# Pitching Run Values for the 2010 Season

**Posted:**September 21, 2010

**Filed under:**Research, Runs Above Average 9 Comments

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.

Rank | Name | Team | CL | K% | BB% | BABIP | TBF | RAA |
---|---|---|---|---|---|---|---|---|

1 | Wimmers, Alex | OSU | JR | 0.293 | 0.085 | 0.322 | 294 | 33 |

2 | Rosin, Seth | MINN | JR | 0.223 | 0.054 | 0.298 | 426 | 29 |

3 | Bischoff, Matt | PUR | SR | 0.240 | 0.043 | 0.326 | 396 | 26 |

4 | Leininger, Drew | IND | SO | 0.161 | 0.074 | 0.304 | 417 | 24 |

5 | Lutz, David | PSU | SR* | 0.166 | 0.080 | 0.316 | 301 | 23 |

6 | Hippen, Jarred | IOWA | SO | 0.161 | 0.070 | 0.337 | 440 | 20 |

7 | Snieder, Paul | NW | SO | 0.220 | 0.101 | 0.221 | 159 | 20 |

8 | Oaks, Alan | MICH | SR | 0.179 | 0.123 | 0.274 | 397 | 19 |

9 | Oakes, TJ | MINN | FR | 0.152 | 0.077 | 0.313 | 375 | 18 |

10 | Isaksson, Phil | MINN | JR | 0.161 | 0.102 | 0.278 | 354 | 18 |

11 | Brooke, Francis | NW | SO | 0.126 | 0.026 | 0.308 | 382 | 17 |

12 | Burgoon, Tyler | MICH | JR | 0.285 | 0.103 | 0.373 | 253 | 15 |

13 | Achter, AJ | MSU | JR | 0.171 | 0.111 | 0.340 | 432 | 14 |

14 | Bucciferro, Tony | MSU | SO | 0.135 | 0.063 | 0.322 | 384 | 14 |

15 | Robertson, Zach | IOWA | SR | 0.242 | 0.115 | 0.336 | 252 | 12 |

16 | Gailey, Matt | NW | JR | 0.167 | 0.078 | 0.227 | 90 | 11 |

17 | Soule, Billy | MINN | FR | 0.161 | 0.115 | 0.307 | 218 | 11 |

18 | Roberts, Bryan | ILL | SO | 0.246 | 0.102 | 0.289 | 118 | 11 |

19 | Matyas, Scott | MINN | JR | 0.385 | 0.128 | 0.371 | 156 | 11 |

20 | Jokisch, Eric | NW | JR | 0.151 | 0.105 | 0.348 | 410 | 10 |

21 | Cahill, Kevin | PUR | SR | 0.222 | 0.175 | 0.240 | 126 | 10 |

22 | Brosnahan, Bobby | MICH | FR* | 0.191 | 0.135 | 0.362 | 319 | 10 |

23 | Morgan, Matt | PUR | JR | 0.228 | 0.091 | 0.368 | 320 | 10 |

24 | Simpson, Tim | MSU | JR | 0.226 | 0.097 | 0.233 | 93 | 10 |

25 | Haase, Joe | PUR | SO | 0.157 | 0.114 | 0.273 | 140 | 10 |

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.

I did not know Snieder was this good. Ohio State player NW weekend 1 so I really did not keep too much track of them.

Question, should, and if so how, or is it already in some form included, a pitcher’s slugging against be incorporated?

While Wimmers would seem to have a high BABIP, the number of XBHs is nowhere near the number Brooke allowed. I guess the question is how low does a low BABIP need to be to provide results that might cause a head scratch?

Does that make sense? I’m far from being a knowledgable Sabrhead.

I guess there isn’t a set number for when you start to question the BABIP of the pitcher. The league average BABIP in 2010 for pitchers was .345 so Wimmers and Brooke were better-than-average but Brooke had a lower one than Wimmers: .308 to .322. Now, pitchers can control BABIP to some extent and, let’s be honest, Wimmers is easily a better pitcher than Brooke — so I’d be more concerned about Brooke’s BABIP regressing to .345 than Wimmers.

I’d say once you get to around 30 or so points off from the league mean, it’d be somewhat worrisome. Someone like Leininger or Brooke or Snieder.

As for the first part, the base runs method uses all types of hits — singles, doubles, triples, homers — as well as K’s and BB’s (and I include HBP’s into the BB’s).

Basically, I’m going to be adjusting each pitcher’s singles, doubles, triples, and homers toward the league average rate. So it may hurt Wimmers and help other, potentially worse, pitchers. It will also probably undervalue guys who are major ground ball pitchers and overvalue guys who give up lots of fly balls (fly balls turn into HR’s more than GB’s [obviously], so someone with a high HR rate will be helped by regressing to league mean).

Basically, it’s a lot of massaging to try to find some hints of the true talents on the season. Working with the sample sizes that are in the limited college season (especially if the player gets hurt, like Wimmers did), leave some things to be desired.

[…] 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, […]

intersting analysis. Trying to figure out exactly what this all says. question with this how does batters faced factor into the ” runs” saved? IE if a guyfaces 200 batters and saves 10 runs, another faces 200 baters and saves 10 runs are you saying the same thing?

Yes. The batters faced is essentially playing time. So if two guys have similar RAA numbers over similar TBF, they were basically the same in terms of value. It’s why someone like Kevin Cahill had a better season than Eric Jokisch; Cahill posted similar RAA numbers over about 25% the amount of TBF of Jokisch.

Does that make sense?

OK. thanks, so if I have you right, Jokish faced 410 batters, RAA 10, Cahill faced 126 batters RAA 10. You say Cahill had a better season. If I have your theory correct, that seems right, same RAA for almost 1/4 batters so almost 4 times effective??? yet Cahil ranked lower???

Yeah. I’ve rounded to the nearest whole number because I think decimal places give a false pretense of precision that just isn’t there (these weights probably aren’t 100% correct for the college baseball run environment, but they’re pretty good). So the actual totals are Jokisch at 10.42 and Cahill at 10.09 — basically less than half a run separating the two. While Jokisch is barely better, I’d say that Cahill had the better season given the smaller amount of batters he faced.

[…] I have my Unadjusted Runs Above Average […]

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