Spring Training Hitter Stats Deep Dive

Spring training stats don't matter. Except when they matter a little bit. In 2015 The Economist's Dan Rosenheck presented the evidence that certain stats like walk rate, strikeout rate, isolated slugging, and steal attempt rate could increase the accuracy of projections--especially for rookies. You can view his slides from the MIT Sloan Sports Analytics Conference here. Although Rosenheck describes his math as elementary, I'm going to dumb it down a bit to get to something that's doable for me and hopefully still useful.

We're going to compare the performance of White Sox players in the Cactus League relative to the league average, then see how that compares to their ZiPS projection relative to the American League.

The baselines
I set an arbitrary minimum of 40 plate appearances for players in the Cactus League so that the standard deviations weren't messed up by players who barely played. The average walk rate (BB/PA) for said players was 8.56%, the average strikeout rate was 19.60%, and the average isolated power was a robust .190. How does this compare to the 2016 American League season? Per BRef's listed 600 PA average, AL hitters walked at an 8% clip last year, struck out at a 20.67% rate, and had an ISO of .165. There are some rounding issues here. Sorry!

The walk rates and strikeout rates between the AL 2016 and Cactus League 2017 were pretty similar. The main differences here are the standard deviations. With a higher talent variance and smaller sample size, the the Cactus League standard deviations (for hitters with 40+ PAs) are 4.71 BB%, 8.50 K%, and 0.102 ISO. For 2016 American League hitters (min. 60 PA), the standard deviations were 2.97 BB%, 6.72 K%, and.059 ISO. I'm assuming that ZiPS is projecting similar walk, strikeout, and power rates, and standard deviations as we saw in 2016.

The numbers

Cactus League Rate Stats Standard Deviation Comparison to ZiPS
Player BB% K% ISO P CL BB Z Diff CL Z K Diff CL Z ISO Diff
Melky Cabrera 3.3% 6.6% 0.103 -0.63 -0.18 -0.24
Nicky Delmonico 10.1% 11.6% 0.345 0.66 -2.53 1.16
Jose Abreu 5.7% 12.9% 0.203 -0.17 -0.55 -0.50
Leury Garcia 3.0% 13.6% 0.082 -0.19 -1.29 0.13
Yolmer Sanchez 6.5% 14.5% 0.250 0.69 -0.88 1.42
Tyler Saladino 7.3% 14.5% 0.347 0.57 -0.55 2.15
Todd Frazier 4.9% 17.1% 0.154 -0.83 -0.65 -1.07
Tim Anderson 0.0% 19.3% 0.123 -0.03 -1.13 0.09
Danny Hayes 7.0% 20.9% 0.225 -1.37 -1.32 0.84
Jacob May 3.1% 21.5% 0.175 0.09 -0.56 1.33
Adam Engel 15.9% 22.7% 0.028 1.87 -1.27 -0.57
Avisail Garcia 4.8% 25.4% 0.153 -0.29 0.03 0.11
Yoan Moncada 10.9% 30.4% 0.366 -0.32 0.50 2.01
Cody Asche 18.9% 32.1% 0.404 2.44 0.42 2.12
Matt Davidson 9.2% 38.5% 0.210 0.14 -0.09 0.40
Rymer Liriano 11.3% 41.5% 0.170 0.62 0.57 0.35

So what are we looking at here, hoss?

Bolded values in the right three columns mean that the player had a better standard deviation relative to league average in the Cactus League than ZiPS projects him to in the American League.

Nicky Delmonico had a walk percentage that was about a third of a standard deviation above Cactus League average. ZiPS projects him to have a walk rate about a third of a standard deviation below the league average walk rate (in the 2017 AL). The difference between +.33 standard deviations and -.33 standard deviations is .66 standard deviations (Cactus League Walk ZiPS difference). He is projected for a strikeout rate 1.59 standard deviations more than league average (having a high strikeout rate is bad), but in the Cactus League he struck out at a rate .94 standard deviations below the league average. His power relative to league average was also better than his projected power relative to league average, so he gets bold across the board.

Tyler Saladino, Yolmer Sanchez, and Jacob May (barely) are the other three hitters who beat expectations in all three comparisons here. Cody Asche had a crazy Spring filled with three true outcomes. Adam Engel controlled the strike zone, but apparently did not hit the ball with any authority.

So what does it all mean?
Probably not all that much! Rosenheck has said that an extreme spring performance relative to expectations may change the projection by 50 OPS points. Delmonico's impressive strikeout rate (and the fact that he's a rookie) may qualify him for that sort of back of the envelope adjustment. That's still probably not enough of a bat for 1B/DH, but it may be worth noting that he's been in the black in BP's Fielding Runs Above Average metric at every minor league stop save one, and most of that time was at third base. Let's see what he does at Charlotte.

You can find support here for the Lawrie dismissal, Bourjos trade, and decision to roster Asche.

Glad we have all of this sorted out in time for everyone to immediately forget about all spring training stats forever.
Cactus League stats are sourced from, 2016 American League stats from Baseball Reference, and Dan Szymborski's ZiPS projections were found on

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