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Identifying Burnout for Starting Pitchers (Before It's Too Late!)

Antonio Losada examines high usage rates by starting pitchers compared to historical trends to find SP who may experience second-half burnout. These players may be sell candidates for fantasy baseball.

We live in the era of data. There are numbers everywhere, and more than in any other place (in the context of sports), in baseball. Statistics have been a fundamental part of the batted-ball rounds for decades now. And as couldn't be otherwise, more and more franchises are at the cutting edge, putting analysis to practice and employing the very best methods they can come up with to get the best results on the field.

One of the most sought after and talked about trends in baseball nowadays is that of pitchers' usage. Each passing year it seems we recognize how pitchers (or any player, for that matter) are humans at the end of the day and continuous and prolonged performance at a maximum level of effort can be quite taxing.

This is why starting pitchers, more than any other players in baseball, are seeing their work rates cut.

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Where Do We Come From?

We just have to take a quick look at the data to see how this is indeed a fact. I have pulled every starting pitcher-season from 2010 to 2019 from Fangraphs. There are 762 player-seasons in the dataset. Then, I've plotted every player-season in the next chart (excluding those of 2019 to not introduce noise while calculating the trendline):

The circles in red represent players with 30 or more starts and the circles in green those with fewer than 30. The size, although not very appreciable, is also related to the number of games started.

I don't think there are any doubts left of what's going on. Each passing season there have been fewer starting pitchers throwing great amounts of innings.

 

Where Are We Headed?

If we add the 2019 player-seasons to the chart, we can see how the leaders of the pack are about to catch the trailers from past years:

That dot leading the way for the 2019 pitchers is Trevor Bauer. He's started 24 games by the date I obtained the data (August 2) with a combined 156.2 IP. Although he's still way behind Max Scherzer's 220.2 IP in 33 G last year, he's only less than five innings from getting on par with 2018 season's trailer Ivan Nova. The problem is that Bauer is going to catch him having pitched in five few games!

But we need to dig deeper and thread finer if we really need to know the truth. And the truth, in this case, is not hidden under games or innings pitched, but rather in pitches thrown.

Suppose Bauer were removing hitters on a one-pitch per PA basis (every throw becomes a groundout). He'd have thrown 156.2 IP * 3 batters per inning, which is a total of 468 plus two extra hitters, that is, a square 470 pitches. Ivan Nova threw a total of 2529 pitches last year. That is nothing abnormal. In fact, the abnormal would be to only throw 470 pitches to remove 470 batters. But you get the idea.

What the real data says is that while Ivan Nova took 2529 pitches to remove 683 batters (200 more than if he had only faced three per inning). That is an average of 3.7 pitches per batter. On the other hand, Trevor Bauer has thrown 2685 pitches and faced 664 batters for an average of 4.04 pitches per batter. As you can see, the load Bauer is carrying is already considerable and only looks like it gets even worse during the next few weeks.

 

Identifying Potential Burnouts - An Introductory Example

To try and find some potential pitchers with a high risk of burning out during the final stretch of the season I'm only going to use data from the 2017, 2018 and 2019 seasons. I am going to calculate differences from one year to another (from 2017 to 2018, and from 2018 to 2019), calculate some average metrics related to pitching, and find some burnout candidates.

My dataset includes 337 pitcher-seasons. Given that some starters have suffered injuries in that timeframe, others may have changed teams and roles, joined different rotations with different levels of talent, etc, I'm going to only look at pitchers which in 2018 played between seven more/seven fewer games from those they played in 2017, with a minimum of 23 G. That would get rid of some outliers. 62 of them did so.

Of those 62 starters, only four (Jameson Taillon, Blake Snell, Jose Berrios, and Zack Godley) played 7 G over what they did in 2017. Of those, though, only Zack Godley averaged more pitches per 9 IP (nine more, to be exact). The Diamondbacks burned Godley a little down the stretch, and what was a 3.37 ERA in 2017 became a 4.74 ERA in 2018. He allowed more walks and amassed fewer strikeouts (his K/BB ratio dropped from 3.11 to 2.28).

On the other hand, Jameson Taillon averaged 17 fewer pitches per 9 IP. That allowed him to lower his load over the long run. He threw a total of 2960 pitches, slotting behind 27 other pitchers during the 2018 season. As you may have guessed, his 2017 ERA of 4.44 improved to 3.20 in 2018, he maintained his K/9 ratio exactly the same and walked almost one fewer batter per nine IP. Load management seems to matter.

 

Identifying Potential Burnouts - Time To Find Our Candidates

Enough theory, and enough examples from the good old times. It's time to cut to the important thing, the current season.

