The 2020 Big 12 Baseball season, like sports everywhere, came to an unceremonious end a few weeks ago after just a month of games. Such a shortened season makes evaluating player performances from that season tricky because of a few factors.
First, the small sample size of at-bats that players received. Dylan Neuse, a Texas Tech CF, led the Big 12 in plate appearances in 2020 with a whopping 89, less than a third of the 289 plate appearances that he had in 2019.
Second, the season got canceled before Big 12 play began, meaning that teams weren’t playing very many marquee matchups against talented foes. The teams that each Big 12 squad were not of the powerhouse variety, leading to drastically different talent levels between Big 12 teams and their opponents, which makes the records and stats skewed.
Despite these issues with the shortened season, player evaluation continues and we’ll use what we have.
Using available stats, pulled from d1baseball.com and individual team websites when necessary, I created a profile for each “qualified” player in the Big 12. The qualifying cut-off ended up with 48 plate appearances being the lowest total, in addition to the requirement of hitting a % of games played number.
From the 64 qualified hitters, I got the conference averages from the 2020 season in order to evaluate the players against their peers in their conference. Here are the conference averages for the (shortened) 2020 season and the 2019 averages.
The 2020 averages are higher than the 2019 averages and I believe the explanation lies in the level of non-conference competition that teams were facing. I wanted to point that out before jumping into the evaluations because some of the Big 12 players had phenomenal performances that wouldn’t have been sustainable once Big 12 play arrived.
Most of these stats are pretty standard, but I want to give a brief explanation for the newer ones and explain why I chose those stats.
We’ll start with wOBA, which stands for weighted on-base average. It’s very similar to OBP and assigns different weights to hits, extra-base hits, walks to give credit to outcomes that are more favorable. OBP treats all times on base as equal when, in reality, they aren’t. In terms of evaluating with wOBA, it uses the same scales as OBP, meaning that a good OBP number is also a good wOBA number and vice versa.
Calculating wOBA weights gets really complicated with run expectancy matrices and linear weights, stuff that I frankly don’t know how to do right now. So, I chose to take the coefficients for the 2019 MLB season from FanGraphs.com, which can be found here. Thus, the formula for wOBA came out to this:
Using MLB numbers for this exercise is not a perfect way to get wOBA for the Big 12 season, but it’s what we’ve got so I’m using it.
I’m also using BABIP, Batting Average on Balls in Play, in this exercise. BABIP is exactly what it sounds like; a measurement of how many times a ball in play goes for a hit. The equation never changes, making it a reliable stat to use.
However, the opposing defense and luck are things that can affect a BABIP and explanations for drastic changes in hitting lines, but the defense and luck factors make BABIP a fickle stat. But it helps as an indication of how often hitters get hits on their batted balls, giving us an opportunity to see what a player’s quality of contact is.
The last stat I want to talk about is wRC or Weighted Runs Created. wRC is an attempt to quantify, with a single number, the total offensive value of a player and is based on wOBA. wRC is a cumulative statistic, rewarding total production, rather than just on a per plate appearance basis which is nice because it rewards those who play more, while also supporting per appearance players by using wOBA. The formula is as follows:
The league wOBA for the Big 12 in 2020 was 0.361, while the wOBA scale was 1.157 (FanGraphs.com), and the Big 12 averaged 0.16 runs per plate appearance. Put that together and you get the formula for wRC that I used. The median wRC total was 10.33 and the maximum was 20.408 to give you an idea of the scale.
This isn’t a perfect way to evaluate college baseball players but with the lack of accessible advanced stats for college baseball, I had to manufacture my own with the tools at my disposal. The small sample size and the lower level of competition are things I want to stress again because I believe that they had an impact on the higher-level performance in the short 2020 season versus 2019. As long as we acknowledge that, we can still proceed with Big 12 Baseball evaluations.
So, without further ado, let’s jump in and examine the performances of the 2020 Jayhawks.
On the surface, Anthony Tulimero had a very solid start to his collegiate career with Kansas, posting a 0.314/0.368/0.412 slash line in 57 plate appearances for the Jayhawks. A slash line like that indicates a contact hitter without much power who needs a little more patience at the plate to be a super-effective OBP guy. That sounds accurate looking at the rest of Tulimero’s profile, particularly his BB% of 8.77% and K% of 22.81%, both marks that are below average.
The power numbers, XBH%, and HR% are also below average, which we extrapolated from his below average SLG. However, they aren’t *that* far below average, especially for a freshman as power is something that we expect to come in time as a player grows a little more and gets time in the weight room with a collegiate training staff.
