Last week, I introduced Long Fly Ball Rate and how it could be useful to evaluate the power output of hitters. To summarize, Long Fly Balls are generally a good indicator of home runs, which makes sense since balls that are hit further have a better chance of clearing the fence. But perhaps more importantly, the leaders in Long Fly Ball Rate not only have better-expected stats, such as expected slugging but also generally get better results in terms of actual slugging. Compared to hitters whose home runs are mostly the result of pulled fly balls, their expected and actual sluggings tend to be much lower than those hitters who hit more Long Fly Balls. It’s not that pulling home runs is bad, it’s just that a hitter needs to be able to consistently do that to put up strong home run totals, and maybe aren’t the best indicator of solid contact.
Here in part two of the analysis, we’re going to take a look at some hitters who, based on Long Fly Balls, perhaps overperformed their power totals from a season ago and may be in for a power decline as well as some hitters who despite having a high rate of Long Fly Balls, didn’t hit as many home runs as would be expected. Before we jump into it, here is a link to the full leaderboard for your viewing pleasure.
Alright then, let’s get to it. Starting with the overperformers.
Long Fly Ball Rate: The Overperformers
To start off in identifying overperformers, I first looked for the hitters with at least 300 plate appearances that hit at least 15 home runs in 2019 but had a Long Fly Ball Rate that was less than the 21.5% league average. That returned me a list of 55 hitters, ranging from stars such as Alex Bregman, Ozzie Albies, and Manny Machado to others such as Orlando Arcia, Freddy Galvis, and Kevin Pillar, so there’s a good mix of hitters who were extremely solid a year ago, and some lesser hitters as well. I’m calling these 55 hitters “overperformers” just because they match these criteria, here’s a link to the full group of 55, but I want to note that I don’t necessarily believe that Max Kepler and Ketel Marte are “overperformers”, and it should be noted that their Long Fly Ball Rate is only just a touch below league average. With that cleared up, we can sort these hitters by the lowest Long Fly Ball Rates, and the top 10 looks like this:
| Player | Long Fly Balls | Total Fly Balls | Long Fly Ball % | Total HR |
|---|---|---|---|---|
| Adam Eaton | 10 | 110 | 9.09% | 15 |
| Jesse Winker | 7 | 55 | 12.73% | 16 |
| Jason Kipnis | 14 | 102 | 13.73% | 17 |
| Brett Gardner | 11 | 80 | 13.75% | 28 |
| Whit Merrifield | 18 | 129 | 13.95% | 16 |
| Corey Seager | 16 | 111 | 14.41% | 19 |
| Jurickson Profar | 13 | 90 | 14.44% | 20 |
| Orlando Arcia | 12 | 81 | 14.81% | 15 |
| Scott Kingery | 12 | 79 | 15.19% | 19 |
| Kyle Seager | 16 | 101 | 15.84% | 23 |
It doesn’t shock me to see Brett Gardner here; as I mentioned in Part 1, Gardner set career highs in nearly every power-related category in 2019, but it was based on a combination of him pulling the ball more than ever, playing in an extremely favorable home park, and a juiced baseball, not by him making more hard contact, and that shows up in his .372 xSLG.
Among the other fantasy-relevant names, Corey Seager’s name popping up here definitely surprised me. 2019 was of course his first season post-Tommy John surgery, so it makes sense for some of his power to take a while to return to his pre-surgery levels. He got off to a slow start in 2019, and his .332 xwOBA and .464 xSLG are not anything too flashy, but the power did seem to come back later in the year; after a down month of July, he posted a .277 isolated power mark in August and September. He also didn’t pull many of his home runs, at a 42% pulled home run rate, and he’s not hitting many more home runs than his Long Fly Ball totals would suggest that he deserves. I wouldn’t be too particularly worried about Corey right now. If the power still isn’t there this season, then I would be concerned, but I still want to draft him basically anywhere I can right now. As for the rest of this group, you aren’t drafting Whit Merrifield and Adam Eaton for their power, so I wouldn’t be too worried about them showing up here. Jesse Winker will always be a player I’m interested in, but he’s also not someone who is expected to give super big power numbers—still, it doesn’t look great to see him here with nine fewer Long Fly Balls than total home runs. Part of that I’m sure is due to his home ballpark, but unlike Gardner, he doesn’t pull his home runs, with just a 12.5% pulled home run rate in 2019. That was the lowest among hitters with 300 plate appearances, so he isn’t even taking much advantage of some potential cheapies down the line. The slugging could take a bit of a hit, down from the .473 mark from a year ago, but he should continue to hit for a good batting average and get on base plenty enough to keep himself relevant, as long as he gets the playing time. Elsewhere, the rest of these hitters aren’t hitters that I would want to draft, save for deep leagues, where the pickings would already be slim.
