a woman is asking what is good . ALT: a woman is asking what is good .

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Did they change projections? I couldn’t see anything that stood out

@redsoxstats.bsky.social What is the price you would be willing to pay for Sandy?

Does the recent reporting from Olney re: deferrals and present value (closer to 3/90) change your opinion here?

Re-made the univariate model with Percent IVB Change as the dependent variable instead of IVB Z-Score. Coefficient for temperature is 0.002, or 0.2% for every degree change in temperature, 2% for every 10 degrees. Correlation is a bit weaker for IVB percent difference than IVB z-score.

@mikepetriello.bsky.social, Lance mentioned that he had seen some statcast wind data that was more descriptive/specific, is this publicly available? I don't seen anything for wind on statcast, currently using retrosheet's wind data.

Got it. Going to try and incorporate some interaction with headwinds expected positive for IVB and tailwinds expected negative and see if there is anything there.

The model aims to predict an individual pitchers' z-scores, so using league average is a bit of a shortcut evaluation, but it doesn't seem far off from the 2% you are suggesting?

Expanding on this, league avg 4SFB IVB Std deviation is 2.97", so 10 degree change is roughly a 0.55" change in IVB, which is a 3.5% change from the league average IVB of 15.71", but not sure if that should be the denominator?

I am not entirely sure how to go about finding a "fraction" here because I'm not quite sure what the denominator should be.
For the univariate OLS model of iVB_Z-Score ~ Temperature, the Z-Score decreases by 0.0186 for a 1 degree increase in temperature.

@redsoxstats.bsky.social not sure where you primarily reside now but thought this might be of interest to you.

The initial goal of this was to see if Walker Buehler was substantially weather/season-average predicted 4SFB iVB, suggesting regained life on the pitch. More work needed here, but seeing 3 outperformances to end the year is mildly encouraging.

Contrasting two games of similar pitchers / weather. We see that the Z-Scores are far crazier in Citi Field than Yankee Stadium. The next step here would be to try and model iVB for an individual ballpark, based on weather.

In looking at Freddy Peralta's first start of the season (per @lancebroz.bsky.social suggestion, also at Citi Field), we see a similar Z-Score outperformance by most of the game's pitchers. This suggests that ballpark structure could play a greater role in pitch movement than initially understood.

Curious if you have further thoughts on what to look for here re:wind data, or what aspects of you think play the biggest role in iVB variance @pobguy.bsky.social ? @elibenporat.bsky.social mentioned that you might have some insight here.

Continuing the discussion from twitter, both @tjstats.nesti.co and @lancebroz.bsky.social mentioned that it is likely the wind data is not descriptive enough, including the possibility of wind bouncing off wall behind home plate having an amplified effect.

Attempts to include wind direction in the linear model did not improve the models performance.

This suggests that either a) the weather(specifically wind) data is not descriptive enough (and thus is not being appropriately accounted for by the model) or b) there are other factors at play that have not been taken into consideration

The model predicts a 4SFB iVB Z-Score of 0.41 for this game; though the actual Z-Scores were all much higher than this
bsky.app/profile/chuc...

This model is trained using data from the 2024 MLB Regular Season.

We can then use this to predict what we would expect 4SFB iVB Z-Score for pitchers to be in G3 of the NLCS, based on the weather (51 degrees Fahrenheit, 8MPH wind speed).

Our model will look like the following:
(Predicted 4SFB iVB Z-Score for game) = B_0 + B_1 * (Wind Speed) + B_2 * (Temperature)

We find both temperature and windspeed have a significant effect on 4SFB iVB Z-Score, and that they account for ~22% of the variance in this Z-Score.

It has been mentioned by many, including Buehler himself, that the weather in NLCS G3 had a strong effect on pitch movement. To better understand how weather impacts one's 4S iVB Z-score, we can train a linear model.

Walker Buehler had a strong outing in G3 of the NLCS. His 4S Fastball averaged 20.2" of iVB, outperforming his season average of 16.6". Other pitchers in this game saw similar outperformances.

Digging into Walker Buehler's playoff performances. Found the fairly strong relationship between a pitcher's IVB and temperature to be interesting:

Do you mean this as in they’ll be priced out or you don’t think Vlad is worth that contract?

At this point, what are your ideal additions? Burnes / Bregman at 2B?

Credit to sources: @seidler.bsky.social @redsoxstats.bsky.social @jon-becker.com

Layman's Red Sox Offseason Thoughts I am not a professional.

First attempt writing about baseball:
open.substack.com/pub/chuckrak...

Was curious your thoughts on this Stats. If they can extend him is it not worth the price they pay in prospects, if he projects to be Skubal-level good?

You mentioned not wanting Burnes to some degree because his contract would be too big. Do you share that similar sentiment re: Fried if it’s true he’s getting 200MM+ as Nightengale reported? If so, why is he more palatable to you than Burnes at that price? Primarily the concern with Burnes’ cutter?