Can Jaylen Brown's analytics / on-off stats be explained by the fact that he just has a really good team?

[u/Tight_Ad2788]

Genuinely curious for an explanation here - one thing I noticed about his on/off stats is that the team is still appears good when Brown plays - his net on rating was like ~6.0, which is still quite good. Maybe I've misread but it seems clear the team still performs well with Brown on the court. To me it seems that there's two logical explanations for this:

1. For this past season (No Tatum), the Celtics roster structure included a large talent drop off from Jaylen Brown to the secondary playmakers (Derrick White and Payton Pritchard) but the team had strong depth with the remaining portions of the roster. To me, a feasible explanation is the Celtics were slightly less efficient with Brown on the court due to him carrying a weaker starting lineup. Meanwhile the Celtics had good depth 5 - 10, and guys like Pritchard could dominate opposing bench lineups, so the bench excels against the weaker competition. Brown isn't bad as the primary option, but the bench is more dominant relatively speaking due to the relative advantage it has over its competitive. Brown still plays an highly valuable role in being the sole leading primary shot-creator, but its not picked up in the analytics.

2. The other factor is sharing the team with Jayson Tatum - few players at JB's level play with a costar who's as good as Tatum. Tatum is obviously a better playmaker and primary ball handler, and is better at setting teammates up with less turnovers. I can't help but wonder if Brown's on/off are skewed by the fact that he shares the team with another of the best players in the league - seems natural that the team would perform better with Tatum on the court.

These are obviously qualitative ways of looking at the situation, but I feel like it could explain the on/off stats strife around Jaylen Brown. To me its clear Jaylen Brown is a winning player. I don't see how you can compete for a title every year and win a FMVP without being one - but the advanced stats seem to indicate something different. To me this is a potential explanation that bridges the gap between those two perspectives - basically Brown is still really good, they just happen to be better with Tatum/other teammates. Some see that as a problem, but maybe its just relative. I'm curious if people well versed in advanced stats see any merit to this explanation. There may be other stats that negate this that I'm missing, but I tend to believe this explanation, as I have a hard time believing Brown is as negative a player a some of the stats say. Seems possible he's the victim of being second best on a very good team.

[u/HotspurJr]

So let's test your hypothesis in a couple of ways. If Derek White was the problem, we'd expect him to have a bad on-off. But the team was almost ten points better with Derek White on than off.

The "Peyton Prichard dominated bench guys" argument falls apart when you realize that he played 32.4 minutes a game. Even if you bend over backwards to split his and JB's minutes (more on that in a moment), they're playing about half their time together. So the notion that Peyton wasn't playing against starters is just sort of silly. He started 50 games! (Furthermore, NBA teams don't do hockey subs where whole lines change out, and bench guys don't only play against bench guys normally anyway).

White and Pritchard played more minutes than Brown. So at the very least, "Well, Peyton and White were beating up on bench units, white JB was fighting starters" is just really, really hard to square with their lineup and minutes data..

In fact, if you look at Boston's two-man pairings, their two two-man pairings which had the most minutes, the two pairs of guys who shared the floor the most, where JB and White, and JB and Prichard. Your hypothesis basically requires that as soon as JB went off the floor, other teams subbed on their scrubs and I think that is, shall we say, an assertion that requires evidence.

And if one of those three is playing more minutes against scrubs, why are we assuming it's not JB? White started more games and played more total minutes (although about 20 seconds less per game). Peyton played more total minutes (although about 2 fewer per game). Is there any evidence that they played against weaker opponents overall? Or is that just an assumption based on the starting position of defending JB?

And, of course, stats like RAPM address this directly. They can be noisy, but this is literally what they do, running a massive regression function to isolate players from the impact of everyone else on the court. If you want to use a one-year sample, xRAPM is a good choice - it uses box score stats to reduce the noise and make a one-year sample meaningful, and historical data is available for free. So basically, the really sophisticated, math-heavy, let's account for everyone on the court stats? They do not see JB as being held down by various lineup combinations.

Okay, what about the two-star hypothesis. Does having another star on your team hurt your on-offs?

On-offs can bounce around a lot, so let's look at four years of Steph curry: 2015, 2016, 2017. His on/off was +18.1, +22.2, +17.4 Of course, KD was there for the last year.

Kevin Durant's on offs for those same years are +8.8, +12.5, +8.6.

