Big Ten Conference Recap: Purdue Pitching

The team pitching recaps from the 2010 season are all linked to under the 2010 Season Recap tab. This is the tenth installment, focusing on the Purdue Boilermakers.

The Purdue Boilermakers finished the 2010 season at .500 in conference play with a 12-12 record, but had a very good 33-24 overall record. The strength of the ‘Makers was the pitching staff. I have them finishing fourth in the conference in estimated runs scored. However, their pitching staff led the conference by nine estimated runs allowed. Total that all up and I actually had Purdue as being the best team in the Big Ten in 2010.

Below are the raw numbers for the Purdue pitching staff last season.

Name CL K% BB% K-BB% BABIP Pitches TBF
Bischoff, Matt SR 0.240 0.043 0.197 0.326 1352 396
Cahill, Kevin SR 0.222 0.175 0.048 0.240 466 126
Calder, Tyler SO 0.071 0.143 -0.071 0.300 49 14
Collins, Sean SO 0.091 0.091 0.000 0.328 288 88
Gannon, Pat FR 0.139 0.099 0.040 0.324 342 101
Gunter, Calvin SO 0.186 0.110 0.076 0.386 602 172
Haase, Joe SO 0.157 0.114 0.043 0.273 471 140
Jansen, Matt SR 0.188 0.162 0.026 0.348 809 229
Mascarello, Blake SO 0.211 0.105 0.105 0.289 404 114
Morgan, Matt JR 0.228 0.091 0.138 0.368 1119 320
Ramer, Robert FR* 0.089 0.078 0.011 0.219 289 90
Schreiber, Mike FR 0.180 0.081 0.099 0.359 382 111
Sestak, Connor SR 0.067 0.133 -0.067 0.429 149 45
Sudbury, Mike SO 0.267 0.267 0.000 0.000 60 15
Wurdack, Drew SR 0.192 0.099 0.093 0.372 1076 313

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Exploring Team Defense

One of the big banes of Sabermetrics is attempting to quantify team defense. There are nifty tools out there like Ultimate Zone Rating, Defensive Runs Saved, Total Zone (all three of which can be found at Fangraphs) that are the most “advanced” defensive metrics available for Major League Baseball.

However, Colin Wyers of Baseball Prospectus fame has questioned defense with a lot of logical fore-thought. The long and short of it is that the processes of the advanced metrics like UZR or John Dewan’s DRS systems aren’t necessarily the problem; it’s the data being put into it. There’s numerous biases that can enter the mix and that compounds things. Crap in, crap out, so-to-speak. If your data isn’t good, it’s almost going to ensure that there’s nothing of value that will come out of the formula.

One thing we do have, though, are outs and balls in play. I asked Colin, and he confirmed, that using Defensive Efficiency Ratio is the best metric for team-level fielding.

Now, since I don’t have any database skills at all, I can’t do a plays made/not made (which is essentially Sean Smith’s Total Zone metric that you find on Baseball Reference)  on an individual level like Jeff Sackmann does, but I can use B-Pro’s Def Eff formula and apply it to the Big Ten teams from 2007-2010.

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