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Robert Ritchie's avatar

Concerning GIDPs, it is mildly irritating that the broadcast does not contextualize the raw number. The raw number is not very informative, but GIDP% is. In other words, at what rate does the player ground into a double play when there is an opportunity to do so (runner on first with less than two outs)?

For the 2024 season, Toronto's GIDP% is 14.0%, MLB's third-highest (the MLB Average is 9.8%). At the player level, the GIDP rates of Blue Jays are as follows (small sample size warning):

- Kirk (40.0%)

- Clement (22.2%)

- Turner (22.2%)

- Springer (21.4%)

- Bichette (19.1%)

- IKF (17.7%)

- Kiermaier (16.7%)

- Vlad (15.8%)

No other Jay has hit into a double play in 2024.

Regarding Vlad specifically, his 2022-2024 GIDP% is 15.6%; MLB's Average GIDP% is 11.3%.

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Gabriel Gutierrez's avatar

I have a theory. Could it be that the analytics team is bad? That they have bad data to work with? Some decisions are just baffling. I work at an analytics department in an international company, and sometimes the level of data literacy of high management executives is disappointing, and sometimes they make decisions after they fixate on a small insight with an incorrect interpretation. Baseball is of course different, but still could happen. I think they overestimated the impact the shift ban would have, and they thought good defenders would be at a premium. The league's BABIP hasn't changed much after the rules changes, so if they bet on it in offence and defence, it would explain why they prioritize contact and defence. A radical change in philosophy would be needed to correct for the miscalculation.

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