Another way that we can evaluate these 55 hitters is to take a look at how their Long Fly Balls compare to their overall home run total. After all, Long Fly Balls are supposed to be a good indicator of home runs, as I showed in Part 1. If we take each hitter’s total home runs and subtract them from their Long Fly Balls, we should, theoretically, come up with a list of hitters who benefitted most in their home run count despite not hitting the amount of Long Fly Balls that their home run totals suggest they should have. Doing this exercise gives us quite a few more interesting names. Here are the top-ten biggest differences in total home runs to Long Fly Balls:
| Player | Long Fly Balls | Total Fly Balls | Long Fly Ball % | Total HR | HR – Long Fly Balls |
|---|---|---|---|---|---|
| Brett Gardner | 11 | 80 | 13.75% | 28 | 17 |
| Daniel Vogelbach | 15 | 92 | 16.30% | 30 | 15 |
| Alex Bregman | 26 | 143 | 18.18% | 41 | 15 |
| Manny Machado | 22 | 119 | 18.49% | 32 | 10 |
| Yuli Gurriel | 22 | 108 | 20.37% | 31 | 9 |
| Jesse Winker | 7 | 55 | 12.73% | 16 | 9 |
| Max Kepler | 27 | 128 | 21.09% | 36 | 9 |
| J.T. Realmuto | 17 | 101 | 16.83% | 25 | 8 |
| Ketel Marte | 24 | 115 | 20.87% | 32 | 8 |
| Jurickson Profar | 13 | 90 | 14.44% | 20 | 7 |
Again we see Gardner and Winker, but there are a lot more interesting names here than in the previous table. Kepler and Marte show up here as well, but I’m not sure they necessarily belong. Remember my disclaimer earlier in the section. Yes, they are technically considered “overperformers” just based on the criteria of this particular query. Their Long Fly Ball rates are just a touch below the 21.5% league average, but they also pull a lot of home runs, too. Kepler pulled 81% of his home runs last season, and Marte did so at a 78% clip. While those are both high numbers, Kepler is already a pretty extreme pull hitter, so he should continue to maintain that profile in the near future. Marte isn’t as much of an extreme pull hitter, but his overall power numbers are supported by xSLG at a .521 mark, which is down from his .592 actual one but his breakout season was more due to improvements elsewhere, and the extra home runs came along with it. Even if his home run totals drop off, he should still be an extremely solid hitter and not one that I would have much concern over.
The more intriguing names to me from this group are Bregman and Machado. Let’s start with Machado. His first season in San Diego is likely considered a disappointment, although he still hit 32 home runs. Our fears of how he would perform at home in Petco Park were realized with a dreadful .219/.297/.406 slash line at his home park, but he was more Machado-like on the road. The obvious answer is that his home park just really impacted his power output. It’s the most likely answer, but is that actually the case? It doesn’t appear so, not by Long Fly Balls anyway:
| Split | GP | PA | Long Fly Balls | Fly Balls | Long Fly Ball % | HR |
|---|---|---|---|---|---|---|
| Home | 78 | 317 | 11 | 60 | 18.33% | 15 |
| Road | 78 | 344 | 11 | 59 | 18.64% | 17 |
In identical games played at home and on the road, and nearly identical plate appearances, Machado had the same exact number of Long Fly Balls with again, nearly identical fly ball totals, which leads to essentially the same Long Fly Ball rate. It doesn’t appear that his home struggles were caused entirely by the ballpark, at least not by this metric. It might require a deeper analysis, but I believe that the likely reason for Machado’s down 2019 season has more to do with him making less quality contact, with him setting new-or-close-to career lows in nearly every Statcast hitting metric. I hate to even say this and put all of the focus onto the juiced ball, but it certainly is possible that the juiced ball is the reason why Machado reached 30 home runs in 2019 in the first place. I would want to take a deeper look at this before I come to that conclusion, but by Long Fly Balls, it appears that Machado belongs in the overperformers group, at least his 2019 does. It’ll be interesting to see what he does in his second season in San Diego.
