Hitter Volatility Through Mid-June

Last year I reintroduced VOL, a custom metric that attempts to measure the relative volatility of a hitter’s day to day performance. It is far from a perfect metric, but at the moment it’s what we have.

If you recall, a lower VOL value is better in the sense that it indicates a hitter has been more consistent offensively. However, both good and bad hitters can be consistent, so a lower VOL always needs to be viewed in the proper context. The other thing to keep in my mind is that (as a reader pointed out) there is a strong correlation between VOL and PA/G, as we can see by looking at VOL and batting order position (for 2013):
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Now, that isn’t the worst problem, since we see similar relationships between PA/G and overall wOBA and wRC+. Also, one nice feature is that as the average PA/G increases the correlation with VOL gets weaker. What I’ve done in this iteration is to limit the calculation of VOL to just those games where the hitter logged at least three Plate Appearances. When this is done the correlation between PA/G and VOL drops to -.25 — for now, I can live with that.

Here is the VOL leader board through June 16th (min 200 PA):

VOL+ is simple a player’s VOL relative to league average ([VOL/lgVOL] * 100).

Evan Longoria (4.3 PA/G) is currently your most consistent hitter, sitting at 28% better than league average. That’s great news for the Rays considering he has a 154 wRC+ so far in 2013. Not only is producing at an extremely high level offensively, but his performance has been quite consistent, game-to-game.

Contrast that to the Marlins’ Placido Polanco. Polanco (4.2 PA/G) has the sixth-best VOL so far this year, but he’s hitting 41% worse than league average. That means the Marlins are getting a steady dose of bad from their third baseman on pretty much a daily basis.

Sorting the leader board by wOBA also gives us a few interesting comparisons. One is Josh Donaldson and Ryan Braun.

Both players have averaged 4.2 PA/G this season and have logged relatively similar wOBAs (.378 and .376, respectively). However, Ryan Braun’s VOL is 28% better than league average while Donaldson’s is 7% worse — a 35% difference. So while Donaldson has been marginally better in terms of creating runs, Braun has done almost equally as well with a greater day-to-day consistency than Donaldson.

For those interested, I also ran team-level VOL (sorted by least to greatest VOL):

Batting Order PA/G VOL
1 4.4 0.449
2 4.2 0.488
3 4.1 0.488
4 4.0 0.491
5 3.8 0.517
6 3.6 0.532
7 3.5 0.549
8 3.4 0.544
9 2.1 0.775
Royals 4.1 38 0.491 0.295
Tigers 5.0 40 0.505 0.340
Rays 4.8 38 0.507 0.324
Orioles 4.9 39 0.507 0.330
Rangers 4.4 39 0.511 0.325
Mariners 3.5 38 0.517 0.297
Indians 4.8 39 0.520 0.323
Blue Jays 4.6 39 0.522 0.312
White Sox 3.6 37 0.523 0.288
Red Sox 5.3 40 0.526 0.343
Athletics 4.6 39 0.528 0.306
Angels 4.5 39 0.529 0.321
Twins 4.2 40 0.537 0.297
Yankees 4.0 38 0.540 0.300
Astros 3.8 37 0.542 0.298
Marlins 3.2 38 0.551 0.265
Giants 4.4 39 0.552 0.303
Cardinals 5.1 39 0.563 0.307
Brewers 4.1 38 0.564 0.295
Reds 4.6 39 0.567 0.313
Pirates 3.8 37 0.572 0.277
Diamondbacks 4.4 39 0.573 0.302
Dodgers 3.6 38 0.575 0.293
Phillies 3.7 37 0.587 0.308
Padres 4.2 38 0.588 0.295
Rockies 5.2 40 0.588 0.319
Nationals 3.5 37 0.603 0.280
Mets 3.9 39 0.611 0.274
Cubs 4.0 38 0.613 0.300
Braves 4.4 38 0.621 0.310

Tigers’ fans should be happy to see their team at number two on the list, as they have the second-highest team wOBA and do the second best job of replicating that performance on a game-to-game basis. Combine a consistently great offense with that rotation and it’s easy to see why Detroit should make another deep run this post-season.

The Braves offense turns out to be the most inconsistent — slightly better than average, but inconsistent. Now, given their pitching this may not be as big of an issue were they more of an average- to below-average run prevention team. However, it makes you wonder how they will perform in the different context of the postseason.

That’s all for now. Like the velocity loss leader boards, I will be updating VOL throughout the season, hopefully on a monthly basis.


For a more complete list of hitters in 2013, see here.

Bill leads Predictive Modeling and Data Science consulting at Gallup. In his free time, he writes for The Hardball Times, speaks about baseball research and analytics, has consulted for a Major League Baseball team, and has appeared on MLB Network's Clubhouse Confidential as well as several MLB-produced documentaries. He is also the creator of the baseballr package for the R programming language. Along with Jeff Zimmerman, he won the 2013 SABR Analytics Research Award for Contemporary Analysis. Follow him on Twitter @BillPetti.

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What’s the relationship between VOL and K rate, especially on the team level? Seems like it would be pretty high.


VOL doesn’t mean the results are good or bad, just that they’re consistent.