Some hitters are good at making contact. Other hitters are good at making quality contact. Being good at one usually means you aren’t good at the other.
This contact/contact quality trade-off is fundamental to hitting at the MLB level in 2020. So much so that a batter’s swing and miss tendencies explain nearly half of barrel rate (r2 of 0.47 between whiff rate and barrel/BBE). This indicates that barrel ability is largely a function of a hitter’s choice in approach – do I prioritize choking up or swinging for the fences?
Notice the dearth of dots in the upper right quadrant of the graph, the area highlighting players that are above average in both whiff and barrel rate. It’s vacant! Outside of Mike Trout, and to a lesser extent Mookie Betts and Anthony Rendon, no player is able to consistently outperform in both metrics. This anecdotal example supports the notion that most players must choose whether they prioritize contact or contact quality.
But what about the other half of barrel rate that isn’t explained by whiff rate? It’s likely that a hitter’s raw power and pitch selection ability allows them to either over- or under-perform their expected barrel rate. This phenomenon is represented visually by the distance of the dots from the trend line in the graph. The higher the dot is above the line, the better their barrel to whiff efficiency, and vice versa.
The dots above the line have disproportionately better wOBAs (redder is better) than the dots below the line. This highlights the importance of the barrel-whiff relationship in determining a hitter’s capabilities at the plate.
Establishing a Barrel/Whiff Statistic
There’s different ways to formulate Barrel/Whiff Ratio. One option would be to divide a player’s Barrel/BBE rate by their whiff rate. This formula would capture most of what we want to know, however, there are issues with comparing rate stats that use different denominators (batted balls v. swings).
A better option would be to divide a player’s total barrel count by their total whiff count (totals barrels / total whiffs). Another option, suggested to me by Tom Tango, would be to divide barrel count by the sum of barrels and whiffs (barrels / barrels + whiffs). The former is an intuitive ratio that is easy to calculate on the fly, while the latter is the more elegant and technically sound way to go about things. Neither version will change the outcomes described below by much, so I will use the easier to calculate (total barrels / total whiffs) formula as my proxy for Barrel/Whiff Ratio.
For some context, league average Barrel/Whiff ratio is 0.11, or one barrel for every ~10 whiffs. A very good hitter, like Freddie Freeman or Anthony Rizzo, would post a Barrel/Whiff ratio in the 0.15+ range (1 for 6). And then there’s Mike Trout, who paced the league from 2017-19 with a god-like 0.33 (1 for 3)!
Relationship with Offensive Production
Barrel/Whiff Ratio is the most descriptive statistic of long-term offensive performance that I’ve come across. To get a sense of its power, take a look at the graph below that compares Barrel/Whiff Ratio to wOBA for hitters with at least 1,000 PA from 2017-19.
The resulting r2 is 0.57. This means that 57% of the variation in player wOBAs is determined by Barrel/Whiff Ratio. Let’s see how that stacks up against some other statistics:
Barrel/Whiff has a much stronger relationship with long-run wOBA than other Statcast-related indicators like Barrel/PA (0.38 r2) and exit velocity (0.36). It also has nearly three times the explanatory value of BB/K (0.21). That’s some serious explanatory horse power.
Understanding the value of Barrel/Whiff
I was confused by these results at first. Why is Barrel/Whiff better than Barrel/PA at explaining offensive production? After all, Barrel/PA directly measures the outcome of a plate appearance. Shouldn’t that be what’s most relevant in terms of offense?
The issue is that Barrel/PA only really explains barrels. It offers little other substantive information about the hitter. Barrel/Whiff Ratio, on the other hand, is touching upon something more: the quality of their overall approach.
This is evident when comparing their respective relationships with plate discipline, proxied by BB/K ratio.
Barrel/PA has no relationship with BB/K ratio, yet Barrel/Whiff is at 0.21 r2. Why does Barrel/Whiff have a relationship with a plate discipline metric like BB/K?
This likely goes back to the pitch selection skills discussed earlier. In order to achieve a surplus of barrels relative to whiffs, hitters probably have to make good swing decisions at the plate. These better swing decisions translate into more barrels and fewer whiffs, but also more walks and fewer strikeouts!
Barrel/Whiff Ratio is measuring more than just barrels and whiffs. It’s offering a view into the quality of a hitter’s process at the plate, which is why it’s such a good descriptor of offensive production.
Peruse the below Barrel/Whiff Ratio 2017-19 leaderboard to see how your favorite players shake out. Note that the color of the bars indicate the hitter’s wOBA, with redder being better.
Trout, Mookie Betts, and Anthony Rendon are in a class amongst themselves, each locating in the 0.29 – 0.33 range. For comparison, fourth place Justin Turner is at 0.22.
You’ll notice that Turner, Jose Ramirez, Michael Brantley, Francisco Lindor, and Alex Bregman – players with mediocre Barrels/BBE and Barrels/PA rates – have their offensive capabilities treated more fairly by Barrel/Whiff.
Justin Smoak and Manny Machado, both in the top 15 of Barrel/Whiff Ratio, have under-performed with decent but unspectacular wOBAs in the ~.350 range. Are these players good rebound candidates for 2020 or is there something else holding back their offensive production? Gary Sanchez, Jose Martinez, Salvador Perez, and Jose Abreu are other players whose production is lagging what their Barrel/Whiff ratios would project.
Conversely, Kris Bryant owns a .382 wOBA over the last three years but has a decidedly average Barrel/Whiff of 0.12. Brandon Nimmo has put together a .362 wOBA with a 0.08 Barrel/Whiff that trails the likes of Martin Maldonado and Chris Taylor. Are Bryant and Nimmo regression candidates?
Concluding Remarks and Further Research
I hope that this post gave you enough data to understand Barrel/Whiff Ratio and made you excited enough about its capabilities to start using it for yourself.
Posts in the coming weeks will focus on providing analysts with Barrel/Whiff Ratio annual leaderboards, year over year changes, and more detailed ways to identify breakout or regression candidates.
I will also focus on exploring the predictive capabilities of Barrel/Whiff Ratio (how it affects offensive performance in future years rather than just the current ones). I still need to do more work on this, but the early signs are positive, with Barrel/Whiff Ratio in Year 1 predicting wOBA in Year 2 better than Barrel/PA, Barrel/BBE, and Exit Velocity.