Introducing the HIM metric

HIM

Introduction

Rogelio was awesome and referred to a new metric in his recent Wenceel Perez article that has been in the works. This article is the first of a series and is the explanation of what it is, what it should measure, and a sneak peek at who has what in some of the Tigers minor league organization right now. Without further ado, let’s get into it!

What is it

It’s supposed to be a metric that helps combine how hard a player hits the ball with actual power production. It’s still in it’s infancy and could very well see some changes along the way. Similar to wRC+, 100 is going to be league average. The lowest you will see is 0 since you can’t really have a negative ISO or hard hit rate.

The clever name from Chris is the Hard hit rate ISO Metric, or, HIM.

And here’s the equation being used:
(ISO / league ISO) * (Hard Hit Rate / league Hard Hit Rate) * 100

I’ve got this setup so that it can encompass the season or you can break it down by batted ball type, and it all reads the same.

Though I want to note, like with any sort of metric, this is still somewhat a work in progress. There could be changes along the way to adjust this rankings.

What is it supposed to tell you

It’s meant to show you how above or below average a player is at not only hitting the ball hard, but how productive they are when compared to the rest of the league. This inspiration came from Spencer Torkelson early in the year. So many conversations of how he’s hitting the ball hard, yet we were seeing no results. This should help to show that in one spot.

There is some testing that still needs to be done to see how it’s correlating through the farm system from level to level. As with anything, the larger sample size, the more accurate the results are going to be.

If a player has a 0, it means either their ISO or hard hit rate (sometimes it could be both) is at 0. This was done by design because they usually go hand-in-hand. It’s not very often we see someone with any sort of ISO who isn’t also hitting the ball hard. It’s also not very often we see a player hitting the ball hard and not getting rewarded.

How do Detroit Tigers guys look?

This is the real fun part, right? Right now we have the metric calculated out for Toledo and Lakeland via the data we have been able to gather from baseball savant. So let’s take a look!
Note: this is through games played on 8/28

First let’s look at Toledo:

Overall HIM Groundball HIM Line drive HIM Flyball HIM
Wenceel Perez 160 493 154 98
Justyn-Henry Malloy 108 130 46 179
Colt Keith 147 224 61 184
Tyler Nevin 147 137 65 150
Nick Maton 102 0 62 115
Andre Lipcius 59 35 34 58
Isan Diaz 196 0 112 143
Ryan Kreidler 108 94 0 195
Dillon Dingler 106 0 74 103
Eddys Leonard 159 131 68 129
Donny Sands 68 184 87 22
Michael Papierski 54 132 75 19
Nick Solak 44 245 24 75
Parker Meadows 133 125 148 100
Joe Rizzo 121 278 104 72
Andrew Knapp 87 41 75 79
Grant Witherspoon 96 0 178 87
Corey Joyce 76 296 50 85
Johan Camargo 96 105 63 64
John Valente 45 61 54 16
Akil Baddoo 68 133 75 0
Riley Greene 0 0 84 321
Brendon Davis 87 132 81 90
Andy Ibanez 196 190 217 95
Jermaine Palacios 98 0 29 187
Jonathan Davis 159 72 140 234
Kerry Carpenter 60 0 36 79
Matt Vierling 0 0 0 0
Steele Walker 23 0 84 0
Zack Short 163 0 142 237

And next Lakeland:

Overall HIM Groundball HIM Line drive HIM Flyball HIM
Jim Jarvis 41 79 117 0
Max Anderson 148 86 94 104
Mike Rothenberg 196 198 87 405
Jose De La Cruz 156 53 179 204
Manuel Sequera 89 0 185 67
David Smith 0 0 0 0
Abel Bastidas 55 63 66 21
Sergio Tapia 74 341 36 40
J.D. McLaughlin 84 176 107 18
Seth Stephenson 67 337 71 18
Cristian Santana 77 0 48 98
Bennett Lee 0 0 0 0
Max Clark 62 0 150 0
Josue Briceno 50 0 75 0
Kevin McGonigle 28 0 0 0
Clayton Campbell 91 0 75 0
Brett Callahan 104 0 84 0
Cole Turney 178 0 0 728
John Peck 0 0 0 0
Carlos Pelegrin 136 166 77 162
Andrew Jenkins 76 201 57 21
Dillon Dingler 475 0 380 460
Ryan Kreidler 105 0 0 117
Archer Brookman 100 265 55 96
Moises Valero 107 74 91 112
Luke Gold 130 122 88 104
Daniel Cabrera 40 0 0 81
Alvaro Gonzalez 98 0 0 182
Peyton Graham 94 217 48 74
Mario Feliciano 109 0 137 0
Dom Johnson 128 65 66 188
Lazaro Benitez 95 0 180 122
Tyler Johnson 27 103 14 0
Carlos Mendoza 105 0 0 364
Adinso Reyes 140 111 94 222
Andrew Navigato 116 244 83 39
Wenceel Perez 156 600 54 0

Some things stand out to me right away.

  • Lots of examples in here why I mention sample size. Riley Greene in Toledo is a prime example.
  • Every player is below average in at least category… except for Parker Meadows.
  • Max Anderson is confusing. Overall, he seems to be really good. Individually he’s… not. But this is because he excels in either ISO or hard hit rate for each and is below the average for the other in all three categories. Overall, he’s above average for both. He is 1.2% higher for groundball hard hit rate, which is nearly 50% of his batted ball type. That’s going to help him out a bit in his overall score. This can be applied to several players listed here as well. And it is also why it’s broken down this way.

Conclusion

Hopefully, you enjoy this! I have never done anything like this. As changes and updates are made, there will certainly be more posts on it explaining those changes and why it was decided to go that way. There will also be a big league’s version of it as well. Some of those numbers are interesting! And if you have any questions, comments, criticisms, you can find me at OPSenheimer on basically all social media platforms at this point. Feel free to ask away!

Introduction Rogelio was awesome and referred to a new metric in his recent Wenceel Perez article that has been in…

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