Statistical Updates

I’ve neglected this blog over over a full calendar year. With the NCAA Super Regional’s currently on television, now is as good a time as any to do my first Big  Ten Conference data dump/season recaps in over a year.

I’ve tweaked my data (again) to what I feel comfortable with. If you’d like to get a bit nerdy, continue reading down after this paragraph. If you don’t, just know that I’m using the following measures for offense, defense and pitching.

Offense – I’m using Weighted On-Base Average, or wOBA. It uses linear weights to give each type of outcome from a plate appearance a run value. You multiply these values by the number of times each outcome occurred and divide by plate appearances. This will give you a team’s (or player’s) wOBA. The nice thing about wOBA is the ability to easily convert it into a runs above average metric dubbed Weighted Runs Above Average or wRAA. Additionally, you can take it a step further and calculate Weighted Runs Created which is adjusted for league average — or wRC+. This number is the same scale as OPS+ where 100 is league average and each point above/below 100 is equivalent to one percentage point. Why do this? Because wRAA is a counting stat, wRC+ is not. This allows us to compare how well a player performed offensively in his 100 plate appearances to a player who had 180. While the wRAA may favor the latter player, wRC+ will help us decide who actually was better. It takes playing time essentially out of the equation.

Defense – I haven’t changed my calculations on defense at all since my last postings on this space. I am using Defensive Efficiency Ratio because it’s the best team-defense metric at the Major League level. Given how little data we have for the Big Ten compared to the MLB, Defensive Efficiency Ratio is almost undoubtedly the best defensive metric available for the Big Ten. I calculate it just as Baseball Prospectus does and put it on the “plus” scale, where 100 is league average. This allows us to compare across various seasons.

Pitching – I changed my metric over to Fielding Independent Pitching, or FIP.  From here, we can calculate a runs above average number for the individual pitcher or team in question quite easily. It attempts to remove defense and focus on things a pitcher can control. However, I haven’t studied whether FIP is a reliable number in college baseball. I’m pretty certain that the theories behind defensive-independent run estimators like FIP hold true at the college level, it’s just not entirely certain. From here, I’ve calculated an Expected FIP (xFIP) of sorts. Instead of normalizing home-run-to-fly-ball-ratio like Fangraphs does, I’ve substituted a league-average home-run-per-contacted-ball percentage for each pitcher. I don’t know how much I’ll present an xFIP data because the lower you move in the baseball ranks, the more a pitcher’s abilities to prevent home runs and induce weak contact increases. It’s a little cross-checker of mine to help me contextualize the data a bit more.

The nerdy part: I’ve calculated custom linear weights by using Tom Tango’s Markov Calculator. For FIP, I calculated custom FIP weightings based on this blog post by Tango called Deconstructing FIP.

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2011 Relief Pitcher Leaderboards

Updated for games through Monday, April 5th. Minimum 75 batters faced

Rk Name Team RL K% BB% BABIP pERA paRAA
1 Martin, Chad IND SW 0.137 0.087 0.248 4.28 7.7
2 Walkling, Dave PSU RP 0.341 0.098 0.283 3.31 6.5
3 Ignas, Ryan PSU RP 0.117 0.096 0.236 3.63 6.3
4 Dearden, Matt IND RP 0.157 0.135 0.258 3.84 5.1
5 Wieber, Tony MSU RP 0.204 0.108 0.238 4.70 3.4
6 Korte, Brian IND SW 0.110 0.061 0.303 4.62 3.3
7 McKinney, Brett OSU RP 0.147 0.093 0.278 4.61 2.8
8 Jahns, Michael NW RP 0.146 0.146 0.299 5.37 1.8
9 Strack, Will ILL RP 0.198 0.139 0.292 5.48 1.6
10 Halstead, Ryan IND RP 0.156 0.091 0.286 5.46 1.3
11 Lala, Patrick IOWA RP 0.167 0.222 0.208 5.58 1.1
12 Wittgren, Nick PUR RP 0.222 0.046 0.333 5.75 1.0
13 Fangman, Tim IOWA RP 0.101 0.101 0.309 5.89 0.5
14 Carr, Matt IND RP 0.197 0.148 0.247 6.13 -0.1
15 Clark, Kyle MICH SW 0.129 0.099 0.302 6.22 -0.4
16 Quigley, Jack NW RP 0.175 0.125 0.346 6.34 -0.5
17 Haase, Joe PUR SW 0.158 0.082 0.336 6.43 -1.3
18 Ramer, Robert PUR RP 0.209 0.116 0.315 7.04 -2.0
19 Breedlove, Lance PUR RP 0.095 0.052 0.364 7.32 -3.3
20 Leininger, Drew IND SW 0.112 0.099 0.316 7.41 -4.8
21 Lakatos, Alex MICH RP 0.171 0.210 0.326 8.81 -4.8
22 Ballentine, Ben MICH RP 0.161 0.145 0.354 7.77 -4.9
23 Vangheluwe, Kevin MICH RP 0.227 0.148 0.385 8.67 -5.4
24 DeNato, Joey IND SW 0.196 0.155 0.377 8.26 -5.5
25 Mascarello, Blake PUR RP 0.186 0.062 0.410 8.16 -5.6
26 Waszak, Andrew MSU SW 0.078 0.126 0.346 9.48 -7.9
27 Pack, Chris ILL RP 0.108 0.118 0.333 10.16 -9.5
28 Sandquist, Ricky IOWA SW 0.063 0.168 0.406 15.27 -18.6
AVG 0.157 0.124 0.331 7.44

