A Pitcher’s True Strike Out Potential

Oct 04

A Pitcher’s True Strike Out Potential

Mike Podhorzer has looked into the relationship of a batters’ average fly ball distance as it relates to their HR/FB ratio, and has found results that will allow others to more accurately project a hitter’s home run totals from year to year.

This got me thinking. Which can be a good or bad, but in this case, the authors’ labor produced a fruitful return. While a hitters’ HR/FB ratio can fluctuate indiscriminately from year to year, Podhorzer has proven a batters’ average fly ball distance is a better indication of a player’s true talent power production. In the same light, my study looks at how a player’s swinging strike rate (SwStr%) is a better indication of a pitcher’s strike out potential than K/9.

My assumption was that K/9 and SwStr% have a strong relationship. But, how strong of a relationship is it? To find this out, I took all qualified starter seasons from 2003 to 2013, which gave me a sample size of 933 pitchers, and ran a correlation between their SwSTR% and their K/9. The results showed that there is an exceedingly positive correlation between SwSTR% and K/9, to the tune of a .807 correlation coefficient and a .65 R2.

Screen shot 2013-10-03 at 1.06.11 PM

What is important to note is that there are very few pitchers present in the sample with a SwStr% above 13%, which may be symptomatic of something larger. Getting batters to swing and miss is difficult. The more often you can get a batter to swing and miss, the more valuable you are as a pitcher. As a result, the higher the SwStr%, the smaller the sample size becomes. For example, Johan Santana (2004) and Kerry Wood (2003) are the two lone dots to the farthest right on the graph with SwStr% of over 15: wow.

After the relationship between SwStr% and K/9 ratio became unmistakable, I calculated what a particular SwSTR%s translates into, as far as K/9, with the formula Y=68.473*x+0.8435, and got this chart:

Screen shot 2013-10-03 at 1.55.30 PM

The next step is to take what we have discovered and apply it to a sample. The chart below shows each qualified pitcher for 2013, their SwStr%, xK/9, K/9, and K/9-xK/9.  xK/9 is what we would expect a pitcher’s K/9 to be based off of their SwStr%, and K/9-xK/9 shows us how much a pitcher over performed or under performed their SwStr% and xK/9.

Ubaldo Jimenez8.80%6.869.56-2.70
Yu Darvish12.60%9.4611.89-2.43
Jose Fernandez10.10%7.759.75-2.00
Justin Masterson9.10%7.078.94-1.87
Shelby Miller9.00%7.008.78-1.78
A.J. Burnett10.60%8.099.85-1.76
Cliff Lee9.40%7.278.97-1.70
Yovani Gallardo6.90%5.567.17-1.61
C.J. Wilson8.10%6.387.97-1.59
Chris Tillman7.90%6.247.81-1.57
Gio Gonzalez9.40%7.278.83-1.56
Lance Lynn9.50%7.348.84-1.50
Felix Hernandez10.70%8.169.51-1.35
Stephen Strasburg10.60%8.099.39-1.30
Chris Sale10.80%8.239.49-1.26
David Price7.90%6.247.28-1.04
Max Scherzer12.00%9.0510.08-1.03
Matt Cain8.60%6.727.71-0.99
Jeff Samardzija10.50%8.029.01-0.99
A.J. Griffin8.60%6.727.7-0.98
Dan Haren9.00%7.007.95-0.95
Justin Verlander10.50%8.028.95-0.93
Edinson Volquez8.50%6.657.55-0.90
Jon Lester8.40%6.597.47-0.88
Hyun-Jin Ryu8.10%6.387.22-0.84
Scott Feldman7.20%5.766.54-0.78
Adam Wainwright9.60%7.418.16-0.75
Ryan Dempster9.90%7.618.32-0.71
Ian Kennedy9.60%7.418.09-0.68
Anibal Sanchez12.40%9.339.99-0.66
Rick Porcello8.50%6.657.25-0.60
Mark Buehrle6.90%5.566.14-0.58
Bronson Arroyo6.00%4.945.52-0.58
Mike Minor9.60%7.417.96-0.55
Doug Fister8.00%6.316.85-0.54
Jose Quintana8.80%6.867.38-0.52
Madison Bumgarner11.10%8.448.9-0.46
Homer Bailey10.70%8.168.57-0.41
Jeremy Guthrie5.10%4.334.72-0.39
Bartolo Colon6.30%5.155.53-0.38
Derek Holland9.90%7.617.99-0.38
Travis Wood7.70%6.116.48-0.37
Tim Lincecum11.10%8.448.79-0.35
Mike Leake6.70%5.425.71-0.29
Wade Miley7.90%6.246.53-0.29
Joe Saunders6.10%5.015.26-0.25
Matt Harvey12.50%9.399.64-0.25
Jeff Locke8.30%6.526.76-0.24
Julio Teheran10.50%8.028.24-0.22
Clayton Kershaw11.40%8.648.85-0.21
Bud Norris9.30%7.207.4-0.20
James Shields9.80%7.547.71-0.17
Kyle Kendrick6.50%5.295.44-0.15
John Lackey9.80%7.547.65-0.11
Mat Latos10.30%7.897.99-0.10
Eric Stults7.10%5.705.79-0.09
Andrew Cashner8.10%6.386.46-0.08
CC Sabathia9.60%7.417.46-0.05
Kevin Correia5.90%4.874.9-0.03
Edwin Jackson8.90%6.936.930.00
Jordan Zimmermann8.70%6.796.790.00
Miguel Gonzalez8.10%6.386.350.03
Kyle Lohse7.30%5.835.660.17
R.A. Dickey9.40%
Wily Peralta8.30%6.526.330.19
Jhoulys Chacin7.50%5.975.750.22
Hisashi Iwakuma10.30%7.897.580.31
Andy Pettitte8.40%6.596.220.37
Jeremy Hellickson9.50%7.346.970.37
Zack Greinke10.40%7.967.50.46
Patrick Corbin10.70%8.167.690.47
Ricky Nolasco10.60%8.097.440.65
Cole Hamels12.00%
Ervin Santana10.00%7.686.870.81
Dillon Gee9.40%7.276.420.85
Hiroki Kuroda9.90%7.616.710.90
Kris Medlen10.90%8.307.191.11
Jorge de la Rosa9.20%
Jarrod Parker9.60%7.416.121.29

The results show that Ubaldo Jimenez, Yu Darvish, and Jose Fernandez are the pitchers who have outperformed their xK/9 the most in 2013. These three pitchers also have great a great amount of deception and/or command (deception in Jimenez’s case: because, no one has ever called Ubaldo a control artist). And, while they may have outperformed their true talent in 2013 to an extent—they all had remarkable years—maybe that deception and control, which SwStr% does not take into account, leads to less swings by batters and more pitches taken for strikes, as opposed to swung at for strikes.

Perhaps xK/9 is more helpful when we look at pitchers who underperformed their SwStr%, like Jarrod Parker and Kris Medlen. Both of these pitchers had down years compared to what their projections suggested, but their xK/9s seem to be optimistic about their futures. Parker showed a .18 improvement in his K/9 from the first half to the second half of the season, while Medlen showed almost a full run improvement going from a 6.81 K/9 in the first half to a 7.67 K/9 in the second half.

While xK/9 may miss something—deception and command—when it comes to pitchers that outperform their SwStr%, xK/9 seems to find a reason to be optimistic when it comes to pitchers like Kris Medlen and Jarrod Parker who have underperformed their SwStr% and strike out potential.

Devon Jordan is obsessed with statistical analysis, non-fiction literature, and electronic music. If you enjoyed reading him, follow him on Twitter @devinjjordan.

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