Early 2019 Statcast Hitting Trends

Last Thursday, I discussed the early 2019 hitting trends and yesterday, I hopped over to the pitching trends. Today, I’ll return to the hitting trends, but this time from our good friend Statcast. With data going back to 2015, we now have a pretty good picture of what has been in the past and what is happening now.

Statcast Exit Velocity Trends
Season Avg Exit Velocity (MPH) Avg Fly Ball Exit Velocity (MPH) Avg Fly Ball Distance (ft)
2015 87.3 90.3 315
2016 87.7 91.0 318
2017 86.6 91.2 320
2018 87.6 91.6 319
2019 88.3 92.4 321

We start with exit velocity trends. First, I present the overall exit velocity. After bouncing up and down from 2015 to 2018, EV has jumped above 87.7 MPH for the first time, clearing 88.0 MPH to 88.3. That’s a significant jump. However, overall exit velocity could be deceiving and isn’t actually the number you want to focus on. Do you really care if batters are hitting their grounders or pop-ups harder than before? No, not really.

Instead, the important metric is the fly ball EV. All else remaining constant, hitting the ball harder is going to result in more home runs. It’s quite simple. Since home runs is a category in the vast majority of fantasy leagues, this has a direct impact on our projections and values. Looking at this trend, we find that fly ball EV has actually steadily risen each season, before spiking this year, representing accelerated growth. This is far more meaningful than the overall EV trend which generally shows stability (aside from the 2017 dip), before this year’s surge.

So as we know, hitters are swinging for the fences — they are striking out more, hitting more fly balls, and hitting those fly balls harder than ever.

Oddly, the increased fly ball EV hasn’t fueled much of a jump in average fly ball distance. After a jump from 2015 to 2016, there hasn’t been a whole lot of movement. Certainly not as much as one would expect given the uptick in fly ball EV and what we have seen in HR/FB rate. It’s counter-intuitive and I’m not sure what the explanation is here.

Now let’s check the quality of contact trends.

Statcast Quality of Contact Trends
Season Barrels/Fly Ball Solid Contact/Fly Ball Flare-Burner/Fly Ball Poorly-Under/Fly Ball
2015 13.5% 10.4% 3.1% 72.9%
2016 16.8% 10.0% 2.8% 70.3%
2017 19.5% 10.3% 3.6% 66.5%
2018 20.8% 11.0% 3.4% 64.7%
2019 23.7% 10.6% 3.3% 62.4%

Wowzers, check out that barrels per fly ball trend! There was consistently strong growth each season from 2015 through 2017, then growth slowed, before speeding up again this year. We can see that hitters weren’t barreling up their fly balls at the expense of solid contact or flares/burners, but rather poorly hit balls where they got underneath it. Trading poorly hit balls for barrels sounds like quite the recipe for success.

So batters have nearly doubled their barrel rate since 2015. Compared to 2017, batters have increased their fly ball EV by 1.3% and barrel rate by 21.4%. That seems significant, right? So again, how could that have possible only resulted in an average fly ball distance one foot further? It’s mind-boggling. Remember, barrels already accounts for launch angle, so you can’t argue that maybe batters are hitting their barrels at a less optimal angle than in 2017.

Whatever the explanation for the mismatch between avg fly ball distance and the other figures, all the power metrics you care about point to a leaguewide power outburst. This doesn’t rule out a “juiced” ball, of course, as that could certainly influence all these numbers.

Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year. He produces player projections using his own forecasting system and is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. His projections helped him win the inaugural 2013 Tout Wars mixed draft league. Follow Mike on Twitter @MikePodhorzer and contact him via email.

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Assuming the ’15-’18 data sets represent full season samples, couldn’t the avg fly ball distance mismatch in the 2019 data set be explained by a lower game-time temperature sample of only March/April games, thus suppressing avg fly ball distance?