Next up: Bregman. If you recall in Part 1, I discussed Bregman for a bit before getting into the full details of Long Fly Balls. Bregman has sort of been the inspiration for my “obsession” with Long Fly Balls and slugging during this offseason because his Statcast metrics don’t exactly paint him to be the type of hitter that he was in 2019, so I find it very interesting to see him tied for second in the biggest difference between total home runs and Long Fly Balls. Only Gardner had a bigger difference in xSLG compared to actual slugging than Bregman did with the .121 difference in his .592 actual to his .471 expected. Not that .471 is bad, but .592 is a mark that was tied for the sixth-best in baseball in 2019, and .471 is more in line with what Brian Goodwin did last season. Still good, but no longer looks as great. For a refresher, here is the exact same table from Part 1, which shows a few of Bregman’s Statcast metrics:
| AVG EV | Hard-Hit% | Barrel/BBE% | Sweet Spot% | xSLG | |
|---|---|---|---|---|---|
| 89.3 | 37.5 | 5.4 | 36.5 | 0.471 | |
| Rank (out of 273) | 121 | 159 | 205 | 89 | 97 |
Again, these don’t exactly look the numbers of a hitter who finished as the runner-up for American League Most Valuable Player. So, how does a hitter put up numbers as Bregman did in 2019, despite regular Statcast metrics? Mostly a combination of pulling the ball, home ballpark, and a juiced baseball that benefits all hitters (I’ll leave you to speculate over buzzers and other contraptions). Not that this is a bad thing, because it’s not. If a hitter can repeat this, they should continue to shatter their Statcast metrics (it’s probably not a coincidence that Yuli Gurriel is also in this group). Let’s quantify this a little. We know that Bregman’s home park is a great one for hitters, which has been shown from the outstanding research done by fellow Pitcher List-er Dan Richards in his own two-part look into park factors, that I definitely recommend checking out. Dan’s work shows that Minute Maid Park is the second-most friendly park to right-handed hitters (which both Bregman and Gurriel are) so it makes sense for Astros righties to do better from pulling the ball to left field, which Bregman did plenty of in 2019:
| Player | Pulled Fly Balls | Total Fly Balls | Pulled Fly Ball% |
|---|---|---|---|
| Kurt Suzuki | 37 | 71 | 52.11% |
| Hunter Renfroe | 47 | 96 | 48.96% |
| Alex Bregman | 59 | 143 | 41.26% |
| Josh Phegley | 29 | 72 | 40.28% |
| Edwin Encarnacion | 41 | 99 | 41.41% |
| Mitch Garver | 27 | 80 | 33.75% |
| Miguel Sano | 32 | 72 | 44.44% |
| Paul DeJong | 48 | 123 | 39.02% |
| Renato Nunez | 43 | 112 | 38.39% |
| Nolan Arenado | 47 | 132 | 35.61% |
Looking just at the right-handed pulled fly ball leaders, Bregman clocks in at the third-highest rate (Gurriel is 14th), so Bregman clearly knows that he should be taking advantage of Minute Maid Park’s dimensions and pull the ball. Looking at not just right-handed hitters but now all hitters, Bregman is still towards the top, but dropping now to seventh in terms of pulled fly-ball rate. In terms of results on pulled fly balls, Bregman slugged 2.123 on those balls, but had an expected mark of just .943, the ninth-largest difference among all hitters. This shows me that Bregman isn’t exactly making the best contact, but is able to take advantage of an extreme offensive environment to put up elite results. If Bregman were to all of a sudden stop pulling fly balls at an extremely high rate, I would expect his power output to drop. I don’t foresee this happening anytime soon, and Bregman should still be a top producer, but it is something to keep in mind and this should explain the big differences between his actual results and his Statcast metrics. The same goes for Gurriel, who if you remember had just a 109 wRC+ in the first half of 2019 before exploding in the second half, and is ten years older than Bregman, and potentially more likely to see his results turn negative quicker than Bregman.
