APBRmetrics

Yeah, I leave the lambda at 3000 (standard found by J.E., which usually results in a range of about +/- 5 or 6 by the end of the regular season) for every run, so the early season numbers will be more compressed. There will certainly be some whacky results even with this method, but it's probably f...

But I am curious why you think that high school academic history/SAT scores aren't dependent on a student's job/financial situation, family issues, work ethic, etc.? I'm not sure if you're being serious or not here. Assuming you're not joking, there is a world of difference between a typical high s...

It's definitely not just you. This is certainly a strange start to the season. Although I think it was somewhat predictable after watching games from the covid bubble last season. Players are on edge and team chemistries are getting messed with. Covid is having a massive effect on everything around ...

I'm confused. Why wouldn't we just take FGs made - Assists as the unassisted baskets? Assists in the boxscore are not the number of times you were assisted, but the number of times you passed to someone else, who then scored on a FG. Oh, sorry. I misread that before. I thought we were talking about...

ok not really into the whole RAPM measures (not metrics!) but since you mentioned boxscores and skewed distributions....when I was looking into specific individual boxscore stats (continuous) the models that fitted best was the Weibull model. It can adjust for left and right skewness and it can app...

directional accuracy Define that please. I just mean that I want my model's output to be somewhat close to what has happened historically for other games with the same number of minutes remaining and the same point spreads. So, if the model sees that tonight's game between HOU and SAC where HOU is ...

Perhaps you're just pointing out that there is a better way to approach building a model that predicts game outcomes than the approach I've taken. I would certainly agree with that. However, my use case is simply to help me be able to flag which possesions occur during "garbage time", so d...

I really disagree with this way of thinking (i.e. evaluate temporal performance only w.r.t. the final outcome). You can always construct counterexamples of models that, acording to your evaluation logic, can have a high prediction accuracy at t=48. Imagine a trivial model that predicts 0.5 from t=0...

You're taking an (originally tail-end-of-population) subset of people, but then you're providing them with resources that aren't available to the outside world... I think the end result is a mix of tail-end and gaussian Distributions of various simple BoxScore stats will tell the same story. None o...

Another example is the fairly well-known fact that SAT scores do a good job of predicting who gets into graduate school but does not do a good job of predicting (can in fact be negatively correlated with) success in grad school. This is a different problem though. There are two entirely different d...

But I cannot think of a better way for evaluating live time prediction methods. You can definitely train them from past data as rainmantrail said but evaluating them is I think much trickier I would be more interested in evaluating the performance of model A vs model B. This is very easy to evaluat...

I know you don't have data for assisted vs unassisted baskets but couldn't you use the box score data to create a proxy for that? For example if you know the PG had 20 assists in the game and his teammates made a bunch of 3's, you know that they got assisted a lot. But if you see an Allen Iverson g...

Agreed. Here's the deal--big men drive the defense, to a large degree. Big men should have a wider spread than guards. A bad defensive big man hurts the team more than a bad defensive guard, and a good defensive big man helps the team more than a good defensive guard. But I cannot, for the life of ...

Here's a prime example of what I'm talking about. Here's a link to a recent article from 538 that highlights my exact concern about adjusting for "luck". https://fivethirtyeight.com/features/what-to-watch-for-in-the-2020-21-nba-season/ The relevant paragraph from this article is quoted bel...

Underlying skills do change, but not very quickly unless something like an injury causes a shift. But the gist is the following. Whenever you hear "regression to the mean", be wary of the following: for regression to the mean to make sense in any statistical way, and assuming you are not ...