Lots can change with the results of one swing. Ryan Jeffers’ two-run shot in the tenth inning of May 29th’s game in Houston changed the final score, a 7-5 Minnesota Twins win. It also altered Twins history. The 117.4 mph screamer bested the numbers of the brawny Nelson Cruz and Miguel Sanó. He’s now the man with Minnesota’s hardest-hit ball in the Statcast era. Achievements and assists aside, my expectations for Jeffers may have also changed.
He’s not a stranger to hard hits, having crushed a ball 113.2 mph last year, 91st percentile in the MLB. 117.4 mph represents a whole other beast. Comparable to what Vladimir Guerrero Jr. and Aaron Judge have hit, that number is 99th percentile. If he is truly on that level of bat speed, there could be an elite batter hiding within Jeffers. Factoring in his 26-year-old youthfulness, career-best 2023 hitting numbers, and the scuffling Christian Vázquez, Jeffers has become an intriguing player. Why? Well, there’s an intuitive connection between smacking baseballs and batting success.
Using the most fun form of statistical analysis (at least in my opinion), regression, we can see the relation between exit velocity and various batting measurements. BaseballSavant has this neat feature as part of their website, so you don’t need a tool like R Studio or Tableau to try it yourself. Due to some (annoying) intricacies of their website, I decided to use average exit velocity (EV) and what they call “Best Speed.” The latter does not represent bat speed, but its numbers do not match max EV.
I use xwOBACON because of its uses in assessing overall batter skill. It’s expected weighted on-base average, only that it does not factor in strikeouts or walks. Essentially, it rewards batters for making strong contact for extra-base hits. Reaching base often is nice, but the value of extra-base hits over singles and walks needs to be considered. wOBA, and therefore xwOBACON, does this.
The correlation coefficient of these two stats, xwOBACON and average EV, is a fairly strong 0.61. The technical definition would illicit an explanation of “61 percent of the variation in xwOBACON is accounted for by average EV.” Since class is not in session, my explanation of the 0.61 is: xwOBACON is fairly strongly correlated to average EV. The same graph with “best speed” in place of average EV is below. Also below is a visualization of the best indicator of xwOBACON, Barrel %.
Dissatisfied with the particular statistics available in their tool, I decided to do some quick clicking in Tableau. Unfortunately, joining expected statistics data with quality of contact data proved impossible; there was just no way for me to join the datasets on Player ID. No xwOBACON and max EV graph today.
Regardless, I came up with this graph to help explain my excitement for Jeffers’ power potential:
The r-squared value of this relationship is 0.43, an admittedly weaker correlation than what’s ideal. However, it’s important to factor in the meaning of each statistic. Barrels are not just hard-hit balls, they also factor in launch angle. We are not comparing max EV to, say, another EV-related statistic like hard-hit rate. Though not a strong correlation, an r-squared of 0.43 still implies that hitting balls harder “makes it easier” to barrel a baseball. MLB’s definition of a barrel also explains this. If you hit the ball 116 mph, you can hit with a launch angle between eight and 50 degrees; a much wider distribution than the 25-to-31-degree range for 99 mph batted balls. Crushing baseballs helps, but it’s better to keep them off the ground while you do it.
I’d like to quickly make some things clear. Jeffers hitting a ball 117.4 mph is awesome, but I am not saying raw power alone is something to get excited about. As we can see, barrel percentage has a much stronger correlation with xwOBACON. What is truly exciting about max EV is its use in predicting a player’s OPS. For every mph over 108, a player can be expected to gain six more points to their predicted OPS. For Jeffers, he is now expected to have an OPS 54 points greater than his predicted value. I don’t have access to his PECOTA projections, which was the site used by the gentleman that concluded this production over expected, but most sites penciled him in as a .700 OPS hitter.
The most pleasant takeaway from Jeffers’ hot shot is such: he has elite power, and players with elite power perform better. 54 OPS points greater than we think better. A less pleasant takeaway is that he still has to improve his contact skills if he’s to become a more complete batter. If he isn’t able to, there’s still a slugger in his game.
