In last week’s write-up we took a look at the offensive side of baseball and the continued evolution of batting metrics, and for this week’s write-up I originally was going to do a similarly-structured write-up with the pitching side of sabermetrics. However, after giving it a second thought I thought I’d switch it up and use this topic as an opportunity to just demonstrate how modern day pitching metrics can be utilized when evaluating a pitcher and his development while also using it as an excuse to talk about my favorite pitcher in all of baseball, Kyle Freeland.
Kyle Freeland is an anomaly that I could probably write an entire book about, and he has only played two full seasons of major league ball. In 2017, Kyle Freeland put together an above average season for a rookie starting pitcher. In the following season, Kyle Freeland took a monstrous leap and became one of the best pitchers in the National League, finishing fourth in NL Cy Young voting. He markedly improved in basically every statistical category fathomable as you can see below.
NOTE: The “minus” metrics for pitching are similar to the “plus” metrics for batting which we covered in the previous write-up, in that they are park and league adjusted and are scaled in a way that 100 is league average. However, the inverse is true with the “minus” stats in that each point below 100 represents the percent better a pitcher is than the league average, and each point above 100 represents the percent worse a pitcher is than the league average.
But it isn’t Kyle Freeland’s incredible development as a pitcher that is what is most fascinating about him. What makes Kyle Freeland so fascinating is that despite having the misfortune of pitching in the extremely hitter-friendly Coors Field for half of his games, his home/away splits show that he is actually a much better pitcher at Coors.
The result of these astonishing splits is my favorite betting “trend” ever: In Kyle Freeland’s starts in his first two seasons:
- The under went 41-16 for +23.4 units (37% ROI)
- The under in home games went 25-5 for +19.5 units (59% ROI)
- The F5 under in home games went 25-4-1 for +20.6 units (62% ROI)
Like most betting “trends”, the Kyle Freeland under “trend” is not some magical force that leads to guaranteed profits over time for the rest of eternity. Instead, it is merely a reflection of a previously uncorrected and/or inefficient pricing pattern or strategy in the betting market. To help illustrate this, lets take a look at some of the underlying elements that may have led to this incredibly profitable trend with Kyle Freeland’s starts.
The first thing that makes Kyle Freeland’s success in his first two seasons and his success at hitter-friendly Coors Field during that time so astounding is a 25 year old performance trend of pitchers drafted by the Rockies. As you can see in the below, not only are Rockies-drafted pitchers dead last in WARP accrued with their drafted team, they are the only team with a negative figure in that regard. The forward-projecting sentiment that comes as a result of this historical performance can explain a part of the undervaluing and mispricing of Kyle Freeland’s starts, especially the starts from his 2017 rookie season.
Part of Freeland’s comfort at Coors can be attributed to the fact that the ace was born and raised in Denver, allowing him to be acclimated essentially since birth to the effects of the altitude. As a result, Kyle Freeland experiences a Freaky Friday-like home/road phenomenon in which the altitude and conditions of Coors is his “comfort zone” while pitching elsewhere is what pitching at Coors is like for the the rest of the league. Nevertheless, whatever adjustments betting markets made following the 2017 season to better capture Freeland’s comfort at home was never going to be enough to capture his development as a pitcher heading into and during the 2018 season.
The biggest change for Kyle Freeland in 2018 was his pitch selection. A large reason for this shift is directly tied to the development of sabermetrics and its ability over the years to identify which pitches work better and worse at Coors due to the conditions. In summary for the unaware, curveballs and sinkers have a measurably sharp drop-off in performance whereas sliders and cutters are proposed as better alternatives. As you can see in the above, Freeland opted to cut his sinker usage by over half in 2018 and reallocated that volume to the rest of his more Coors-friendly arsenal. The change was certainly deliberate as Freeland himself noted, “Last year we discovered after the first half that guys were looking for sinkers down and away, because they knew I would be throwing them, and I started getting hurt throwing those pitches”. Freeland also worked on his command to punch his fastballs up and in and especially against right-handed batters, as you can see in the below with 2017 on the left and 2018 on the right and with both charts being from the catcher’s perspective.
The end goal of these shifts in Kyle Freeland’s game was to cause as much soft contact as possible. As Freeland said, “Getting in on their hands is going to induce a lot of weak contact, especially if they aren’t able to get that barrel around and then once you do that, it opens up options to where you can throw your changeup down and away, and it comes out of your hand looking like a fastball, and then the next thing they know it’s off the end of their bat for a weak ground ball or a weak fly ball”. This concerted effort to induce soft contact not only proved to be fruitful for Freeland (who finished 18th in groundball percentage), but it seemed to be an effort pushed by the Rockies pitching staff that helped Jon Gray (10th) and German Marquez (12th) achieve similar results in 2018.
But what should we expect from Kyle Freeland in 2019? The vast majority of projections I’ve seen (PECOTA, FanGraphs, etc.) seem to suggest that Kyle Freeland’s 2019 season will be more similar to his 2017 season than his 2018 season. Considering that generating weak contact does not seem to be a pitcher skill that typically translates year over year, I can see why those projections are positioning Kyle Freeland as a major regression candidate. And given the historical performance of some of those projection systems, Freeland probably is very likely to show significant regression in 2019.
But I don’t really care, because Kyle Freeland fascinates me endlessly and I’ll root for him (and those unders) until we both fail.