The Luckiest and Unluckiest Batters by xwOBA

Last week I posted an article about Chris Taylor and how I expected him to regress. I won’t get into that much detail here but I just want to look at the luckiest and unluckiest players of 2017.

The under-archiever leaderboard looks like this (copied from Baseball Savant):

1	Miguel Cabrera	0.382 – 0.322	0.060	Graphs
2	Mitch Moreland	0.371 – 0.335	0.036	Graphs
3	Victor Martinez	0.344 – 0.311	0.033	Graphs
4	Alex Avila	0.401 – 0.368	0.033	Graphs
5	Albert Pujols	0.326 – 0.294	0.032	Graphs
6	Kendrys Morales	0.358 – 0.326	0.032	Graphs
7	Brandon Moss	0.336 – 0.305	0.031	Graphs
8	Taylor Motter	0.288 – 0.259	0.029	Graphs
9	Alex Gordon	0.300 – 0.275	0.025	Graphs
10	Jose Martinez	0.411 – 0.386	0.025	Graphs

 

And here is the over-achiever leaderboard. Also in the top-30 are the mentioned Taylor, Jose Ramirez, Nolan Arenado and Javier Baez, among notable players:

1	Eduardo Nunez	0.275 – 0.348	-0.073	Graphs
2	Marwin Gonzalez	0.320 – 0.387	-0.067	Graphs
3	Zack Cozart	0.332 – 0.399	-0.067	Graphs
4	Mallex Smith	0.239 – 0.305	-0.066	Graphs
5	Jose Altuve	0.349 – 0.413	-0.064	Graphs
6	Dee Gordon	0.254 – 0.318	-0.064	Graphs
7	Scooter Gennett	0.312 – 0.374	-0.062	Graphs
8	Kevin Kiermaier	0.279 – 0.341	-0.062	Graphs
9	Charlie Blackmon	0.364 – 0.424	-0.060	Graphs
10	Ronald Torreyes	0.241 – 0.299	-0.058	Graphs

 

Now the question is whether it is really all luck. If you look at the unlucky leaderboard, it is pretty easy to see that many of them are slow as dirt. The over-achiever group has some average-speed players (for example Marwin Gonzalez), but also speedsters like Altuve, Smith, Gordon and Kiermaier.

Overall, the under-performers had a higher launch angle, higher exit velo, and a slightly but not significantly higher pull rate (thought that might be a factor due to the shift, but really wasn’t).

 

	sprint speed	exit velo	launch angle	pull%
under-performers	25.66	89.24	12.59	42.1
over-performers	27.98	84.04	8.49	40.89

 

Of course we don’t know whether those factors like low LA and low power, which are generally associated with worse hitting, are not correlated directly to the sprint speed. To test that, I looked at some sub-groups. When searching for harder hitters at lower LAs, I took EVs of over 89, paired with LAs under 9 (just eight players fulfilled that BTW). You get a slightly positive differential, which means slight under-performance, but only by about 18 wOBA points. Looking at soft hitters (below 85) with high LAs (<12 degrees), it does get more significant at a wOBA difference of 30 points.

Hard hitters with high LAs, however, only under-perform a tiny bit (about 8 points), so LA alone doesn’t really seem to make a difference. Hitting fly balls soft might be a factor that affects the under-performing, and very clearly speed does.

What we need to find out is how much of that is sustainable year to year. We do know that some pitchers have the skill to outperform their FIP, but for the most part pitchers who outperform their FIP will regress. Under or over-performing xwOBA might not be pure luck; there are factors which likely have an influence on that. Some of that might be holes in the xwOBA stat that can be fixed over time, and others might be caused by the player type. I think we need to do more analysis on the predictive value of xwOBA and the factors that influence it.

But of course one last thing needs to be said: Over-performing your wOBA is nice, but still, the overall production counts. Some of the over-performing hitters are still not good hitters (Gordon, Torreyes, Gennett), while some under-performers are good.