Early Results of the Shift Alterations
As everyone knows, the shift was banned for this season with players needing to be on the infield dirt and just two on each side of second base. I’m going to take an early glance to see if more hits are happening because of the extra holes in the infield and shallow outfield. Overall, the results ended up close to expectations but are noisy in some spots.
For the shift information, I’m using two rates, the full and strategic shift designations. For clarification, here is the explanation of the “strategic” shift from Baseball Savant.
A “strategic” shift is our current catch-all for positioning that is neither “standard,” nor “three infielders to one side of second base.” More granular categories, like “guarding the lines,” “five infielders,” etc., may be added in the future.
Examples of this often include just a single player being out of position, like a second baseman being shifted to short right while no other fielders are, as in the image above, or a shortstop moving very close to the second base bag, outside of the usual shortstop zone, but not quite moving to the other side of it.
During the offseason, I examined how the shift might affect individual players and the league-wide BABIP. For The Process, I looked at players moving from the full to the strategic shift. I used the strategic values since defenders could still move around this, just not as much as before. It was far from perfect, but I felt it was better than assuming no shift. Here are my conclusions from the book.
Jeff looked at into several solutions, including taking handedness into account, and ended up with the following formula to estimate a player’s change in BABIP:
BABIP Gained = Full Shift%^2 * 0.035
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And here are expected individual hitter BABIP gains for various full shift amounts.
| Full Shift% | BABIP Change |
|---|---|
| 90% | .028 |
| 80% | .022 |
| 70% | .017 |
| 60% | .013 |
| 50% | .009 |
| 40% | .006 |
| 30% | .003 |
| 20% | .001 |
| 10% | .000 |
| 0% | .000 |
On the league-wide value, I was off a bit with the league-wide value so far going from .243 to .249 or .006. Close.
As for the individual players, I bucketed the players into 10% point groups for anyone who hit in both 2022 and 2023. Then I found the Harmonic mean of the plate appearances to help weigh the yearly change. First, I bucketed just the full shift values.
| Full Shift% | BABIP Change | AVG Change | Count |
|---|---|---|---|
| > 90% | .013 | .019 | 8 |
| 80% to 90% | .013 | .006 | 23 |
| 70% to 80% | .022 | .012 | 33 |
| 60% to 70% | .010 | .007 | 29 |
| 50% to 60% | -.004 | -.009 | 29 |
| 40% to 50% | -.016 | -.009 | 39 |
| 30% to 40% | .005 | -.010 | 27 |
| 20% to 30% | .014 | .018 | 37 |
| 10% to 20% | -.001 | .001 | 65 |
| <10% | .002 | -.001 | 111 |
| >65% | .017 | .009 | 81 |
The top and bottom 20% came out near expectations with decent jumps for the most shifted players and no change for those who weren’t shifted. Now in the middle, values bounced all over the place.
I wondered if those in the middle were being strategically shifted a bunch and adding those shift values might clean up the results. I reran the test with the full and strategic shift rates combined. Here are the results.
| Full and Strategic Shift | BABIP Change | AVG Change | Count |
|---|---|---|---|
| > 90% | .019 | .022 | 21 |
| 80% to 90% | .018 | .006 | 43 |
| 70% to 80% | .006 | -.002 | 32 |
| 60% to 70% | -.008 | -.001 | 29 |
| 50% to 60% | -.027 | -.021 | 39 |
| 40% to 50% | .030 | .015 | 34 |
| 30% to 40% | .004 | .010 | 49 |
| 20% to 30% | .000 | .004 | 71 |
| <20% | .002 | -.002 | 83 |
| >65 | .014 | .007 | 114 |
The results stayed the same. The top and bottom 20% are nice and clean while the middle bounces around.
In both cases, I highlighted the results for those who see the particular shift two-thirds of the time. In each case, there was about a 15-point jump in BABIP and an ~8-point jump in AVG. The results so far match the preseason expectations and in a month or so, it will be time for another check-in.
Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
Thanks for this update, appreciated
I’m surprised the difference is so low. I feel like I’ve seen a TON of grounders get through that were sure outs last year.
Perhaps, but there are then nearly as many balls being gobbled up by normally-positioned infielders that would have found the hole in last year’s shifts. For most batters the shift never made an enormous difference in the first place. It was about the defense attempting to shave a bit on the margins here and there.
Unclear if this kind of study is useful at all.
Seems like better to figure out what type(s) of batters the change affects most and probably more importantly by how much. We can all easily guess the former (at least all the pull hitters) me thinks, but how much is another story…