Exit Velocity Leaderboards | The Process Report

Exit Velocity Leaderboards

Exit velocity is all the rage right now. It’s shiny and new and might even be an incredible tool for estimating the contributions of a ball player on his team. Unfortunately, like any new technology some folks have latched on to the gospel before the final draft has been written. There are kinks to work out, but lucky for us fans there are brilliant folks out there already ironing the creases into oblivion.

Baseball Prospectus just rolled out a new leaderboard that adjusts for some of the discrepancies seen between parks due to systemic issues, but also for the park factors that even curmudgeons reluctantly acknowledge exist:

However, we’ve seen many people take the raw average of a player’s exit velocities and assume it to be a meaningful indication, in and of itself, of pitcher or batter productivity. This is not entirely wrong: Raw exit velocity can correlate reasonably well with a batter’s performance.

But this use of raw averages also creates some problems. First, if you use exit velocity as a proxy of player ability, then you must also accept that one player’s exit velocity is a function of his opponents, be they a batter or pitcher. Put more bluntly, a player’s average exit velocity is biased by the schedule of the player’s team.

Second, and much more importantly, we have concluded Statcast exit velocity readings, as currently published, are themselves biased by the ballpark in which the event occurs. This goes beyond mere differences in temperature and park scoring tendencies. In fact, it appears that the same player generating the same hit will have its velocity rated differently from stadium to stadium, even if you control for other confounding factors.

They go on to point out some of the smaller issues that they are working to smooth out, but the real takeaway is that they have used their adjusted exit velocity in conjunction with launch angle to derive a leaderboard of expected runs contributed. You can find links to each of the leaderboards for pitchers and batters in the linked article, but here’s a snippet of what they’re hoping to capture:

Finally, our leaderboards also go one step further, and translate exit velocity and launch angle into estimated runs generated/prevented by the player. These run estimates account for both adjusted exit velocity and launch angle, as it is the combination that really matters. To our knowledge, no other public leaderboard does this.

This should not be considered the final step as evolution is often gradual and always occurring, but this is a big leap. As such, let’s use these leaderboards to focus solely on the Rays:


The rank is out of the 566 batters they have listed and to make that context easier to absorb I have added the percentile column. This immediately passes the sniff test. The guys on each of the tails have become noted for their tendencies. Souza, Forsythe, Casali, Longoria and Dickerson, everything they hit is a scorcher. Conger, Kiermaier, Morrison and Jennings have caught many a fan’s ire for their inability to hit the ball with authority. The Rays have basically six guys, who are mostly everyday starters, that are essentially in the upper quarter of batted ball velocity. This is a great thing! Additionally, we can see that for most of those guys their actual runs created lags behind the prediction perhaps indicating that many of these guys should continue to regress upward.


Flipping over to the pitchers we see a different story. The stalwarts of the bullpen are doing an above average job of limiting hard contact, but the best starter on the list, Smyly, is only middle of the pack league-wide. Chris Archer has been one of the worst in the game, which is something you know if you’ve watched him pitch at all. Even the outs are loud this year. Odorizzi and Moore haven’t been much better and we also see some of the bullpen flotsam in there towards the bottom. While upgrading a weak pen link is relatively easy it is very difficult for a team to get their starters straightened out. Unlike the hitters we can also see that several of these guys have been a bit fortunate and probably should have yielded even more runs.


To wrap this up we can look at the totality of the leaderboards for each team by focusing merely on the expected and actual runs earned or yielded. As a team the Rays offense is in the bottom third of the league in predicted runs, and has shown up even that modest total by having the fourth lowest actual runs. This gap should tighten up as time goes by, but without raising the predicted runs you should not expect to see this offense all of a sudden take flight.

We see the opposite story when looking at the pitchers. Rays pitchers feature solidly in the top-ten of staffs when it comes to predicted runs, but when looking at the actual they place second trailing only the wunderCubs. This should regress down slightly, but if the predicted runs keep tracking along you’re looking at one of the best staffs in baseball.

The last few weeks have seen these roles reverse on the team as it counted on riding good pitching and enough hitting to another divisional banner. The short term sees the Rays hitting better than expected and pitching, well, lousy, of late. To capture where we’re going, however, it is beneficial to use the whole of the season, which sorts some of the small term bias out. The offense has been a joy to behold, but I’m not completely sure it is here to stay. Getting the pitching back on track will help this team continue to climb out of the hole they have dug for themselves.


  1. mattc286 wrote:

    Great stuff! Interesting that the batters are underperforming in runs produced vs. expected based on adjusted exit veloicity (as we might have expected watching the games) but also that the pitchers are overperforming. How does this compare across the league? In other words, is the avg. expected = avg. produced for both hitters as a whole and pitchers as a whole, or is there some systematic error here that is crediting pitchers more than is due?

    • Jason Hanselman wrote:

      Thanks! It would appear to be a systemic issue as the total for predicted runs (for batters) is at 1,816 with actual being at 1,666. It’s not enormous, but it does exist at an inflation of close to 9%. I don’t really want to venture a guess as to why this is the case, though will put more credence in the gap if it still exists in another month or so. Jonathan Judge (@bachlaw) is a great twitter follow and he was one of the people that worked on this so I’d reach out to him with any model-specific questions.

      • mattc286 wrote:

        Thanks for the info, will be interesting to see if the trend continues or regresses. I should use Twitter more than I do, but I went ahead and followed him. Still, very encouraging to see 4 guys in the top 10%. And the Rays took the lead in HRs last night, so they got that going for them, which is nice.

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