This is just looking at total home runs compared to Long Fly Balls, but if we factored in Pulled Home Run rate into the equation, we would also get some more interesting names. For instance, Jose Ramirez and Jeff McNeil both pulled 91% of their home runs and had below-average Long Fly Ball rates, so a decline in home runs could be in store in they don’t pull as many home runs in the future. Ditto for Didi Gregorious and Eduardo Escobar—two hitters who are on the wrong side of 30, and could see their performances decline. Generally, the hitters with the highest Pulled Home Run rates and low Long Fly Ball rates aren’t hitters with a ton of home runs, with totals in the low to mid-20s range. This makes sense as they aren’t hitting enough Long Fly Balls, which generate a good number of home runs, and they also generally don’t have an attractive average fly ball distance, which suppresses their home run per fly ball rate. Overall though, it looks like hitters who overperformed their Long Fly Ball rates need to be able to consistently pull fly balls or play in an environment that is more hitter-friendly to continue to put up strong home run totals.
Finally, we’re off to the underperformers.
Generally speaking, there aren’t many names in this group that are lesser-known. I figure that there are two ways of looking for underperformers by Long Fly Ball rate. The first is to look at hitters who hit more Long Fly Balls than total home runs, not unlike what we did to find the Bregman group of overperformers, and the second is to factor in home run per fly ball rate. I find the results using the second method a bit more interesting, as hitters in that group all have above-average Long Fly Ball rates, but the home runs have yet to show up as much as expected, which makes them more exciting to me in terms of identifying potential breakout candidates. Let’s first start by looking at some hitters who hit more Long Fly Balls than total home runs, and who are already pretty decent at hitting home runs. Taking a look at the top-ten we get the following hitters:
| Player | Long Fly Balls | Total Fly Balls | Long Fly Ball % | Pulled HR | Total HR | Pulled HR % | Total HR – Long Fly Balls | HR/FB% | AVG FB Distance |
|---|---|---|---|---|---|---|---|---|---|
| Charlie Blackmon | 38 | 129 | 29.46% | 22 | 32 | 68.75% | -6 | 24.81% | 341 |
| Avisail Garcia | 26 | 77 | 33.77% | 5 | 20 | 25.00% | -6 | 25.97% | 332 |
| Howie Kendrick | 22 | 67 | 32.84% | 11 | 17 | 64.71% | -5 | 25.37% | 342 |
| Paul Goldschmidt | 38 | 129 | 29.46% | 19 | 34 | 55.88% | -4 | 26.36% | 341 |
| Mike Yastrzemski | 24 | 78 | 30.77% | 9 | 21 | 42.86% | -3 | 26.92% | 340 |
| Garrett Cooper | 18 | 46 | 39.13% | 6 | 15 | 40.00% | -3 | 32.61% | 340 |
| Ian Desmond | 23 | 73 | 31.51% | 7 | 20 | 35.00% | -3 | 27.40% | 339 |
| Matt Adams | 22 | 58 | 37.93% | 17 | 20 | 85.00% | -2 | 34.48% | 346 |
| Anthony Rendon | 36 | 141 | 25.53% | 23 | 34 | 67.65% | -2 | 24.11% | 336 |
| Yasmani Grandal | 30 | 103 | 29.13% | 18 | 28 | 64.29% | -2 | 27.18% | 332 |
There are some pretty interesting names here. Let’s start at the top with Charlie Blackmon. Blackmon, of course, plays his home games in Colorado, so his (as well as Ian Desmond’s) Long Fly Ball totals may be skewed by the thin Denver air. However, that’s not necessarily a fault against these two hitters. Based on Long Fly Balls, Blackmon and (to a lesser extent) Desmond, should be hitting more home runs. However, I will let you know that 30 out of Blackmon’s 38 Long Fly Balls occurred at home, where 22 of his home runs were hit. Colorado is always going to be a wild card, as I never have really known what to make of the home and road splits for their hitters, so I’m really sure what to make about Blackmon only having eight Long Fly Balls on the road. I do know that Blackmon’s been trending the right way in terms of exit velocity, Hard-Hit rate, and Barrels, so as long as those don’t fall off a cliff anytime soon, he should still be a solid option, and maybe he hits home runs at a better rate in the future.
