clemens –1.18
Greg Maddux –1.14
Carl Hubbell -.94
Randy Johnson -.92
Kevin Brown -.91
Dwight Gooden -.89
Mike Garcia -.84
Hal Newhouser -.82
Sandy Koufax -.81
Bert Blyleven -.75
Ron Guidry -.73
Rick Reuschel -.71
G. Alexander -.70
Gaylord Perry -.68
Urban Schocker -.65
John Smoltz -.65
Lefty Gomez -.65
Bob Gibson -.62
(I also looked at ERA relative to the league average in addition to this standard deviation technique and he would be 20th, still a very high ranking). Reuschel is in obviously very good company. This means that, when only looking at pitcher controlled factors, he was outstanding at preventing runs in the context of his era and parks. This was done while pitching 3500 innings (38th since 1920) and winning over 200 games.
Some conventional stats back up my claim. From 1972 –1984, the years Reuschel was on the Cubs, he was 23rd among all major league pitchers with 1000+ IP in HRs allowed relative to the league average (thanks to the Lee Sinins Sabermetric Encyclopedia). He allowed 25% HRs fewer than the average pitcher would have, pitching in Wrigley Field! Wrigley was a great HR park during this period, compared to other NL parks, allowing 42% more HRs than average. Yet Reuschel was one of the best in baseball at preventing HRs during this period!
For his entire career, Reuschel gave up 21.6% fewer HRs than average. This is 41st for all pitchers from 1920-2004 with 2000+ IP. Pitchers he is ahead of include
He is 50th in strike-out-to-walk ratio relative to the league average in all of baseball history for pitchers with 3000+IP. His strike-out-to-walk ratio was 2.16, 31% better than the league average of 1.65. Pitchers he is ahead of include
Jim Palmer, for example, had the luxury of great fielders behind him, like Brooks Robinson, Mark Belanger, Dave Johnson, Bobby Grich and Paul Blair. Did the Cubs have anyone that good from 1972-1984?
So, we can see that Reuschel was very, very good in things that the pitcher mostly controls: HRs, BBs and Ks. His high rankings in these stats warrant his induction into the Hall of Fame, especially when we see some of the pitchers he is ahead of.
Technical note: In using the park effects to adjust for HRs, I take the factor, say 120, and find the number that is half-way between it and 100 since a pitcher only pitches half his innings in his own park. Then I would use 110. If a pitcher allowed 1 HR per 9 IP, I divide 1 by 1.10 and get .91. Then I see how far from the league average that is. That difference gets divided by the standard deviation. Then that gets plugged into the formula.