Tuesday, March 5, 2024
AnalysisChicago CubsMLBNational LeagueNL Central

Zero to Juan Soto: The Tremendous Transformation of Jason Heyward

Photo Credit: ESPN

I’m not going to sugarcoat it: it has been a rough few years for Jason Heyward. After a hungry 97-win Chicago Cubs team gave him 8/$184M for the elite play at which he showed could happen, he faltered. The value they gave to that money just never came back. It was a puzzling change in performance for Cubs fans and an almost painfully gleeful one for Cubs rivals.

To put those words into numbers, in the first half of Heyward’s contract he had a .252/.327/.383 slash line, 90 wRC+, .309 wOBA (.322 xwOBA), and 6.0 fWAR in 2151 PA. His defense was a primary benefactor for those wins above replacement. His 27.2 UZR, which goes into fWAR, and 42 DRS are both very impressive. They helped to give Heyward positive value amidst the offensive regression. However, teams pay for your value to over-perform your contract in free agency. And that just didn’t happen in this case.

So, let’s picture the timeline entering 2020. The Cubs struggled to improve their roster due to payroll constraints, have four major talents on the final years of their salaries, and, to add insult to injury, the devastating COVID-19 pandemic brings the season down to just 60 games. So, what did Heyward do? He resurged in a way the Cubs were only imagining.

It’s no understatement to say Heyward had a fantastic season. He had a .265/.392/.456 slash line, 130 wRC+, .368 wOBA (.371 xwOBA), and 1.8 fWAR in 181 PA. At that pace, he’d have had the highest fWAR in a single season since 2015 and the second-highest of his career. So, the question has to be how he got there. After all, in his small 50 game sample, he already surpassed his prior fWAR/150 games as a Cub.


Ch. 1: Hit Tool

A primary benefactor in Heyward’s resurgence was his quality of contact. To measure this, I’ll be using xwOBAcon. This stat essentially uses a player’s exit velocity and launch angle to measure what their xwOBA should be on batted ball events. In 2020, Heyward’s was a modest .404. Not only was this an improvement from his prior .360, but it also marked his first season above the league-average mark.

Baseball Savant, being as friendly to the inquisitive mind as it is, has six different batted ball classifications that go into measuring xwOBAcon. There’re three good ones: Barrel%, Solid%, and Flares/Burners% and three bad ones: Weak%, Under%, and Topped%. The table below measures Heyward’s separated by 2019 and 2020.

YearPoorly/Weak%Poorly/Topped%Poorly/Under%Flares/Burners%Solid%Barrel%
20192.7%35.7%23.6%25.4%5.9%5.7%
20203.6%33.0%15.0%35.7%8.0%4.5%

While there’s clear improvement across the board for Heyward, none sticks out as much as Flares/Burners%. These are a bit more difficult to classify, as there’re two different types of batted ball events that go into it. A flare is hit at a higher angle with a lower exit velocity while a burner is the opposite. The stat itself performs very well. In 2020, the league average wOBAcon and xwOBAcon on it were .616 and .595, respectively.

Heyward’s improvement on the stat was no joke. Out of every player with a minimum of 100 batted ball events in 2020, his Flares/Burners% ranked 2nd behind José Iglesias (another breakout star in 2020). The league-average on the stat this year was 24.2%. That would mean Heyward’s is almost 50% above league-average, a very impressive feat. A feat that deserves a swim in the deep end.

When looking into why Heyward improved so much in this stat, it’s hard to find variables of correlation. Flares and burners are harder to control than barrels and solid contact. But, me being me, the question of controlling something that’s prone to variance and gives hitters with weaker power an edge over the top of the league really piqued my interest.

My intrigue and desire for answers led me around a lot of Baseball Savant profiles from similar hitters to Heyward. Eventually, one Sunday morning, I came upon the radial chart for White Sox shortstop Tim Anderson in 2019, who had both an offensive breakout and Flares/Burners% of 30.2 that season.

A radial chart measures the exit velocity and launch angle of a player’s batted ball events. This chart shows only batted ball events from Anderson’s that were flares and burners.

Upon looking at this radial chart, I noticed that a grand majority of his flares and burners were singles while doubles and outs comprised the maximums and minimums in terms of wOBAcon contribution. This makes sense, as the league-average xwOBAcon for them is somewhat comparable to the league-average for singles (.521). Being that they’re are mostly comprised of smaller hits, my mind connected the dots between this and Alex Chamberlain‘s study into hit tool. His findings focused on one primary variable: the standard deviation of launch angle (stdevLA).

The standard deviation of launch angle is, essentially, the distribution of a player’s launch angles. The higher the number, the more launch angle variance and vice versa. And, wouldn’t you know it, Flares/Burners% and stdevLA are connected! The chart below models the correlation between the two stats in 2019.