Avisail Garcia is the first really intriguing name here, at least in my opinion. He was a pleasant surprise a season ago for the Rays, and now he is in Milwaukee, which is still a fine place to hit. I’m actually a pretty big fan of Garcia, and I plan on doing a deeper look at him soon in the future. What I can tell you right now about Garcia is that he sprays the ball to all fields, which includes his home runs. His pulled home run rate of 25% is the seventh-lowest in baseball, and not unlike another Long Fly Ball champ that I talked a little bit about in the first part, in Franmil Reyes. Garcia’s xSLG of .492 isn’t too far off of Reyes’ .512 actual slugging from 2019, and Garcia is also one of the best at getting Long Fly Balls, as he had the 11th-highest Long Fly Ball rate in 2019 and continues to hit the ball hard, and he cut down on the ground balls last season. I’d be interested in him just based on the xSLG and batted-ball peripherals, but to see him not only as one of the best at getting Long Fly Balls but also one of the unluckiest as it relates to his Long Fly Balls to total home runs, well now I’m more than just intrigued. The outfield situation in Milwaukee is a bit hairy, as well as how many games we actually may get in 2020, but over the course of a full 162-game season, I wouldn’t be surprised to see Garcia hit over 30 dingers.
As someone who wrote a post essentially saying that I’m buying into Mike Yastrzemski’s power output, it certainly feels good to see him here. Not only does he hit Long Fly Balls at a rate that was inside the top-25, but he also hit more of them than total home runs. With the dimensions changing in San Francisco’s park, maybe he’ll be able to squeeze out a few more home runs at a better rate. His overall average fly ball distance is extremely healthy, as are most of his other batted-ball metrics. I already liked Yastrzemski much more than most, but I like him a lot more right now.
Garrett Cooper showed up as the hitter with the third-highest Long Fly Ball rate from 2019. That’s right, Cooper is sandwiched in there with some of the best pure power hitters in the sport in Miguel Sano, Jorge Soler, and Nelson Cruz. I couldn’t believe it either. Cooper has actually been a player I’ve had an interest in, going back to his days as a Yankee in 2017 in which he performed well in a small sample. His minor league stats were always great, but were dismissed because of where he played: Colorado Springs. Still, I was interested. 2019 was his first season with at least 100 plate appearances, and he had a solid 111 wRC+ last season with 15 home runs, and he maybe could have had more. He still hits too many ground balls, at a 52.9% clip in 2019, which definitely drags him down a bit, and he won’t likely improve much on his 111 wRC+ without getting the ball off the ground. Still, when he hit fly balls in 2019, he absolutely crushed them, not just by average fly ball distance, which was right up there with some of the best hitters in baseball, but also by results. See the following table:
| SLG | xSLG | ISO | wOBA | xwOBA | |
|---|---|---|---|---|---|
| 1.477 | 1.630 | 1.023 | 0.743 | 0.816 | |
| Rank (out of 273) | 20 | 5 | 27 | 19 | 4 |
These results are no joke. These ranks are out of 273 hitters with at least 300 plate appearances in 2019, and Cooper is towards the top of all five of these leaderboards. Get the ball in the air more, Garrett! Playing time is again an issue here, as 29-year-olds on a rebuilding team aren’t exactly given the most priority, but the Marlins are a team that have actually acquired a number of veterans this offseason, so maybe they’ll play the veterans. If Cooper plays well enough, maybe he gets traded to a contender and gets everyday playing time, but your guess would be as good as mine at this point. In a full season, I think Cooper should easily eclipse 20 home runs, and could push for a lot more than that, especially if he puts the ball on the ground less often.