RL – Pitcher’s roll. If a pitcher started 40-69% of his games, he is a swingman (SW) and 0-39% is a relief pitcher (RP)
K% – Percentage of batters faced a pitcher struck out.
BB% – Percentage of batters faced a pitcher walked and hit by pitch
BABIP – Batting Average on Balls In Play; a measure of ‘luck’
pERA – An ERA replicate via the Base Runs method that is adjusted for park
RAA – Using pERA to estimate a pitchers ‘true’ amount of runs contributed to his team.


2011 Starting Pitcher Leaderboards

Updated for games through Monday, April 5th. Minimum 75 batters faced

Rk Name Team K% BB% BABIP pERA paRAA
1 Schreiber, Brad PUR 0.259 0.068 0.278 3.76 9.3
2 Buccifero, Tony MSU 0.136 0.060 0.290 4.48 8.6
3 Hill, Steven PSU 0.182 0.051 0.275 4.53 8.4
4 Rucinski, Drew OSU 0.170 0.080 0.321 4.41 5.1
5 Anderson, John ILL 0.155 0.108 0.295 5.32 2.9
6 Wunderlich, Kurt MSU 0.187 0.096 0.315 5.61 2.4
7 Walter, John PSU 0.192 0.147 0.299 5.62 1.9
8 Morgan, Matt PUR 0.205 0.143 0.271 5.58 1.4
9 Garner, David MSU 0.168 0.102 0.333 5.95 0.5
10 Johnson, Kevin ILL 0.165 0.106 0.305 6.11 -0.1
11 Wolosiansky, Dean OSU 0.104 0.185 0.275 6.26 -0.5
12 Farrell, Luke NW 0.209 0.092 0.375 6.28 -0.7
13 Monar, Blake IND 0.193 0.140 0.385 6.84 -3.1
14 Brown, Nick IOWA 0.140 0.118 0.294 7.10 -4.6
15 Tyson, Dan NW 0.121 0.092 0.364 8.17 -6.7
16 Johnson, Heath PSU 0.110 0.233 0.312 8.32 -7.2
17 Lubinsky, Austin MINN 0.168 0.118 0.358 8.76 -7.4
18 Mills, Tyler MICH 0.180 0.129 0.371 8.15 -7.5
19 Oakes, TJ MINN 0.135 0.088 0.358 8.29 -8.3
20 Isaksson, Phil MINN 0.099 0.083 0.308 9.00 -9.4
21 Greve, Greg OSU 0.176 0.112 0.412 10.07 -11.1
22 Brooke, Francis NW 0.168 0.029 0.481 10.11 -12.9
23 Hippen, Jarred IOWA 0.140 0.084 0.348 9.14 -13.9
24 Dermody, Matt IOWA 0.202 0.150 0.371 9.62 -14.2
25 Havey, Jack NW 0.132 0.139 0.404 11.29 -17.3
26 Kimes, Corey ILL 0.150 0.170 0.387 11.86 -18.7
27 Brosnahan, Bobby MICH 0.101 0.107 0.386 10.82 -19.9
AVG 0.157 0.124 0.331 7.44

K% – Percentage of batters faced a pitcher struck out.
BB% – Percentage of batters faced a pitcher walked and hit by pitch
BABIP – Batting Average on Balls In Play; a measure of ‘luck’
pERA – An ERA replicate via the Base Runs method that is adjusted for park
RAA – Using pERA to estimate a pitchers ‘true’ amount of runs contributed to his team.


2011 Individual Hitting

Updated for games through Monday, April 5th. Minimum 50 plate appearances.