To account for the season being still uncompleted and midway down the road, I'll use pro-rated stats to 30 G, which align with what we could expect in terms of games started by an ace nowadays. I will use those values also for the 2018 translation, so both seasons can be compared on the same terms.

Here are the pitchers that, at the current pace, would finish the season with 15 or more IP/30G than last season had they played exactly 30 games in both years:

Name 2018 IP/30G 2019 IP/30G Difference Increase Pct.
Lance Lynn 154 192 38 24.9%
Wade Miley 147 172 25 17.1%
Mike Minor 168 191 23 13.7%
Joey Lucchesi 150 167 17 11.1%
Sonny Gray 147 163 16 11.0%
Tyler Mahle 146 161 15 10.4%
Marcus Stroman 161 177 16 10.2%
Lucas Giolito 162 177 15 9.5%
Matthew Boyd 165 180 15 9.2%

Our old friend Shane Bieber barely missed the cut with a difference of 14 IP/30G between 2018 and 2019, as he was clearly surpassed by others, namely Lance Lynn (38), and not only in the pure count but also in the Increase Percentage.

As we already know, that is not half the truth, though, as we must account for thrown balls instead of innings. So here, instead of IP/30G deltas (the difference between one year and the next one), I have listed the pitchers with the highest deltas in terms of pitches thrown per 30G (min. Difference of 100):

Pitcher 2018 Pitches/30G 2019 Pitches/30G Difference Increase Pct.
Mike Minor 2734 3100 365 13.4%
Lance Lynn 2918 3217 299 10.2%
Luis Castillo 2688 2925 237 8.8%
Shane Bieber 2721 2954 233 8.6%
Sonny Gray 2523 2734 212 8.4%
Trevor Bauer 3113 3356 243 7.8%
Hyun-Jin Ryu 2596 2794 198 7.6%
Matthew Boyd 2768 2967 200 7.2%
Marcus Stroman 2695 2886 190 7.1%
Joey Lucchesi 2490 2648 158 6.3%
Chris Sale 2806 2977 171 6.1%
Jake Arrieta 2671 2821 150 5.6%
Charlie Morton 2688 2824 136 5.1%
Brad Keller 2828 2969 141 5.0%
Patrick Corbin 2856 2996 140 4.9%
Marco Gonzales 2652 2781 128 4.8%
Mike Leake 2708 2832 125 4.6%
Clayton Kershaw 2728 2852 124 4.5%
Noah Syndergaard 2894 3026 131 4.5%
Ivan Nova 2616 2734 118 4.5%
Julio Teheran 2712 2829 118 4.3%
Jon Gray 2710 2827 117 4.3%
Stephen Strasburg 2947 3063 116 3.9%
Jacob deGrom 3011 3120 109 3.6%
Eduardo Rodriguez 2889 2993 104 3.6%

Completely different story. These truly are the pitchers in danger of burning out down the road. These are the ones who are throwing more pitches per game than they did in 2018, by far. While it doesn't mean they are the ones throwing the most pitches overall (just look at the difference in projected pitches for Trevor Bauer and Sonny Gray, for example), it shows who is throwing way over his standards and what he did last season.

Probably nobody would argue Lynn, Minor, and Bieber are aces well worth allowing an increase of their load given the potential return. But they could be slowly entering dangerous territory if they keep their current pace. And the same goes for quite some more starters.

You can take the data as you please, but to me, there is the main takeaway to extract from it and two solutions to at least try to solve it. If indeed performance decays with a higher number of pitches thrown (by one's standards and average, again, not compared to the rest of the league), then every single one of those pitches is to a certain extent risking their production level during the final weeks of the season. To solve this issue, either they "improve" their pitching (by removing batters earlier with fewer throws) or have their teams pull them off the games earlier.

Of course, both things are easier said than done. One can't just flip the switch and become a batter-killer overnight. No one will ever remove hitters on a single-pitch basis. It's nonsensical. And second, we all know most aces want the spotlight and to be on the mound for as long as possible, which could make difficult the game-time side of the equation. Not many pitchers will auto impose a pitch limit on themselves, nor will their teams be willing to dramatically reduce the number if they feel like they're getting the most out of them when they're out there in the field.

As for you owners out there, it'd be crazy to drop say, Luis Castillo, because he's on his way to throw more pitches than he did last season. Yes, there is the chance he burns out and ends with a steep decline in production, or that his team starts cutting playing time to maintain his performance at a high level.

At the end of the day, aces gonna ace, but keep an eye on those names just in case.

More 2019 Fantasy Baseball Advice




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