Providing Context to StatCast Power Numbers

Last week, I wrote about the expected power from JaCoby Jones and Lewis Brinson. In the article, I mentioned the hitter’s rank compared to other hitters with no context resides just the rank. Today, I correct this flaw in my analysis by finding the league averages and putting the data on the 20-80 scouting scale.

While overall ranks do provide some information, it’s tough to put the rankings into context. Nelson Cruz is first in average exit velocity (EV) at 97 mph. Dropping down 2 mph in exit velocity is Luke Maile at #10. Two more is Jacoby Jones at #26. And another two is Francisco Lindor at #75. The first 4 mph in drop was just 26 players while the next 2 mph was 49 players. The batted ball decline rate is not linear and just a few tenths of a mile-per-hour can jump a player 20 spots in the rankings.

I need a way to label hitters and had to invoke some math. I took the hitters with 100 batted balls per season from 2015 to 2017 and found the overall average value. Using the 20-80 scouting scale, I gave the average values a 50-grade.

Next, I found the standard deviation from this average in both directions. For each standard deviation from the mean, I changed the grade by 10 points (standard procedure behind the scouting scale).

In some instances, a value went negative. In those cases, I fudged the number a bit (actual values in parenthesis).

I tired of writing about during math. Here are the final values in which I assumed most people just skipped to. They are in order from the StatCast leaderboard available at Baseball Savant.

StatCast Batted Ball Placed on a 20-80 Scale
Grade Range Max EV Avg EV FB/LD EV GB EV Max Dist Avg Dist Avg HR Dist % > 95 mph Brls/PA
80 +3 SD 120 95 100 94 498 233 434 58% 11%
70 +2 SD 117 93 97 91 476 213 422 50% 9%
60 +1 SD 113 90 95 87 454 192 409 42% 6%
50 Average 110 87 92 84 432 171 397 34% 4%
40 -1 SD 107 85 89 81 409 151 385 26% 2%
30 -2 SD 103 82 87 78 387 130 373 18% 1% (-1%)
20 -3 SD 100 79 84 75 365 109 360 10% 0 (-3%)

So going back to Jones and Brinson, here are their StatCast power grades.

JaCoby Jones’s 2018 StatCast Grades
Stat Value Grade
Max EV 112 60
Avg EV 93 70
Max Distance 422 45
Avg Dist 194 60
Barrel % 6.8% 60
Average 59
Lewis Brinson’s 2018 StatCast Grades
Stat Value Grade
Max EV 114 60
Avg EV 87 50
Max Distance 429 50
Avg Dist 144 35
Barrel % 3.8% 50
Average 49

From these numbers, Brinson has shown a bit more raw power this season. On the other hand, Jones has been much more consistent with his approach with an overall above average power profile.

The values can be used help find above and below average power hitters. For example, I took the five categories from above and then found the hitters with below average traits in each. One name immediately stuck out from this season, Brian Dozier (2017 stats included).

Brian Dozier’s 2017 & 2018 StatCast Grades
Stat 2018 Value 2018 Grade 2017 Value 2017 Grade
Max EV 104 30 112 60
Avg EV 86 45 88 50
Max Distance 384 30 435 50
Avg Dist 155 40 190 60
Barrel % 1.7% 40 5.7% 60
Average 37 56

His power has dropped from above average to well below average. The big key for me is the max value drops. He just doesn’t seem to have much raw power in his swing right now. His preseason training could have taken a back seat when he was dealing with a kidney stone. Or he could be hiding a semi-major injury. He is definately off.

Hopefully, I could add some context to the StatCast batted ball data. Owners can now have a better idea of a player’s value than just his rank among other hitters. Comparisons and trends can be found more easily.

Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR once, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.

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4 years ago

This is amazing. There’s so much Statcast data floating around, and so little of it has been parsed in a way that makes it actionable. Bravo.