The coefficient of determination (r2) does show a negative correlation. What this means is that while stdev(LA) decreases Flares/Burners% increases. This conclusion does make sense as well. And, unsurprisingly, Heyward’s stdev(LA) saw a tremendous increase. In 2019, his stdev(LA) was 25.4, ranking 74th out of 225 players (which gives a strong reason for sustainable improvement). However, in 2020, his stdev(LA) was 23.9, which ranked 8th out of 194 players. This is also keeping in mind that the league-average jumped down from 2019 to 2020 by about 1.7. The graph below visualizes Heyward’s fantastic launch angle distribution in 2020.

This distribution would explain Heyward’s Sweet Spot% as well, which measures the percentage of a player’s batted ball events that fall between an eight-to-32 degree launch angle. Not only did Heyward see an improvement from 31.8 to 42.0, but he had the 9th highest in baseball out of every player with at least 100 batted ball events. His Sweet Spot% was also the best of his career by far, with his previous best being the aforementioned 31.8.

Now, of course, how effective Heyward’s improvements are in this regard depends on his average launch angle. Heyward’s stdev(LA) represents the range of his launch angles depending on the number of distributions from the mean. So, two distributions from an average of 10 with a standard deviation of 20 would result in a range of -30 to 50. Heyward’s average launch angle this season was 11.3. This is spectacular for his Flares/Burners%, as the average launch angle on them was almost exactly the same at 11.5. Essentially, an average launch angle indistinguishable from the stat plus a distribution of launch angles close to that average hold up a sign the size of Mount Everest saying that this player will have a great Flares/Burners%.


Ch. 2: Poor Contact

Heyward’s amazing improvement in his Flares/Burners% brought improvements in poorer contact as well, also shown in his aforementioned quality of contact graph. When combining all three types of poor contact (weak, under, and topped) out of every batted ball event for a player, Heyward also saw great improvement. For this “Poor%,” Heyward went from 62.1 to 51.8, another incredible improvement that ranked him 15th in the league in 2020.

Heyward’s stdev(LA) also has some connections to this incredible improvement. The graph below maps the correlation between stdev(LA) and a player’s poor% in 2019.

To lay it out again, because Heyward had such a tight distribution of launch angles in 2019, he had fewer outliers and thus less poor contact. It should be noted that the correlation is *slightly* higher when only looking at Under/Topped% since they only involve launch angles whereas weak contact has different exit velocities than the two others.

Now, I must confess, combining all three is a bit misleading when truly analyzing this aspect of his improvement. Each type of contact has a different severity, so looking at all three individually is a more accurate measure of someone’s quality of contact profile. This makes sense because each classification has different launch angles and exit velocities that go with them. For reference, the graph below maps each type of quality of contact with their league average wOBAcon and xwOBAcon in 2019.

LeaguePoorly/Weak%Poorly/Topped%Poorly/Under%Flares/Burners%Solid%Barrel%
wOBAcon.131.161.089.614.6491.408
xwOBAcon.163.177.092.619.6621.397

As the graph shows, Poorly/Under% easily has the worst impact on a player’s quality of contact profile. Funny enough, Heyward saw a severe decline in this type of quality of contact, going from 23.6 to 15.0. While he did see changes in his poorly/topped% and poorly/weak%, none were close to as beneficial as his improvement there.


Ch. 3: Plate Discipline

Heyward’s xwOBAcon improvement was very impressive, I don’t think there’s any doubt to that. For a player to go from .360 to .404 in one season requires some head-turning and difficult improvement. However, when factoring in how xwOBAcon translates to xwOBA, it’s difficult to stay near your xwOBAcon. Some great hitters have done this consistently, such as Anthony Rizzo, Carlos Santana, and Justin Turner. So, what’s the key? Well, simply said, it’s their K% and BB%.

While Heyward boasted a modest 20.4 K%, one that ranked noticeably above average, his BB% is really the reason I made this a chapter. His was a breathtaking 16.6, which tied him with Joey Votto for the 8th best out of every hitter with at least 180 PA this season. His BB% has been trending up the past few years and took an impressive leap last season, but the only year that he saw one close to this level was in his rookie season back in 2010.

When looking for the “how”, I was led to FanGraphs’s plate discipline stats. Now, I’ll be honest, this is a learning experience for me. I’ve been just a bit lazy regarding my use of plate discipline stats. Anyway, FanGraphs has nine plate discipline stats and, if that wasn’t complicated enough, most of them differ based on which system you use. For this chapter and the next, I won’t be using Pitch Info’s stats. Now, each stat obviously correlates with BB% differently. After running a linear regression model between each of the stats and BB%, I found two stats to be the most correlated with it: O-Swing% and Swing%.

Before getting into some potentially heavy stat language, I feel that it’s important to note that I’ll be using the same parameters as the previous BB% ranking for any further plate discipline stats, BB%, or K% rankings. Got it? Ok, cool!

