How much did limited shifts effect offense? This table looks at hitters with at least 200 PA in 2023 versus the same point in the season in 2022.
| Batting Average | 2022 | 2023 |
| Mean | 0.254 | 0.257 |
| Standard Deviation | 0.036 | 0.032 |
| Max | 0.363 | 0.402 |
| Min | 0.157 | 0.175 |
| Median | 0.253 | 0.258 |
| Count | 163 | 164 |
I’m always amazed at how few players qualify for the batting title. It’s just a little over three per team.
Batting averages are up with big jumps at the maximum (both Luis Arraez) and the minimum. The mean is not all that different, however, while the median has a wider gap.
The standard deviation is narrower. One might expect that if shifts hurt some players more than others. For example there are players that see very few shifts.
Of course, batting average is also influenced by strikeouts and home runs, both of which are up this season. Here is the same data for BABIP, which clears out the influences of those events:
| Batting Average, Balls in Play | 2022 | 2023 |
| Mean | 0.295 | 0.301 |
| Standard Deviation | 0.044 | 0.041 |
| Max | 0.427 | 0.418 |
| Min | 0.181 | 0.172 |
| Median | 0.293 | 0.301 |
| Count | 163 | 164 |
The data shows a larger increase in BABIP than BA, with a smaller spread as well. Here, however, the highest and the lowest values are much lower than in 2023. The limited shift seems to have helped the great middle class of hitters.
The limits on shifts helped BABIP, which was enough to offset the increase in strikeouts to raise overall batting averages.