His best number is easily his batting average of 0.314 that was above average in 2020. However, given his higher BABIP, I think it’s worth wondering how sustainable that pace is for Tulimero. With his hard contact/power numbers below average, it looks like he got lucky with his batted balls falling for hits in between the defense which isn’t really sustainable.
All that being said, Tulimero had a freshman season that had some promising signs and some indicators of what he needs to work on in the future.
Benjamin Sems made some big jumps from 2019 to 2020 while also running into some bad luck which affected his surface stats. His most notable improvements came with his BB % and K % improving, increasing to 17.33% and decreasing to 14.67% respectively. That improvement, especially in his BB %, was key to maintaining an above-average wOBA and OBP despite his batting average falling down to 0.255.
That decrease in batting average is interesting because it’s also accompanied by a sharp drop in SLG from 0.437 to 0.364 despite an increase in the rate at which he hit HRs, from 6.67% to 14.29%. The last piece of the puzzle lies in his XBH/PA rate of 2.67% which is pretty bad.
I think that Sems got really lucky, in 75 plate appearances, to have as many hits go for HRs as he did, which skewed his HR % higher than should be and his XBH % lower than should be (again the perils of using such small sample sizes). In fact, those HRs that he hit were his only extra-base hits of the season. And, as his BABIP of 0.279 shows, he was not getting hits on balls in play very often, meaning that he was making really weak contact or hitting it right at the defense, or both. Regardless, I think that the AVG & BABIP would’ve regressed back to 2019 numbers and, even with the lower contact, Sems still managed to be a productive player with his wRC of 12.48 because he drew so many walks.
James Cosentino had one of the most interesting profiles in the conference after the 2019 season. He didn’t do anything particularly well except get on base at an above-average clip for one reason only: he was hit by 22 pitches in 2019. Naturally, such a thing isn’t really repeatable and he’d only been hit by 1 by the time the season ended leaving him with a poor OBP and wOBA.
He just doesn’t really *do* anything at the plate, although he was hitting HRs more frequently through his first 72 plate appearances. But we have no idea if that would’ve continued through the remainder of the season (I’m betting not). Beyond that, he didn’t add very many other extra-base hits or anything else really. His wOBA of 0.228 shows just how bleak things were for Cosentino.
His BABIP of 0.196 wasn’t helping things either and is so low that he either became the worst hitter in the conference or had a lot of things working against him in the early parts of the season. I don’t think that Cosentino is a 0.179 hitter, but I don’t think his average was going to climb super high. At some point, BABIP is controllable by the hitter with their quality of contact and it doesn’t look like Cosentino was making good contact. His wRC of 3.26 is one of the worst marks in the league and only propped up by his 72 plate appearances.
Nolan Metcalf had a remarkable power surge as a junior, posting a strong wOBA of 0.357 despite a batting average of just 0.244. However, his BABIP of 0.296 and average or above hard contact numbers (XBH % and HR %), indicate that he may have fallen victim to hitting the ball hard, but directly at the defense. Of course, deciphering exactly what caused that low BABIP is going to be extremely difficult with only 51 plate appearances to work with, but again, that’s what we’ve got to work with.
His BB % of 11.76% is just barely average, but he did also get hit by 3 pitches in the early goings of 2020 which helped boost both his OBP and wOBA up to respectable levels. The K % of 23.53% isn’t great, but you’ll live with it if 20% of his hits are going to go for HRs.
Skylar Messinger didn’t really change much from last season. He did improve his BB rate up to 11.59%, sneaking just above league average after hovering around 8.4% in 2019. But his power numbers fell (except for his HR rate because he hit 1 in 69 PA vs 2 in 239 in 2019) and his K rate remained where it was back in 2019.
His BABIP of 0.326 indicates that there’s no reprieve on the horizon for Messinger; his poor batting average is a product of his inability to hit the ball hard for hits. Despite being a junior, there aren’t many positive in Messinger’s profiles which bodes poorly for his future opportunities in baseball. It’s a pretty unremarkable profile and there’s not much to say about Messinger.
Zach Hanna is another Kansas hitter who just doesn’t really do anything notable, good or bad. Walks infrequently and strikes out a lot. That’s a bad combination. He doesn’t hit for power and doesn’t get hits. The BABIP of 0.286 is really low, but of course, so is his batting average of 0.213. There aren’t any positive signs in Hanna’s profile and as a Redshirt Senior, his season and likely his career ended on a downswing unless he returns for an extra year given the NCAA’s decision.