What will we do without the zeros and ones of spring training? The underground, black market .csv file that comes from the person who knows the person who operates a Rapsodo in a mini-camp? How will we go on without knowing spin rates or the depth of clay infield impression drilled by various brands of signature spikes? I have an idea, let’s make it up.
I won’t claim to know as much about Bitcoin as some of my peers, but I know enough to determine that winning $100K of it would be great. For the more crypto-skeptical baseball fans out there, MLB and their new contest sponsor, FTX, are offering cold, hard cash as an alternative reward for their new promo contest. The challenge? Guess who will hit the longest home run of the rest of the season, the distance in feet of that home run, and the type of home run (solo, 2-run, etc.,). Let’s take a look at the details of the Moon Blast contest and see if our more enlightened way of thinking can help make a prediction.
Hi! Disclaimer: In this post I use raw Statcast data to calculate expected batting average (xBA). Evidently the raw data do not include the sprint speed adjustment that the Statcast folks said they made. That adjustment only shows up on player pages and in the search. This explains why it seemed to me an adjustment had not been made! The xBA values on player pages are much closer than the raw values and look similar to what I have presented below, and it explains my confusion herein regarding the matter.
So, this post reinvents the wheel a bit. Perhaps it can serve as a mini-primer or -tutorial for you. At the very least it can serve as further validation of the work that the folks at Statcast completed and instituted a couple of years ago. Just keep in mind that the original post below remains intact, completely unedited.
Thanks for reading!
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It has always seemed rather obvious to me that Statcast’s expected batting average (xBA) failed to properly account for a hitter’s speed (“sprint speed”). It seemed like fast hitters routinely outperformed their xBAs while slower hitters underperformed. In looking at a Statcast-era leaderboard (2015-21) of differentials between actual and expected batting averages on ground balls, obvious names rise to the top: Delino DeShields, Dee Strange-Gordon, Eduardo Núñez, Billy Hamilton, Jose Altuve, Jonathan Villar, Norichika Aoki, Mallex Smith, Jean Segura, Adam Eaton, Starling Marte… the list of players who have historically outperformed their xBAs by the widest margins are (were) all elite speedsters. At the other end of the spectrum, post-prime sluggers: Justin Smoak, Chris Davis, Logan Morrison, Jay Bruce, Kendrys Morales, etc. etc.
I thought this exact phenomenon, which is not a revelation by now, had once nudged the Statcast team to apply a sprint speed adjustment to xBA. Apparently, this happened sometime between the 2018 and 2019 seasons. Here’s the original snippet, which I very lightly edited for clarity:
In one of the most iconic and artistic pieces of American cinematography of all time, power-hungry aliens travel to Earth from Planet Moron Mountain and drain NBA basketball all-stars of their talent. While I still hold out hope that there will be a baseball version of SpaceJam within my lifetime, I can only imagine who amongst MLB’s stars would be cast. One look at statcast leaderboards could help. Here are the 10 qualified hitters so far this year who have seen the largest drain in hard-hit rate:
A while back on Twitter, Razzball’s Rudy Gamble made the following comment in a discussion of Vladimir Guerrero Jr. and his high groundball rate.
trying to think of any plus power guys that never figured out how to reduce a ton of GBs.
maikel franco is the only one that comes to mind with hosmer a possible second
— Rudy Gamble (@rudygamble) March 1, 2021
Vlad’s career groundball rate in just 900 PA is 50.5% which would rank as the 5th highest of 75 hitters. Over the same sample, his 118.9 mph Max Exit Velocity is the highest. It’s like he’s been blasting holes in the infield. So coming back to Rudy’s comment, will a power hitter, like Vlad, eventually get the ball in the air. While the answer is some, it’s likely not enough to make a difference.
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Here is a disputed fact: MLB changed the ball. League brass, on the record, wanted to make the ball livelier but also raise the height of the seams, which would increase drag. The two changes — more bounce, but also more air resistance — would, more or less, offset each other.
The fact is disputed because some of the game’s most intelligent minds — namely, renowned baseball physicists, the very people most capable of determining if the ball is, indeed, different — doubt the ball has changed. It’s imperative I tell you this because they may be right, which would make me (and MLB, for the umpteenth time), well, wrong. Everything that follows assumes the ball has changed. Maybe this meshes with what you’ve witnessed, maybe it doesn’t. This is simply one stupid man’s interpretation of the data available to us thus far.
Early returns suggest MLB accomplished what it set out to accomplish. We can use weighted on-base average on contact (wOBAcon) to describe hitter production on balls in play, aka batted ball events (BBE). The average hitter is slightly less productive in 2021 than in past years, but not egregiously so, as shown below. Also, it’s only April; as the weather warms, so should be the bats. It’s reasonable to expect 2021’s league-wide wOBAcon value to climb a few ticks before year’s end.
Now is that time in the season where you’re probably starting to get a little antsy. Why hasn’t Player A hit any home runs yet? When will Player B steal a base? Do I cut this player? Do I add that player? You may fall into the trap of cutting players on a whim because of a 3-for-31 performance thus far, but then regret that cut when he goes on a home run hitting bonanza in a few weeks. So, what indicators can you look for when trying to decide whether to buy or sell, cut or claim?
Our MLB DFS lineups don’t start and end with pitching. My first five-figure tournament score came on a night where Collin McHugh scored negative points, I think–or maybe it was, like, six points. Extremely flukey, as I made the big money because Justin Turner hit three HRs for me at nearly no ownership. I’m not saying to put pitcher every night or even every now and then. I’m just stressing that each and every slate does not rest upon our pitching.
The pitcher position is so vital because it’s the slot where we can get the most accurate projection in an extremely volatile wing of DFS.
Our pitching isn’t just a source of fantasy points. The price tags on pitchers make it so they shape they dictate the freedoms and restrictions of building our lineups. Before reading this article, it’s highly suggested that you read my article, “DFS Pitching Primer,”so the concepts discussed here make more sense.
That we’re not selecting the best players to win tournaments. We’re constructing the lineups which carry the most leverage without sacrificing many projected fantasy points.
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Blah, blah, some intro stuff on some guy that goes on too long. And here are the hitters who might be changing their launch angle (i.e. groundball rate).
Using Spring Training Ground Outs divided by Airball Outs (GO/AO), some possible swing plane changes might already be detectable. To find possible change, I found the hitters who had a combined 50% GB% and at least 300 PA from 2019 to 2020. Then, I removed those with fewer than 30 spring plate appearances and got the GO/AO values for the rest. Next, I converted the GO/AO to groundball rate (GB%) using the formula in this article. Finally, I just calculated the greatest differences and here are the results.
Maximum Exit velocity is starting to get noticed more and more as the best single stat to measure a hitter’s raw power. While quite a bit has been written on it, the subject’s money quote is from Rob Arthur:
For every mile per hour above 108, a hitter is projected to gain about 6 points of OPS relative to their predicted number.
With several new Florida Spring Training ballparks getting publicly available Trackman, I sifted through all the games and found any players who set a new over 108 mph Exit Velocity high compared to the previous two seasons. Twenty-two players have seen improvement. Most of them had a limited number of plate appearances, so setting a new high should be expected. There are a few regulars who could see an improvement in 2021.
Alejandro Kirk
Combined PA: 25
2019 Max EV: NA
2020 Max EV: 107.4
Combined Max: 107.4
2021 Max EV: 110.3
Kirk has displayed power in the past and this jump is probably setting a baseline versus an actual power increase.
