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Cameron Grove
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Cameron Grove
@Pitching_Bot
Cleveland Guardians R&D, interested in baseball analytics, former astrophysicist, based in London, UK
Entrou em Temmuz 2019
178 Seguindo5.4K Seguidores
Cameron Grove retweetou
Cameron Grove retweetou

The @CleGuardians are looking for a Biomechanics Analyst to join their Baseball R&D group. Apply here: boards.greenhouse.io/clevelandguard…
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As I've left the public space, PitchingBot has a new home on FanGraphs.
fangraphs.com/leaders.aspx?p…
Check out the primer here if you want to know more about what goes on under the hood:
library.fangraphs.com/pitching/pitch…

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Cameron Grove retweetou

PitchingBot and Stuff+ Pitch Modeling Is Now on FanGraphs! blogs.fangraphs.com/pitchingbot-an…
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@tangotiger Fair enough, I thought the graphs above avoided that by changing the samples to still include players on the "bad" side of random variation.
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@Pitching_Bot Still a selection bias... see the two responses from readers describing the reason
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This article is actually an excellent example of selection bias. Can someone out there articulate why I would conclude that?

Taiyo Keilin@TaiyoKeilin
@thechairman04 @tangotiger I think pulling Wheeler was the right call but maybe bringing in Alvarado wasn’t. I don’t know how the Phillies felt their other relievers matched up against Álvarez but it seems hitters gain an advantage the more they see a relief pitcher. baseballaheadinthecount.blogspot.com/2022/01/dont-l…
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@levy_cameron @tangotiger @TaiyoKeilin @SassoCT I couldn't locate the wOBA graph, but here are home runs and Ks


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@levy_cameron @tangotiger @TaiyoKeilin @SassoCT I agree the regular season results are mostly selection bias.
I redid some of the postseason analysis comparing to the odds ratio wOBA of the batter-pitcher matchup and there seemed to be something real there (didn't publish that though, I'll see if I can dig it out)
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Cameron Grove retweetou

This feels relevant
Alvarado vs Alvarez
baseballaheadinthecount.blogspot.com/2022/01/dont-l…
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@VorosM Hard to say much.
Note that the Phillies game would have come under "Cloudy" using this definition of weather. Fastballs show a bit more of a significant change from clear -> cloudy compared to other pitches.

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@whoeferbaseball I filtered all of those out but I agree it would make a good control group.
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@Pitching_Bot That would be a great control group for the effects of weather and temperature; it theoretically removes a lot of the environmental variables that aren't 100% reflected here.
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@tangotiger @Light_Saberist One could argue that hitters have more control over whether they pull flyballs than pitchers have over BABIP.
twitter.com/Pitching_Bot/s…
Whether the effect is significant enough to be worth including is another question.
Cameron Grove@Pitching_Bot
Also, batters have a reliable skill at getting their flyballs to fly further than the model expects when controlling for LA, EV, stadium, & weather. Year on Year R^2 = 0.2 for min. 50 flyballs which is small but significant. Here are the batters who gain/lose the most distance.
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@Light_Saberist It's like saying "You know what's missing from FIP? BABIP. FIP is totally ignoring balls in play. Let's bring in BABIP."
Again, do you want to explain the play (wOBA or FIP + BABIP)? Or do you want to explain the player (FIP)?
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#Statcast Someone was asking about launch data for Judge. I'll take more in-depth look later, but launch angle is easy enough to figure. Draw hypotenuse right underneath ball (see white blur). Then take arctan of opposite (103) over adjacent (189): 28.6 degrees. Actual: 28.3

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@tangotiger @JPosnanski The infield playing in will also have an effect right?
The highest situational babips are generally a runner on third, < 2 outs.

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Why does this happen?
It's a statistical trick, and it's all because of accounting (or non-accounting) of sacrifice fly. This is why OBP doesn't show that kind of split: the SF counts in denominator of OBP. It doesn't in BA and SLG.
cc: @JPosnanski
baseball-reference.com/leagues/split.…

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