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Have the Jays been overplaying Kevin Pillar?

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Has playing almost everyday hurt Pillar’s productivity?

MLB: Toronto Blue Jays at Tampa Bay Rays Kim Klement-USA TODAY Sports

It’s a pattern that has become as familiar as the Sun rising in the east and setting in the west.

On May 9, 2016, Kevin Pillar woke up with a 115 wRC+, making him one of the best players in baseball over the first five weeks. But he promptly went into a nasty slump, hitting .152/.167/.202 (-10 wRC+) over the next four weeks. He then rebounded to post a 97 wRC+ over the last four months of the year, finishing at 82 wRC+ overall.

On May 25, 2017, Pillar woke up with a 125 wRC+, again making him one of the best players in baseball. The ensuing slump wasn’t quite as deep (.137/.196/.221; 8 wRC+ through June 20th), but nor was the rest of season rebound as strong, with a 87 wRC+ that almost matched his 86 mark overall.

On May 12, 2018, Pillar woke up with a 143 wRC+, making him — you guessed it — one of the best players in baseball. Once again followed by a hard slump, as he hit .139/.179/.181 (-8 wRC) over the next three weeks, though the five weeks that followed that were quite rough as well (62 wRC+), for an overall two month stretch between the end of his hot start and mid-July injury of .199/.219/.313 (39 wRC+).

I’ll grant that these endpoints have been selected (“cherry-picked”) to accentuate the differences between the hot and cold stretches, but the broader point is clear. In each of the last three seasons, Pillar has shot out of the gate, usually just long enough for a breakout or “this time is different” narrative to emerge, before crashing hard to earth for weeks and righting the ship on the mediocre-to-poor side of in between.

This yearly trend has led me to wonder if part of this is fatigue related, that is, just being run-down over 162 games. After all, Pillar has been almost literally an everyday player when healthy — 159 games in 2015, 146 in 2016 despite missing 13 games, 154 in 2017 with five missed, and 142 last year despite missing 14 games. Yearly, he’s played in 96-98% of games in which he’s been active.

Establishing that kind of causal link though is not simple. With three seasons/data points, it could simply be coincidence — and there was no such pattern in 2015. There could be other explanations (playing through injuries, etc).

But we did get another interesting data point last year. On July 14th, he was injured diving for a ball, and missed 19 days before rejoining the lineup August 3rd. He scuffled initially, which can be logically attributed to getting back to game speed and form with no rehab games. From August 14 to the end of the season, he posted a 114 wRC+, driven by 17 extra base hits.

The almost three weeks recovering from that nasty sternoclavicular joint sprain was three weeks away from the grind of near daily games and presumably allowed for some physical refreshment (for lack of a better word). And he hit really well. Combined with the fact that unlike the other periods, it’s not coincident with the beginning of the season, I was hopeful it might help show a statistical “smoking gun” for the premise.

Unfortunately, it wasn’t so clear after all. I played around with a lot of different approaches to modelling playing time and (hitting) performance, but failed to come up with a (statistically) significant link. Perhaps that’s a failure on my end to find the right approach, specifically coming up with a good way of measure the impact of cumulative impact of playing over time; perhaps it’s just not in the data.

There is perhaps one interesting takeaway though. Regardless of the exact model, there was a noticeable trend across models. With the 2015 and 2016 data, there was very weak correlation between any measure of playing time and performance, but sightly positive (ie, more playing time = better hitting results), in the range of less than +0.1. For the 2017 data, the correlations were similarly weak, but to the negative side (more playing time = poorer hitting). The correlations for 2018, though still weak, were even more negative in the range of -0.2 to -0.25.

What this may reflect is the increasing impact of age. It is well established that recovery becomes slower with age, especially for baseball players in an age when amphetamines and the like are banned. Particularly given his all out style of play, it may be that Pillar was able to sustain it everyday when he was 26 in a way that is much less so at 30.

It was one thing for Pillar to be playing 98% of the time in 2015-16, when he was clearly an elite defender and more importantly the Blue Jays were lacking for quality outfielders (remember Chris Colabello in left?) and especially viable alternatives to cover centre. But between Pillar taking a noticeable step (or two) backwards defensively and with Randal Grichuk and perhaps Dalton Pompey both at least reasonably adequate, that’s no longer the case.

Even without a clear link that would suggest more rest would be likely to result in improved hitting, I think it would make a lot of sense to regularly rest Pillar. He’s got significant career splits (81 career wRC+ against righties; 102 against lefties), so give him a day off once a week or so against them and get a lefty bat in there, with one of Pompey or McKinney likely to make the team.

If nothing else playing 130-140 games should mitigate a clear weakness. If it keeps him fresher and more productive, all the better.