Ruth’s Chris: Best and Worst First Ball Hitters

Or maybe it’s Chris is Ruth. In fact, if your name is (or sounds like) Chris, you can put up some Ruthian OPS scores when you put the first pitch in play, as shown by this list.

Rk Player OPS ▾ OPStot Diff PA PAtot AB H 2B 3B HR RBI BA OBP SLG TB GDP
1 Chris Davis 1.554 .923 .631 74 670 74 36 10 0 11 23 .486 .486 1.068 79 1
2 Khris Davis 1.504 .828 .676 46 440 44 18 3 0 9 23 .409 .413 1.091 48 3
3 Kris Bryant 1.466 .858 .608 75 650 72 36 7 3 7 26 .500 .493 .972 70 2
Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 2/2/2016.

Those are the top 3 OPS scores from 2015 when putting the first pitch in play, based on a minimum 400 total PA and 40 first pitches put in play.

More after the jump.

It’s long been held (especially by pitchers) that a batter does the pitcher a favor by swinging at the first pitch. That may be true, but when a batter swings at that first pitch and puts it in play (for the purposes of this post, balls “in play” include home runs), he seems to do rather well. For 2015, there were 211 batters with 400 PA, 175 of whom (83%) had a better OPS result when putting the first pitch in play than overall. But, was the OPS result when putting the first pitch in play better than when putting any pitch in play? The answer is still yes, but much less emphatically, as 125 of our 211 batters (59%) had a better OPS result when putting the first pitch in play than when putting any pitch in play. How about other even counts? It’s pretty much a slam dunk that the first pitch is far and away the best of the even counts for putting a ball in play, as 188 of the 211 batters (89%) had a better OPS when putting the first pitch in play than when putting the ball in play on any even count.

So far, it’s all looking pretty rosy for the first ball hitters. Except, to put that first pitch in play, you have to swing at it, and if you miss or foul it off, then you’re behind 0-1. So, how does first pitch OPS compare to OPS for all PA after an 0-1 count? Indeed, there’s the rub. Only 23 of the 211 batters (11%) managed a better OPS in all PA that start 0-1 than when putting the first pitch in play (so, if you go after that first pitch, don’t miss). Comparing only to PAs after 0-1 with balls in play improves that result modestly, as 74 of our 211 (35%) managed a better OPS result when putting the ball in play after an 0-1 count than when doing so on the first pitch. So, there can be a substantial reward for hitters who can put that first pitch in play, but also a sizable penalty for attempting to do so but failing.

But, can hitters be too aggressive in trying to put the first pitch in play? Perhaps not! In fact, only 78 of our 211 batters (37%) had a better OPS in all PA after a 1-0 count than when putting that first pitch in play. Indeed, putting the ball in play on the first pitch even works out better than doing so on a subsequent pitch after 1-0 for 112 of our 211 batters (53%).

If all those percentages have you a bit muddled, here’s a view of our group of 211 hitters showing how often they put in the first pitch in play and how much better or worse they were doing that compared to the rest of their PAs.

First Pitch OPS

The horizontal axis is showing the difference in OPS on a first pitch ball in play vs. OPS from all other PAs. A positive difference signifies batters who had better OPS when putting the first pitch in play and includes most hitters as there is a notable selection bias in these PAs since they conveniently omit the zero OPS strikeouts that have become so commonplace. The vertical axis is simpler, indicating the percentage of PAs with the batter putting the first pitch in play. The four quadrants denote:

  • UR (red) – batters who play to their strength by putting the first pitch in play a lot and who see positive results when doing so
  • LL (orange) – batters who don’t fare well when putting the first pitch in play and don’t do it a lot, thereby minimizing their weakness
  • LR (yellow) – batters who have success putting the first pitch in play but who don’t do it a lot
  • UL (blue) – batters who don’t do well putting the first pitch in play, but still do it a lot

The interpretations above are simplified and likely don’t tell the whole story. For example:

  • The UR batters may show a big OPS advantage on a first pitch in play because, in aggressively going after the first pitch, their OPS suffers from being in an 0-1 hole when they don’t put that pitch in play
  • Similarly, the LL batters may show inferior first pitch in play OPS scores because their OPS scores after the first pitch are enhanced by starting many of those PAs ahead 1-0
  • The largest LR group could maximize their first pitch in play OPS advantage by putting more first pitches in play, but only if they can maintain that OPS advantage when doing so (i.e. only if their movement on the chart is more up than to the left)

So, who were the best and worst first pitch hitters in 2015? Here are a few tables.

Below are the top and bottom 10 of our group of 211 batters for First Pitch OPS, OPS After the First Pitch, and OPS on balls in play after the first pitch (note that for all of these table balls in play includes home runs).

[table id=280 /]

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Next are the OPS differences. The values shown as the difference between first pitch OPS and: overall OPS; OPS after the first pitch; and OPS on balls in play after the first pitch.

[table id=281 /]

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These are the same measures as in the previous table except that the first pitch OPS differences are represented as the % of each of the other OPS measures. J.J. Hardy is notable not only for placing dead last in each measure, but also in how far he trails the second-to-last ranked player.

[table id=283 /]

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Finally, here are some indicators of how batters approach their at bats. First is the % of PAs ending with a first pitch ball in play. The “indexes” are:

  • Aggressive: % of PAs with first pitch in play PLUS % of PAs starting 0-1
  • Selective: % of PAs starting 0-1 (to score well, you need take a lot of first pitch balls AND put the ball in play when the first pitch is a strike)
  • Patient: % of PAs starting 1-0 MINUS % of PAs with first pitch in play (to score well, you need a lot of the first and not too many of the second)

[table id=282 /]

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CursedClevelander
CursedClevelander
4 years ago

Fantastic work here, Doug. So much data to pore over, it’s hard to know where to start.

No surprise that Santana is the least aggressive hitter by this metric. I wonder if he’s *too* selective – last year was his first season under a .400 slugging percentage. He’s always going to get you 90+ walks a year, which is nice, but he was most valuable when he combined that with decent power.

no statistician but
no statistician but
4 years ago

Interesting that two of the three CKhrises led the leagues in whiffs and the third averaged a K a game. Any connection there? Pedroia, the fourth in the mix, doesn’t follow the pattern.

e pluribus munu
e pluribus munu
4 years ago

Doug, I’m having some trouble with the tables and charts. On the charts, I think it’s just a matter of my colors showing up differently (I get purple in the top right: that’s the UR quadrant, right?). But on the tables, I’m having more trouble, and I wonder whether there isn’t some mislabeling on the last one. It seems to me that columns 2 and 4 should add up to 100%, according to your labels, but this is obviously wrong. In the case of Billy Burns, who is the only player who seems to me a potential test case, columns… Read more »

Doug
Doug
4 years ago

BIP + Agressive + Patient should equal 100%. It’s BIP + (0-1 + BIP) + (1-0 – BIP) = BIP + 0-1 + 1-0 = 100%.

e pluribus munu
e pluribus munu
4 years ago
Reply to  Doug

Ah. The problem was that ‘MINUS’ was in caps – very hard to spot.