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What Yankees fans should pay attention to in spring training

Statcast data normalizes faster than any other number, and it could hold some clues for this spring

Divisional Round - New York Yankees v Boston Red Sox - Game Two Photo by Tim Bradbury/Getty Images

Spring training is a tricky time for fans, since baseball isn’t real yet and we can’t quite get excited about a good performance. Effort levels are questionable and quality of opponent is even more so, and we’ve seen lots of players have great springs that don’t carry over when the games start to count. Treat this as the recurring warning to not get too excited over a spring training OPS or ERA.

In the Statcast age, though, we can get excited about some metrics. Statcast tracks process, rather than results, and process tends to be far more repeatable and stable than results. A player’s exit velocity and launch angle are a function of his mechanics, not where the ball lands. As such, we know that raw hitting data, the information we glean from Statcast, starts to stabilize after just 20 balls in play, and becomes virtually reliable after 40.

I miss Russell Carlton, it’s hard to overstate how much easier my life is because of his research.

What does this mean for the Yankees? To start, we have to look at the first base competition, where Luke Voit and Greg Bird are vying for the job. It doesn’t look like the team will have enough bench space for two first basemen who can’t play any other position, so whoever loses this competition will find themselves in Scranton, as both players still have minor league option years remaining.

The reason Voit seems to have the inside track is because his raw contact is so much better than Bird’s. I’ve written about this before, but Statcast tracks Voit as hitting about as well as JD Martinez and Khris Davis. That hasn’t translated to long-term big-league success yet, but it shows the depths of his potential.

Bird, meanwhile, makes about the same quality of contact as Matt Wieters and Kevin Pillar. Quality of contact isn’t the only tool in a player’s profile, of course, but it is an awfully big one, and Bird just gives up so much to Voit on contact quality alone.

Fortunately for Bird, you can learn to build better exit velocity and develop better contact quality. This is what JD Martinez did; rebuilt his entire swing from the ground up and became one of the league’s best hitters. I don’t know if Greg Bird spent his winter rebuilding his swing this way, but if he did, the proof will be in the Statcast data. That data normalizes quickly enough that we’ll know just how close the competition is by the end of spring training, and who legitimately is set up with the most promise in 2019.

Meanwhile on the pitching side, Statcast doesn’t tend to help as much. Exit velocity allowed tends to bounce around a little more in terms of reliability, making it harder to predict for a pitcher than a hitter. One thing that does stabilize fairly quickly is spin rate, and that’ll play a big role in how much faith I have in J.A. Happ.

Happ relies on a high spin rate fastball up in the zone, and if that spin declines, it’s not hard to imagine him being a batting practice pitcher pretty quickly. He has a yellow flag of a slight YoY decline in spin rate, which isn’t something to necessarily panic about as much as it is something to keep an eye on:

I’m not sure if Statcast will publicly release spring training spin rates – they didn’t last year. If we can get our hands on them, that is probably the best barometer we can use to see how Happ’s year will go. The rest of his spreadsheet might be noise, but there will be something in the spin.

Statcast isn’t perfect and we still don’t know everything about how things normalize. Still, there are a couple of metrics to keep your eyes on this spring, that give better clues than traditional stats. Fake baseball might just be able to give us some real insights.