University of Texas 2020 Baseball Evaluations

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 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 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 more favorable outcomes. 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 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, which can be found here. Thus, the formula for wOBA came out to this:

The formula that I used to calculate wOBA

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, , 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, allowing us to see what a player’s quality of contact is.

The last stat I want to talk about is wRC or . 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 (, 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 get started with the University of Texas. UT had a total of 5 players who qualified, most of whom were returners from 2019. However, we are going to kick this off with one of UT’s dynamic freshmen.

Faltine, a true freshman, started all 17 games at SS for the Longhorns this season and had mixed results at the plate. Overall, a 0.259/0.343/0.362 slash line isn’t *terrible*, but the low SLG number pops out, along with the low XBH %. That’s something that can be attributed to being a freshman, being younger, and not having as much time in a collegiate weight room; it’s not entirely fair to expect him to hit for power immediately. It would’ve been nice to see a higher XBH % as a foundation to build on, but he is only a freshman.

For freshman though, one of the numbers that I think is the most important is the OBP/wOBA numbers and how often they’re getting on base because that power usually comes as they grow. Faltine was below average in both of those. His BB % of 8.7% is a few percentage points below the Big 12 average and his batting average was below average as well. I don’t think the lower average is a product of bad luck, despite the BABIP of 0.326. His low XBH % indicates that Faltine wasn’t hitting the ball super hard or far throughout the season; in fact, he hit 15 singles, 3 doubles, and 1 HR in his 69 plate appearances. With a lower quality of contact, it’s hard to imagine that Faltine just got super unlucky.

The last worrying sign for Faltine is his K % of 21.74% was one of the higher ones in the conference (3rd on the team). I like when freshmen have good BB/K numbers because that’s one thing that they have almost total control over.

While Faltine’s 2019 was not great, or even average when considered against his Big 12 peers, it’s really hard to draw conclusions about him from 69 plate appearances against non-conference competition. Any concrete conclusions on Faltine will have to wait until post-2021 when we (hopefully) get the chance to see him at the plate more.

Austin Todd’s transformation from 2019 to 2020 is one of the most drastic in the Big 12. But how much of it is real? Or sustainable?

He went from an 0.256 batting average up to 0.375 in 2020, a huge 0.119 increase. His slugging % increased by a similar amount, both of which are phenomenal signs on the surface for Todd. However, the underlying numbers are worrisome, notably the BABIP of 0.500 which was the 3rd highest in the conference. That simply unsustainable, especially since it’s so out of line with Todd’s 2019 season. It does appear that he did a better job of getting extra-base hits because that XBH % did increase about a full percentage point from 2019 to 2020. But it’s hard to judge whether that’s truly because Todd is getting better contact or if it’s a symptom of luck on batted balls, which is where the small sample of 79 plate appearances comes back to haunt us.

The most disconcerting sign in Todd’s 2020 profile is the drastic shifts in BB and K rate from 2019 to 2020. He walked at an average rate in 2019 and struck out infrequently a pretty good combination. Yet, in 2020, his BB % plummeted to 6.33% and his K % skyrocketed up to 24.05%. I think that this change represents a change in aggressiveness and an attempt to hit the ball harder and in the air more in 2020, two things that his lower XBH and HR rates indicated were an issue in 2019.

Over the course of 200 more plate appearances, I think that the BB rate would have regressed closer back to those 2019 levels as Todd refined a more aggressive approach. The K rate likely would’ve held even as the quality of pitcher faced increased with the start of Big 12 play.

Todd’s short 2020 campaign that portrayed him as one of the best hitters in the Big 12, ranking 18th in wRC, was primarily built off of batted ball luck rather than consistent XBH power. The slight power surge looks sustainable, but the average jump is inflated by his 0.500 BABIP.

Duke Ellis took a notable jump for Texas in 2020 by building upon his already established strengths. His 2019 BB % of 18.6% was one of the best and it held steady in 2020 at 16.9%. What sparked Ellis’ improvement though was a K % that dropped from 24.8% to 7.04%, a 17.76% drop. Cutting down that K rate means that Ellis put the ball in play more than ever in 2020, resulting in his above-average wOBA of 0.368, despite a slightly below average BABIP.

Ellis’ lower BABIP of 0.327 is something to be expected given the quality of contact that he has. His SLG of 0.377 and ISO of 0.075 indicate that he’s not a power hitter, as down his XBH % of 4.23%, which is marginally better than his 2019 rate, but still far below average.

Ellis thrives as an on-base guy who can run rather than by trying to be someone who hits the ball over the fence and that’s okay because he plays to his strengths and is an above-average offensive player with a wRC of 11.78.

From 2019 to 2020, Zubia’s biggest change was transforming more of his batted ball opportunities into HRs and XBHs. His increased HR rate of 17.65%, up from 12.1% and the resulting uptick in his SLG, from a below-average 0.405 to an above-average 0.492. With his 0.326 BABIP, it doesn’t look like Zubia benefited from any extra luck and that the increases in batting power are increases in talent level.

On a per plate appearance basis, Zubia performed at an average rate and his wRC snuck above the median due to his higher number of plate appearances. The thing that kept him from thriving in run production is the below-average wOBA of 0.347 because the two are directly related. But what dragged his wOBA and production down was his drop in BB %, from 18.3% of plate appearances in 2019 down to 9.59% in 2020. In addition to the decreased walk rate was an increased K rate by about 4%.

That’s not a big deal considering the power surge and the fact that he’s putting more balls in play, but the walk rate dropping is concerning. It was one of his strong points in 2019 and something that I hoped he could leverage for higher quality at-bats in 2020. But the increased power and contact quality are very positive takeaways from Zubia’s 2020 campaign.

Kennedy was named to the Preseason All-Big 12 team heading into the 2020 season as he came off of a stellar freshman year for the Longhorns. He did a phenomenal job of getting hits and getting on base, even if there wasn’t much power production.

In 2020, he had a pretty similar season to his 2019 season, posting nearly identical OBP numbers. A slight increase in BB % helped compensate for some poor batted ball luck, as shown by the below-average BABIP of 0.327 that led to his below-average wOBA of 0.326. Getting unlucky on batted balls hindered his ability to produce early on in the season and dragged the overall weight of his offensive production with a wRC of 9.23, below average despite his 71 plate appearances.

His season was streaky, which contributed to the odd combination of results, one of the problems that arises from only using a sample size of 71 plate appearances. He started the season 5–26, hitting just 0.192 over his first 8 games. But to close the season, Kennedy hit 12–33 in his last nine games, a 0.363 clip, showing that his slow start that gets magnified in this small sample size, was probably more due to luck than a magical disappearance of skill. Kennedy remains one of the best contact guys in the Big 12 and got hurt by early bad luck and small sample size in 2020.

Sophomore studying Sport Management and Economics at the University of Texas. Writing about Baseball from an analytical and scouting perspective

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