NBA mailbag: Could LeBron’s suspension spark success for Los Angeles Lakers?

Can a team fight its way out of a slump?

When LeBron James was ejected from Sunday’s Los Angeles Lakers game against the Detroit Pistons for striking Isaiah Stewart in the face, sparking an extended on-court confrontation as teammates and coaches tried to restrain Stewart from seeking out retaliation, it came with the Lakers down 12 in the third quarter after losing their previous three games.

Without their star, the Lakers rallied for a 121-116 win and coach Frank Vogel cited the altercation between James and Stewart as a possible turning point for the team.

“To me, it’s one of those things that can change the momentum of your season,” Vogel said. “To see guys rally around a teammate that just got ejected like that in a strange circumstance. Played with incredible guts.”

That leads to this week’s mailbag question looking back on past NBA fights that have resulted in suspensions like those for both James (who missed Tuesday’s loss to the New York Knicks) and Stewart (who was suspended for two games) to see what happened to the involved teams thereafter.

Throughout the NBA season, I answer your questions about the latest, most interesting topics in basketball. You can tweet me directly at @kpelton, tweet your questions using the hashtag #peltonmailbag or email them to [email protected]

“Did teams that were involved in a fight go on win streaks afterward? Did it serve as motivation?”


— Adam

To answer this question, I used a combination of Patricia Bender’s invaluable compilation of fines and suspensions (up through 2017-18) and data from for the past three seasons.

From those sources, I identified 37 teams that had players suspended over the past decade as a result of on-court altercations that involved both teams, not counting suspensions involving referees or hostile acts during the course of game play. (I also threw out a handful of suspensions within the final 10 games of the regular season since any effect would be more difficult to determine.)

For those 37 teams, a handful of which had multiple players suspended (usually due to players coming off the bench during an incident), I looked at their winning percentage over the course of the season and in the 10 games before and after the date of the scuffle.

Lo and behold, there actually was a small bounce after teams had a player suspended. Over the course of the season, these 37 teams played at a .503 level. During their next 10 games post-altercation, they won at a .519 clip. That’s somewhat surprising given they lost a player to suspension for at least one of the 10 games.

Now, before coaches start instructing their players to think like hockey enforcers during a losing streak, it’s worth noting how modest this effect is. On average, it translated into .13 greater wins per team over the subsequent 10 games, so the odds are about 1 in 8 a team could expect even one win of benefit. And naturally, an effect so modest is likely to be the result of statistical randomness rather than a real trend.

It was interesting to note on the flip side that, for teams that were at least 10 games into the season, they had won at a below-average .481 clip over the 10 games prior to the incident. So there might be some element of frustration involved in altercations.

Of note, the Pistons play at the Lakers Sunday (9:30 p.m. ET).

I gave a short answer to this one on Twitter but figured it’s worthy of a fuller explanation.

Plus-minus data is great in theory because it incorporates everything that happens on the court, even what is difficult to count (though that group of contributions is smaller in the camera tracking era) and doesn’t rely on scorekeeper judgment as some box score stats do (primarily assists, where scorekeeper bias can have an important influence).

The downside, of course, is that what happens with a player on the court isn’t solely a function of that player’s contributions. It’s also about the other four teammates and five opponents as well as sheer statistical randomness. In an individual game, those factors can carry an ineffective player to a great-looking plus-minus, which is why critics of single-game plus-minus are right (but wrong that this is some sort of indictment of analytics).

Over the course of a season, the opponents a player faces should even out, as does much (though not all) of the statistical randomness. But even over that large of a sample, a player might typically play with or opposite the same teammates depending on the consistency of his team’s rotations. That can make it difficult to disentangle their contributions, which helps explain why adjusted plus-minus data is unreliable over a single season. (The current technique, known as regularized adjusted plus-minus, helps with this.)

Part of the way modern all-in-one statistics have achieved greater predictive power is by combining more stable box score stats with the noisier plus-minus data. We can do this subjectively, too. For example, the Denver Nuggets scoring a lot more frequently with Nikola Jokic on the court is no surprise given the reigning MVP’s skill set. It matches his individual output.

Smart having a key impact on offense is more unexpected given his own inefficient scoring. Smart might be the Boston Celtics‘ best passer, certainly, but we can also look at his mixed track record of impact on team offensive rating and effective field goal percentage and be somewhat skeptical. I like the on-off pages on Cleaning the for this purpose because the color scale shows at a glance what kind of effect a player has had throughout his pro career and also isolates which of the four factors on offense and defense contribute to it.

When a player has a years-long track record of on-off impact in a certain category, that’s probably a good predictor. (Smart is like this in terms of the Celtics forcing turnovers, which matches up with his own steal rate.) An outlier 20-game impact, like Smart’s on offense this season, is much more likely to be fluky.

“What is with all these double-digit leads being blown? Is it just me or is the number abnormally high so far this year? If it is indeed high, are there any reasons you can point to or just a wild stretch of randomness?”

— @jimmytoddy

Thanks to ESPN Stats & Information research, here are the records for teams with double-digit leads over the past six seasons (2021-22 through Tuesday’s games) in the chart:

This season’s winning percentage at 75.3% is the lowest in the past six years, though it’s in the same ballpark as what we saw in both 2016-17 (75.8%) and 2019-20 (75.7%). From that standpoint, last season’s winning percentage (77.6%) for teams that led by 10-plus points at any point during the game was much more the outlier.

The relatively flat trend line for winning percentage with a double-figure lead contrasts with the increase we’ve seen in big comebacks, as I wrote about with Baxter Holmes during the 2019 playoffs. I think the difference is 10-point leads have always been reasonably precarious in the NBA, whereas leads of 20-plus were much safer before the league scoring average increased in the past decade.

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