Rk Name Team PA K% BB% BABIP ISO* PA RAA
1 Holm, Jeff MSU 107 0.065 0.140 0.410 0.198 12.2
2 Deegan, Sean PSU 119 0.176 0.059 0.407 0.306 10.8
3 Eckerle, Brandon MSU 117 0.051 0.103 0.454 0.066 9.3
4 Johnson, Micha IU 131 0.214 0.122 0.453 0.125 9.2
5 Boss, Torsten MSU 109 0.147 0.101 0.429 0.247 9.1
6 Steranka, Jordan PSU 119 0.143 0.076 0.368 0.296 7.6
7 Dickerson, Alex IU 126 0.071 0.119 0.367 0.191 7.6
8 Perkins, Cameron PUR 124 0.097 0.097 0.372 0.201 6.5
9 Cypret, Ryan OSU 95 0.042 0.095 0.392 0.175 6.2
10 Talbott, Stephen PUR 114 0.132 0.167 0.400 0.117 6.1
11 Spillner, Tyler PUR 126 0.111 0.143 0.364 0.215 6.0
12 Snieder, Paul NW 103 0.184 0.126 0.409 0.205 4.9
13 DeMuth, Dustin IU 139 0.144 0.108 0.446 0.087 4.6
14 Solomon, Greg OSU 67 0.239 0.045 0.522 0.220 3.7
15 DeBernardis, Joey PSU 116 0.172 0.103 0.405 0.179 3.4
16 Plawecki, Kevin PUR 122 0.033 0.131 0.382 0.061 2.9
17 Bridges, Ryan PUR 93 0.129 0.129 0.359 0.214 2.8
18 Nick O’Shea MINN 59 0.085 0.068 0.367 0.212 2.5
19 Livingston, Jack NW 57 0.211 0.140 0.389 0.240 2.3
20 Serrato, Barrett PUR 119 0.168 0.118 0.417 0.094 2.1
21 Stevens, Trevor NW 114 0.149 0.175 0.392 0.070 1.9
22 Lashmet, Chris NW 113 0.097 0.097 0.367 0.126 1.8
23 Schultz, Trip MINN 63 0.111 0.175 0.318 0.151 1.6
24 Gominsky, Justin MINN 82 0.159 0.085 0.435 0.061 1.5
25 O’Neill, Michael MICH 110 0.173 0.091 0.375 0.113 1.3

Rk – Rank
PA – Plate Appearances
BABIP – Batting Average on Balls In Play; a measure of ‘luck’
K% – Percentage of plate appearances a player strikes out in
BB% – Percentage of plate appearances a player walks OR draws a hit by pitch
Iso* – Park-adjusted Isolated Power, Slugging Percentage minus Batting Average;
RAA – Runs Above Average using a Base Runs method and adjusted for park. Estimate of the number of ‘true’ runs a player contributes to his team.


2011 Team Defense

Updated for all games through April 5th.

Rk TEAM DER Err BIP Out xOut Delta
1 IND 0.662 31 775 513 489 24
2 MSU 0.660 32 670 442 422 20
3 PSU 0.657 38 647 425 408 17
4 ILL 0.653 26 597 390 376 14
5 MINN 0.636 19 538 342 339 3
6 OSU 0.624 37 593 370 374 -4
7 IOWA 0.621 33 742 461 468 -7
8 MICH 0.611 37 736 450 464 -14
9 PUR 0.598 37 774 463 488 -25
10 NW 0.589 36 676 398 426 -28
AVG 0.630

DER – Defensive Efficiency Ratio. Formula taken from Baseball Prospectus; Measures number of balls in play turned into outs by the team
ERR – Errors
BIP – Number of Balls In Play
Out – Number of Outs Converted
xOut – Expected number of outs converted if said team had a league average DER and had the exact same number of BIP as the team in question
Delta – Difference between expected outs and actual outs
List is sorted by team DER


Returning Adjusted Pitching Runs Above Average

One of the things I wanted to look at with the Adjusted Runs Above Average pitching totals (aRAA) was what teams lost the most talent.

What I did was take the sums from my last post and then subtracted out all of the pitchers that were seniors, red shirt seniors, or juniors that signed with a Major League team in 2010. This left me with a returning aRAA total for the pitching staffs.

Some caveats. Obviously, these being my adjusted totals, they adjust for batting average on balls in play (BABIP) and thus, assume that pitchers have little control over their BABIP’s in college baseball. This is a truism for pro baseball, but whether this actually occurs in college ball, I am not sure. It’s just as likely that it does not extend to college baseball as it does.

Also, these aren’t projections. While I’ve done my best to adjust for ‘luck’ by assigning a league-average BABIP to all of the pitchers, this does not account for growth. In college basketball, the typical player improves the most from his freshman to his sophomore season. This is something that I think probably extends to baseball, too, but I’m not positive. Until I can study how pitchers “age” so-to-speak these are not ‘projections.’

That means these are just what the title implies: the total aRAA accumulated by each team’s pitchers in 2010 once you subtract graduates and early-draftees. Read the rest of this entry »


2010 Team Level Pitching Runs Above Average

I’ve completed my run through the Big Ten’s pitching staffs on an individual level with my Runs Above Average statistics and wanted to have a post that included the team totals.

Below, I have my Unadjusted Runs Above Average (uRAA).

Team uRAA
PUR 72
MINN 55
MSU 31
OSU 10
NW 4
MICH -2
IOWA -29
ILL -31
PSU -60
IND -84

Read the rest of this entry »