First-Half Exit-Velocity Overachievers and Underachievers

When a player puts up a great first half that departs considerably from his established levels, it’s generally expected that the player will come back to earth in the second half. This is regression in its simplest form, and it’s baked into the sort of projections which appear at this site. This isn’t to say the player won’t continue to be good, just that he might not be as good as he showed in the first half. The same is true for players with uncharacteristically poor first halves. We expect them to figure things out and get back closer to their prior performance level. We can look at many indicators of the poor performance — BABIP is usually prominent — and tie some of the performance to bad luck. Sometimes it’s injuries. Another avenue we can travel down is to look at exit velocity.

Over the winter, I looked at players who under- or overperformed their average exit velocities in the first half of 2015 and then compared it to their second-half production. Standard caveats about the importance of launch angle and somewhat incomplete data apply, but those players who most outperformed their exit velocity in the first half last season saw massive drops in production in the second half. Here’s the methodology I applied in February (and repeated a few weeks ago in looking at players who underperformed last season):

I created IQ-type scores for exit velocity and wOBA from the first half of last season based on the averages of the 130 players in the sample. In each case, I assigned a figure of 100 to the sample’s average and then, for each standard deviation (SD) up or down, added or subtracted 15 points.

Once the IQ scores for both stats were calculated, I subtracted the IQ score for exit velocity from the IQ score for wOBA to find the players with the biggest disparities.

Here are the overperformers from the first half of last season — i.e. the players whose production most exceeded their exit velocity:

As you can see, players who outperformed their exit-velocity numbers in the first half of 2015 produced a collective wOBA that was 50 points lower in the second half of that season.

With that in mind, here are the overperformers from the first half of this season:

On the whole, this group had a very good first half of 2016. You might notice that three names carry over from the previous season. Last, year Starling Marte increased his exit velocity in the second half and maintained his production. Anthony Rizzo’s production fell, meanwhile, but remained at a high level, and Charle Blackmon saw his numbers fall a bit. Many of these players are bound to experience a decline in production in the second half just because the numbers are high. The chart below shows the above players along with their first half wOBA — as well as their projected wOBA for the rest of the season.

A 30-point decrease in wOBA is already expected from these players because their performances were uncharacteristically strong. Starling Marte, Mike Trout, John Jaso, and Jose Iglesias are projected to have minimal changes, while the rest of the group is expected to experience more substantial drops. Last season, a similar group dropped 50 points on average, so it will be interesting to see how this group fares the rest of the season. The easiest way to outperform your exit velocity is to draw a lot of walks; those have little to do with exit velocity but are very important to wOBA. Many of the players above are quite good at drawing walks, but that was true of last year’s group, as well, and they still experienced a drop.

Next we can turn to the group of players underperforming their exit velocity. This group of players is hitting the ball harder than would be expected given their production. This is the group from last season:

The members of this group experienced a 44-point increase in wOBA during the second half of 2015.

Now here are the candidates this season:

Just like with the overperformers, there are ways to understandably underperform. If a player strikes out a ton, then he’s limiting the number of times the decent exit velocity will work for him. One thing to note among these players is that there are no players carried over from the previous season. Every player on this list is new.

Another thing you might notice is that the list this year is considerably larger than last year’s. There’s a survival bias involved in last year’s group, as only players who played enough in both halves were examined. Some who might have made this list a year ago might have dropped off due to a lack of playing time perhaps because of their struggles. It will be interesting to see how that works this year, and we can already see with Yan Gomes and Juan Uribe that there are players who will not provide a good analysis at the end of the year because they will not have played.

As for some of the rebound being built into the projections, we have that with the underperformers as well.

Justin Upton can’t possibly be this bad over the course of a full season. Yasiel Puig and Randal Grichuk were both just sent to the minors, so it remains to be seen whether they will get an opportunity to improve their numbers. The projections for many of these players look to be closer to their first-half production, so whether or not these players improve significantly will provide evidence on whether this type of analysis is worthwhile. We’re still scratching the surface of what we should eventually be able to do with exit velocity, but the players in this post should be watched over the course of the second half to see where the production leads.