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On this week’s edition of This Week in Rays Baseball, the excellent Neil Solondz-hosted podcast that comes out weekly and looks into Rays happenings, Solondz sat down with Dave Wills, Andy Freed, and Brian Anderson for their final round-table discussion of the 2017 regular season. It was an interesting discussion, as they always are, but one mini-exchange with BA made my analytical ears perk up:
“On the flip side, the home run dependency… If you want to be a team that can occasionally manufacture runs, you have to have an approach at the plate. And that’s what you don’t see with this group. You don’t see anybody cut their swing down with two strikes. You don’t see anybody look to go the other way with two strikes and move a runner. It is all or nothing.”
There’s a lot going on in that 30 seconds of Classic Baseball Talk. It’s the type of paragraph that gives writers like me, who have time to sit back and analyze this type of comment instead of having to respond in the moment, a chance to see if BA is onto something, or if he was mistaken and his in-the-moment take maybe wasn’t as factually-based as he might have thought.
Let’s tackle the two main parts of his argument separately.
Home Run Dependency
The Rays reliance on the long ball has been a classic trope over the last few seasons, as the club has turned to the long ball more than ever. First they broke the single-season franchise home run record in 2016, and now they are just two home runs away from breaking that record again in 2017.
It is quite in vogue among the more pointy-headed of fans to dismiss BA’s type of comment as silly and uninformed, however, BA may actually be onto something. Here are the teams that have most relied on home runs for their total run production in 2017. (Thanks to DRB writer Adam Sanford for pulling the data for and creating this chart.)
Home run dependency 2017
TEAM | RUNS SCORED | HR | RUNS SCORED VIA HR | RUN SCORED W/O HR | RUNS SCORED VIA HR % |
---|---|---|---|---|---|
TEAM | RUNS SCORED | HR | RUNS SCORED VIA HR | RUN SCORED W/O HR | RUNS SCORED VIA HR % |
TOR | 650 | 207 | 326 | 324 | 50.20% |
OAK | 700 | 222 | 344 | 356 | 49.10% |
TB | 644 | 214 | 310 | 334 | 48.10% |
MIL | 693 | 214 | 331 | 362 | 47.80% |
BAL | 715 | 227 | 339 | 376 | 47.40% |
TEX | 770 | 225 | 365 | 405 | 47.40% |
NYY | 811 | 222 | 376 | 435 | 46.40% |
CIN | 718 | 209 | 332 | 386 | 46.20% |
SDP | 579 | 181 | 266 | 313 | 45.90% |
LAD | 717 | 207 | 320 | 397 | 44.60% |
NYM | 698 | 215 | 311 | 387 | 44.60% |
ARI | 755 | 204 | 325 | 430 | 43.00% |
CHC | 765 | 210 | 329 | 436 | 43.00% |
WSN | 775 | 201 | 327 | 448 | 42.20% |
DET | 707 | 180 | 296 | 411 | 41.90% |
PHI | 647 | 165 | 271 | 376 | 41.90% |
HOU | 822 | 222 | 344 | 478 | 41.80% |
KCR | 665 | 183 | 278 | 387 | 41.80% |
SEA | 708 | 180 | 295 | 413 | 41.70% |
FLA | 711 | 184 | 293 | 418 | 41.20% |
ANA | 665 | 172 | 272 | 393 | 40.90% |
CLE | 769 | 198 | 310 | 459 | 40.30% |
CHW | 664 | 175 | 267 | 397 | 40.20% |
MIN | 751 | 194 | 302 | 449 | 40.20% |
STL | 719 | 185 | 285 | 434 | 39.60% |
COL | 772 | 178 | 288 | 484 | 37.30% |
ATL | 687 | 155 | 253 | 434 | 36.80% |
PIT | 615 | 144 | 219 | 396 | 35.60% |
BOS | 739 | 158 | 249 | 490 | 33.70% |
SFG | 603 | 122 | 168 | 435 | 27.90% |
There are the Rays right near the top of the league, trailing only the Blue Jays and Athletics.
That part shouldn’t surprise most fans. The Rays have several go-big-or-go-home players in their lineup, and they have struggled all season with runners in scoring position.
What might surprise folks is that BA might be correct when worrying about this home run reliance.
Among the top six teams in home run dependency, only one of those teams possesses a wRC+ over 100, and only that same team ranks among the top 14 in baseball in wRC+. (Very quick side note: Try to guess which team it is… I’ll wait… Bet you didn’t guess it was the A’s.)
While small ball may be over-festishized by the old school types, it does appear, at least in part, that an over-reliance on home runs can lead stunt an offense at times.
Approach at the Plate
The second part of BA’s comments on the Rays hitters seems even more damning at first. It sounds like he’s saying that the Rays hitters lack the discipline or wherewithal to be cognizant of changing up their approach with two strikes. Thanks to the FanGraphs splits leaderboard, we can actually get some data as to whether or not the Rays change their approach with two strikes or not.
The main thing BA noted was that he didn’t see any of the Rays willing to go to the opposite field with two strikes. In all plate appearances in 2017, Rays hitters have gone to the opposite field 24.6 percent of the time. With two strikes in the count, crazy enough, it’s that very same 24.6 percent.
In the strictest sense of what BA was saying, he was correct. The Rays hitter haven’t gone to the opposite field more with two strikes - they’ve gone oppo at literally the exact same rate.
The fair follow-up question for this data is whether or not that is common around the league. The Rays rank 22nd in overall opposite field percentage, and that rank drops to 25th in two-strike counts. The league, as a whole, goes to the opposite half a percent more often with two strikes.
So while it doesn’t appear to be a massive difference, it does appear as though the Rays are indeed a bit below average when it comes to going the other way with two strikes. Once again, a slight win for BA.
But does it matter if the team goes the other way with two strikes? Maybe. The Rays wRC+ in two-strike count ranks 21st compared to 16th overall.
Now, correlation doesn’t equal causation and none of the top three teams in two-strike, opposite field percentage rank among the top 10 in wRC+ this season, but I don’t think we’ve found enough here to say that BA was specifically wrong.
In fact, I think despite sounding a bit trite and #hottake-ish, BA was pretty much spot on with his comments on This Week in Rays Baseball. It’s not too surprising considering BA is one of the stronger and more informed announcer around the league, but it’s nice to be able to dive into the numbers a bit and see that more clearly.
Stats as of September 21, 2017. Thanks to Adam Sanford for the research and chart in this article.