A little bit further down the list is another hitter who is similar to Cooper in that he has an outstanding rate of Long Fly Balls, but is a hitter that needs to get the ball off the ground to take advantage of it. That hitter is Yandy Diaz. There’s not much to say about Yandy that hasn’t been said already. We all know that there’s a lot to like about Yandy in that he hits the ball exceptionally hard, and while he did make some positive gains in his batted-ball distribution in 2019 by hitting more line drives and fly balls, he still had a ground-ball rate of 51.2%. I won’t ever stop believing that Yandy will turn that around, and looking at Long Fly Balls, there is another reason for me to like him. His 30.2% Long Fly Ball rate is inside the top-30, and like a lot of the other top hitters by Long Fly Ball rate, Diaz sprays the ball around, and his overall average fly ball distance is also strong at 341 feet. He also generally gets very good results on his fly balls, although not quite as strong as Cooper, still it’s good enough to put him right around the top 50 in the same metrics we used to evaluate Cooper above. Diaz may just never get to the point where he hits enough fly balls, although he’s not super far off the league average, he could still get there, and if he does, he may just finally reach that potential that he has.
The final way I want to evaluate some underperformers is to look at hitters who have an above-average Long Fly Ball rate, but for one reason or another, haven’t seen it show up in their home run totals. To get this group of hitters, I looked at their home run per fly ball rate, or more simply HR/FB%, and I calculated these numbers excluding infield fly balls, which is why these numbers will differ from their totals on the leaderboards from FanGraphs. The average HR/FB% of the hitters with at least 300 plate appearances in 2019 was around 24%, so I simply looked for hitters who had an above-average Long Fly Ball rate, and a below-average HR/FB%. This gave me a list of 28 hitters, and then I selected some of the more notable names, to exclude the likes of a Brandon Dixon or a Neil Walker, and threw them in a table, which is below:
| Player | Long Fly Balls | Total Fly Balls | Long Fly Ball % | Pulled HR | Total HR | Pulled HR % | Total HR – Long Fly Balls | HR/FB% | AVG FB Distance |
|---|---|---|---|---|---|---|---|---|---|
| Vladimir Guerrero Jr. | 20 | 75 | 26.67% | 6 | 15 | 40.00% | -5 | 20.00% | 329 |
| Nick Ahmed | 27 | 104 | 25.96% | 8 | 19 | 42.11% | -8 | 18.27% | 330 |
| Danny Jansen | 18 | 73 | 24.66% | 9 | 13 | 69.23% | -5 | 17.81% | 332 |
| Nicholas Castellanos | 32 | 136 | 23.53% | 12 | 27 | 44.44% | -5 | 19.85% | 334 |
| Nick Senzel | 15 | 64 | 23.44% | 7 | 12 | 58.33% | -3 | 18.75% | 327 |
| Mookie Betts | 36 | 154 | 23.38% | 19 | 29 | 65.52% | -7 | 18.83% | 330 |
These six hitters are hitters that I feel are most interesting just based on the difference between their total home runs and Long Fly Balls, and their relatively low HR/FB%. Starting at the top, I don’t feel like seeing Vladimir Guerrero Jr. at the top should be much of a surprise. He didn’t exactly set the world on fire as we expected in his rookie season, and he for some reason hit way too many ground balls which cut into his overall performance. Vlad did do a good job though of spraying the ball all around the field, and he did a good enough job at generating Long Fly Balls. He’s talked a lot about trying to fix his ground-ball issues, and only time will tell if he accomplishes that, but if he does, his fly balls have a good foundation which should translate to better numbers in the future.
Nick Ahmed was the hitter I was most happy to see make this list. His offense has been trending upwards for the past few years, and last year he set new career highs in barrels, hard-hit rate, slugging, and isolated power, and there could be more coming. In 2019, his ground-ball rate jumped nearly seven percent from where it was the season prior, so if he can get that back down close to where it was in 2018, with his ability to hit Long Fly Balls at an above-average rate, we could suddenly see him hitting a lot more home runs. Even with the jump in grounders in 2019, he was still pretty unlucky when it came to his Long Fly Balls, with a difference of eight between his total home runs and Long Fly Balls. Based on that, you could say that Ahmed should have had a mid-20’s home run total despite the high ground ball rate, and if he improves upon that, he could touch 30. Not too bad for a defense-first shortstop. It will be interesting to see what Ahmed does in the future, and I’ll be watching closely.
