APBRmetrics

Lmaoo, did not expect the post to be that long my bad

Currently(sporadically) working on an implementation for a soccer RAPM model. On the back burner also want to make some improvements to the RAPM script I have for the NBA. So here are a list of questions or ideas I've had during the process, some probably not very relevant to the NBA. ______________...

Ran some regular season minute weighted averages of some statistics. Used only top 10 players. rescaled to 240 minutes. Here are the results. XRAPM ------------------------------------------------------------------------------------ Rk Team PI Total Off Def ------------------------------------------...

At a player level I'm also curious how various factors interact with each other. For example how can one go about converting rim frequency ,reb% on/off to points. Is a purely expected PPS method the way to go? Or do you do regression studies?

I did a quick test of this(wanted to see if there were any changes from the regular season to the playoffs) and got these results. Regular Season — No Intercept (R² ≈ 0.99) Factor Oliver Full Past (≤2009) Recent (≥2015) Shooting 40% 42.5% 42.0% 43.5% Turnovers 25% 40.0% 40.8% 37.6% Rebounding 20% 8....

Hey all, Was wondering how much truth there is to live turnovers affecting a player's defensive value. More specifically how many more points per 100 possessions would the average player give up on defense if they averaged one more live turnover per game. Also curious on how this looks at a team lev...

Any explanation for this? Lineup trickery? 3PT shooting 'luck'? Seemed to continue in the playoffs, albeit a small sample size. DFS and Luka continue to look great. Has anyone ran an adjust for this? XRAPM(the site) has his single season rapm at -2.9(9th percentile). He seems to be opting into his c...

Hi everyone, I'm thinking of extending my approach to build an SPM for the NBA and for the game basketballgm. The model I’m working on uses **RAPM from the JE dataset** as a foundation, aiming to combine its stability with box score and potentially tracking data to create a metric that’s both predic...

If you don't test out of sample you end up with an overfit and non-robust model. leave-one-out out-of-sample mean-squared prediction error One question I have about these remarks specifically: I know using in-sample R^2 is bad, and I made a mistake doing this, but I'm using the cross_val_score func...

fwiw, ~8 years seems to be the sweet spot My current confusion with using longer RAPM(which has less noise and should have less collinearity), even when age-adjusted, would be how I accurately get a predictor variable for this longer RAPM. Averaging values seems to make some intuitive sense, but I'...

Also, I wish there were more available spasms, lol. It doesn't seem like a too daunting task; maybe the reward just isn't worth it. I meant to say SPMs here, lol. I just realized you co-created ESPN's RPM. Is there any reason for it being updated based on what you and Steve worked on, and then it g...

Thanks for the replies. Generally, it's better to put in a "best guess" of the player's "true ability." The most straightforward example is that a player who made 2/2 threes should probably not be in the SPM regression with 100% 3p%. Can use Bayesian inference, Kalman filter, or ...

Hey all, I'm currently creating a Statistical Plus-Minus (SPM) model for personal use. I plan on building different variants of the model, starting from raw box score data (for use in the game Basketball GM) and eventually incorporating play-by-play data and other advanced metrics. Right now, I have...