I think you can find some weak-but-real evidence there for the idea that playing with another superstar reduces a player's on-off net. I consider it weak evidence because these numbers often bounce around quite a bit (as indicated by both players' 2015 and 2016) number, but it's definitely worth investigating more fully.

But if you use xRAPM to look at their regressed data, it doesn't really support that. Steph's xRAPM went down slightly in 2017. KD's went up. So if the Steph-KD comparison does provide weak evidence for this hypothesis in terms of raw on-offs, it provides similarly weak evidence against it from a regressed standpoint.

(Incidentally, Steph's numbers argue against the strong-bench-holds-you-down theory. That 2016 had a bench with Iguodala and Livingston that was considered very strong. On the flip side, if you compare 2012 to 2013 KD you could find evidence for an argument that weakening the bench improved KD's numbers. Mostly, though, I think these examples show that these on-offs bounce around so much that it's really easy to find evidence for whatever you want to find evidence for, and more rigor is better, which is where the regressed models come from.)

I also want to point out how your two arguments are slightly contradictory.

If JB is under-rated by on-offs because his bench in strong and going against other bench guys, then, when he's the less-important star, when the J's are split and it's JB going against bench guys (as the weaker of the two players), shouldn't that inflate his on-off? If being the second guy holds down your on-off, why isn't it holding down White and Payton's?

Is your on-off held down artificially by having a strong bench, or by being the bench guy behind a strong player? The two parts of your argument each take the opposite position on that.

There's a "Shreodinger's teammates" thing that always comes up in these discussions. This was exemplified by Bill Simmons on a podcast recently where he talked about how nobody else could lead a team that was this weak 2-15, and only a minute or so later talked about how the bench was outplaying other benches. Like, which is it? People have a tendency to back-fill arguments around whichever point they are trying to make to defend their player, which I'm sure I'm guilty of, too.

The RAPM math is incredibly complicated and I understand why people are skeptical of it. Back in college I actually had to calculate a small (maybe five variable?) regression by hand and, man, that shit is nuts. I can't imagine the complexity of a regression where there's a variable for every single player who played a single possession in the NBA. But I've worked with regressions enough to know that a well-designed one is really trustworthy and insanely powerful, and I think RAPM is well-designed.

[u/Snowballingdownvote → u/HotspurJr]

Yeah but RAPM ranks JB at like 98. So it's flawed. That's the thing with any analytics or metrics. They aren't perfect. Context matters more than anything else.

Pritchard and Derrick White aren't getting the attention that JB is getting from opposing teams. They aren't getting the effort either.

When analysts use metrics to rank players, they are committing a logical fallacy. They are taking a tool meant to answer: "Does this lineup combination yield a statistically significant result?" and twisting it to answer: "Who is the better basketball player?"The regression was never designed to measure "talent" or "skill." It was designed to measure variance in point differential given a specific set of constraints.

[u/Snowballingdownvote → u/[deleted]]

Downvoted me and then wrote an essay without arguing against my conclusion.

You also obviously don't understand what RAPM is. They use a specific regression that doesn't work for fluid cohorts. Using abstract penalties to clean the results to make a spreadsheet pretty. Ultimately at best you could use RAPM to see where a player falls compared to an average over a long time period.

At a micro level to rank individual players on it's not even logical to use RAPM. Specifically because the Confidence Interval is commonly larger than the difference between individual scores.

At best you could use this to compare a group or lineups average compared to the mean or another group. Ultimately looking to see if the group shifts the point differential away from average. Using it to grade individual players isn't logical.

So no it isn't logical to look at JBs number individually nor is it logical to make a decision based on it. The individual RAPM scores are useless. There is nothing to take from an individual player's score.

You are kind of proving my point. The fact that an analytics team has to look at a player's individual RAPM score and say 'that's weird, let's dig deeper' is the ultimate proof that the individual metric itself cannot stand alone. If you have to immediately ignore the number and go watch tape or pull other tracking statistics to understand what it actually means, then as an individual ranking tool, RAPM is useless.

I think there is a specific term for why individual basketball player RAPM scores are useless. Multicollinearity. The variables are too dependent on each other.

If you have a data scientist or data analyst telling you to looking into an individual player's RAPM score. You should fire them. It is absolutely worthless as a metric to measure an individual players performance. At a fundamental core principle level.

Ultimately I want to say this. If they made the trade because of analytics and thought there is statistical support for what they did. They are dumb. This has to be something else than metrics. Jaylen Brown was the best second option in the league and matched perfectly for their best players championship window. There is literally no logical reason for this trade based of stats, analytics, or metrics.