If you’re looking through the glut of catchers, you shouldn’t forget about Danny Jansen. Yes, he left a sour taste in the mouths of people who drafted him last year, but he was much better in the second half of the season, specifically in July and August. Would it also comfort you to know that only Mitch Garver and Gary Sanchez had a better rate of Long Fly Balls in 2019 among catchers with at least 300 plate appearances? He might not be anything special, but he may just be the post-hype catcher we need this year. Why not take a shot with the glob of late-round catchers and one of the best catchers by Long Fly Ball rate? I would do that.
I’m going to talk about Nick Castellanos and Nick Senzel together since they both play for the same team. I’m very excited to see what Castellanos can do in that launchpad of a ballpark in Cincinnatti, as it looks like he was pretty unlucky in terms of his Long Fly Balls to home runs. While I think that Comerica Park in Detroit isn’t as bad for hitters as a lot seem to believe, moving to Cincinnati certainly shouldn’t hurt Castellanos’s chances of turn his strong rate of Long Fly Balls into more home runs. As for Senzel, he isn’t the most unlucky hitter in this group, but like Castellanos, he should be able to take more of an advantage of a favorable home park. His inclusion here could maybe help quell some concern folks have for him, although with so many outfielders for not enough spots in Cincinnati, he may not get the playing time this season to show exactly what he can do. He might need to be traded for that to happen.
Finally, it’s scary to think that Mookie Betts could get even better, but by Long Fly Balls, that could definitely be a possibility. His 2019 season wasn’t quite the fireworks show that his 2018 season was, but it was still excellent, and he may have even gotten a little unlucky in the power department. His Statcast metrics were all still excellent, but one thing to note is that he had one of the largest differences between his actual and expected slugging, and some of that difference I’m guessing has to do with his Long Fly Balls. He hit a good amount of Long Fly Balls last season, but a lot of those didn’t necessarily show up in his home run totals, as only about 58% of his 29 home runs came from Long Fly Balls. Assuming he experiences some positive regression in this area, and everything else remains equal, Betts could put up an extremely nice home run rate in his walk year. Not too bad at all.
Long Fly Ball Rate: Conclusion
That about wraps things up for now for Long Fly Balls. This post has been long enough, so I’ll try to keep this part brief. But hopefully, it’s clear now that Long Fly Balls can be a pretty useful stat when evaluating hitters. When evaluating hitters who overperformed what their Long Fly Ball rates indicate they deserved in terms of total home runs, the common trend seems to be that those hitters either play in an extremely favorable offensive environment, or can pull their home runs enough that they don’t necessarily need to make a lot of strong contact, or even a combination of both. These factors aren’t exactly bad, because all home runs count the same, and at the end of the day, a ball over the fence is a ball over the fence. However, when evaluating hitters, I would prefer to have hitters who consistently hit the ball hard and far, as that usually means that they’ll consistently have a good amount of home runs.
Hitters who underperformed their home run totals despite having a good rate of Long Fly Balls tend to not be extreme pull hitters, hit the ball hard, and have good average fly ball distance marks on their own, which shows up in their expected slugging, and explains part of the reason why a lot of them have actual slugging marks that lag behind their expected ones. Another trend with some of the main underperformers is that they don’t hit the ball enough in the air to take full advantage of their high Long Fly Ball rates. A hitter like Garrett Cooper gets some of the best results on fly balls of any hitter in the league, but because he hits over 50% ground balls, those great results don’t fully leak into his overall stat line. Should these hitters make the necessary adjustments to hit more fly balls, we shouldn’t be surprised to see their power numbers spike.
Overall, Long Fly Balls are a pretty simple metric that can actually end up explaining a lot when it comes to evaluating hitters. It is a tool that I will continue to use to monitor hitter performances and indicate some hitters that may see a power surge or a power outage in the future, and one that I hope you use too.
Photo by Keith Birmingham/Zumapress/Icon Sportswire | Adapted by Justin Paradis (@freshmeatcomm on Twitter)