As you probably could’ve inferred, both of these stats are very similar to one another. The difference is that O-Swing% measures a player’s swings to total pitches outside of the zone compared to overall. Since Z-Swing%, which measures the same thing in the zone, has such a weak correlation to BB%, Swing% has a weaker albeit strong correlation than O-Swing%. The correlation between O-Swing% and BB% in 2019 for qualified hitters is shown below.

The strong correlation shows that the lower the O-Swing% the higher the BB%. This boded very well for Heyward in 2020, as his O-Swing% of 21.7 ranked 16th in the league. This was another career-high for him, with his previous best being, again, in his rookie season. Funny that I keep bringing up 4.6 fWAR Heyward here, huh?

Like his O-Swing%, Heyward’s Swing% was also amazing this season. His Swing% of 36.7 tied him at 9th in the league with Mike Trout. Yes, that’s the unanimous best player in baseball Mike Trout. Oh yeah, and his previous Swing% high was also in his rookie season. Who’d have guessed?


Ch. 4: Juan Soto

For those of you in this piece for the long run, I deeply apologize for going almost 2000 words without mentioning the elephant in the room. Or, in this case, the title. Juan Soto just came off his best season yet, one that drew comparisons to Ted Williams. In case you don’t know who that is, he’s the guy who could allegedly see the commissioner’s signature on the ball as it traveled towards the plate. In 2020, Soto had a .351/.490/.695 slash line, 200 wRC+, .478 wOBA (.451 xwOBA), and 2.4 fWAR in 196 PA. This not only destroyed his previous and impressive career-highs but also set the league on fire.

Like Heyward, one of Soto’s most drastic improvements were his K% and BB%. In 2020, his 14.3 K% ranked 18th while his 20.9 BB% led the league with a 180 PA minimum. Also like Heyward, Soto’s stunning developments in these stats unsurprisingly came with some very good plate discipline.

To start, I’ll call back to O-Swing% and Swing%, two of the most correlated plate discipline stats to BB%. In both stats, Soto ranked within a percent of Heyward’s, which not only is very good in comparison to the league but also gives some more shock value to Heyward’s numbers. Soto’s O-Swing% of 21.0, 0.7 lower than Heyward’s, ranked 11th in the league, and his Swing% of 36.0, also 0.7 lower than Heyward’s, ranked 4th in the league. Both of those fare better for Soto’s BB% than Heyward’s by a smidgen, but they’re both fantastic.

While Soto and Heyward are walking distance in BB%, they’re noticeably further apart in K%. What correlates the strongest to K% are the variations of FanGraphs’s contact%, which measures pitches hit into play out of total swings, and SwStr%. Unsurprisingly, Soto outperforms Heyward more in those categories, but not by very large margins. Or at least a margin as vast as their K% difference. The four stats for each are shown below.

NameO-Contact%Z-Contact%Contact%SwStr%
Soto69.788.981.96.5
Heyward65.085.678.57.9
Like the Swing% variants, “z” and “o” refer to whether they’re inside or outside the zone.

It’s easy to see why Soto had a better K% than Heyward in 2020, but these stats also give some credence to the idea that they’d be closer in K% if given more time. And hey, being plate discipline buddies with one of the best hitters in baseball has its perks.


Ch. 5: Conclusion

So, here we are, at the dawn of the 2021 Cubs season. To the chagrin of many diehard fans, it’ll be without some big names. Yu Darvish and Victor Caratini have already traveled across the country to an exciting Padres team in San Diego. Willson Contreras could be next, with rumors between the Cubs and Miami Marlins already circulating. The Cubs’s new direction reflects a desire to start anew, to build the team back to its former glory with new names.

Big changes to baseball teams are always hard to swallow. There’s always a downhearted “see you later, alligator” as the period of reminiscence, where fans look at the glory days of the roster that once was, commences. But this time of change has brought new life to the Cubs. The farm system is stacking up, especially after a hefty haul from both the Darvish-Caratini trade and the international signing period. With Jed Hoyer, the new president of baseball operations, at the helm, there’s no reason to believe that this will slow down. So, just like with Heyward, there’s an enthusiastic reason to say goodbye to once was and hello to what may be.

Steven Pappas

Hello! My name is Steven Pappas, and I'm a high school junior. I love to analyze and write about baseball data as a huge Chicago Cubs fan and lifelong follower of the sport. I use large databases such as Baseball Savant, basic coding knowledge in RStudio, and my inquisitive mindset to always scour the infinite data available. I really enjoy watching and following basketball and am a Chicago Bulls fan, actively going to their games at the United Center. I love the study of filmmaking, and it's a passion that I've begun to explore as a career opportunity. My favorite works come from the minds of Stanley Kubrick, Yorgos Lanthimos, Alejandro G. Iñárritu, the Coen brothers, and Wes Anderson. As a deft and passionate writer, I use my proficiency to create works from baseball data, for films, and my ideas in the form of short stories and little nuggets. I'm also a libertarian socialist in training and an active Greek Orthodox Christian.