Is The NBA Cup Exciting?

Plus an interview with a LEBRON stan

Dec 05, 2024

G’day mates. I’m writing to you from Sydney, Australia. Please note that while I recover from jet lag and try to avoid getting hit by a car while crossing the street, posts may arrive in your inbox at irregular times. If you have any Sydney recommendations or a basketball run I can join, get in touch.

When the NBA announced the inaugural in-season tournament the hope was that it would raise the level of competition and make games more entertaining during an otherwise mundane stretch of the season. If the NBA could capture some playoff magic during the early portion of the regular season it would be a win for fans and the league as a whole.

Now that the group stage of this year’s in-season tournament (now called The NBA Cup) has concluded, we have some data to see if the games have been any good.

Over on inpredictable.com, Mike Beuoy publishes a page called the NBA preCap every day that estimates how entertaining the games from the night before were. It’s a great resource for helping anyone decide what game to watch the next day without spoiling the outcome. It’s also a great resource for helping us figure out if these Cup games have been entertaining.

One of the key stats Beuoy tracks is how “exciting” each game is. Beuoy defines excitement as how far the win probability “traveled” over the course of the game. A game in which both teams appeared to have the upper hand at multiple points would be very exciting. Whereas a game that was over in the first quarter would be very unexciting. To put it simply, the more zig zags a win probability graph has, the more exciting the game was.

This season’s most exciting game according to Inpredictable was the overtime matchup between the Philadelphia 76ers and the Indiana Pacers. Lots of zig zags.

Meanwhile, this year’s least exciting game was the game in which the Cleveland Cavaliers trounced the Golden State Warriors en route to their 10th straight victory to open the season. Barely a zig or zag in sight.

If the NBA Cup is working as intended, then the Cup games should be more exciting.

The table below shows the average excitement, margin of victory, and game duration of NBA Cup games vs non-Cup games from this season and last season. I’ve excluded the knockout games from last year and limited the non-Cup sample to those games that were played during or before the same time of the group stages.

Including last season, there have been 120 group stage NBA Cup games and 489 comparable regular season games. Not a huge sample, but not nothing either.

On average, Cup games have been less exciting than their non-Cup counterparts. While the difference in average excitement scores isn’t large, it’s noteworthy that it’s even close. The argument for the NBA Cup rests on the notion that the games are supposed to be more competitive. The fact that we can’t tell if they are leads one to wonder whether it’s working as intended.

NBA Cup games also take longer to complete compared to non-Cup games. This difference is probably due to the fact that there are multiple national TV games each night of the group stages, which means more dog and pony show material compared to your average regular season matchup. Regardless, The NBA Cup is giving us less exciting games that take longer to complete. Not a great formula for fan engagement.

Curiously, the average margin of victory has been closer in Cup games than in non-Cup games. That’s surprising given that teams have an incentive to run up the score during the group stages since point differential is one of the first tiebreakers for advancing to the knockout rounds. This could suggest that teams haven’t optimized their strategies for advancing out of the group stages — or maybe they just don’t care.

I’ll end by saying that whether NBA cup games are exciting probably doesn’t matter much. The games are going to be played either way and if they suck no one is worse off for it. Meanwhile, the knockout games of the NBA Cup last year had an average excitement score of 6.8, so at the very least we should be in for a better than average slate of games next week when NBA Cup action resumes.

Times Up

Net Rating is the first thing to look at to gauge how good a team is. But like any single number, Net Rating obscures and flatten the more interesting details that make a team unique.

For example, Net Rating tells us nothing about how often teams are up (or down) big. Two teams with the same Net Rating can spend different amounts of time leading or trailing by double digits.

The chart below shows how often teams are up, down, or within one possession of their opponent. I’ve sorted teams by the percentage of game time they spend up four points or more.

A few thoughts:

The Knicks lead the league in time spent up +20 points. They’re up by 20 or more points a whopping 20 percent of game time (the next closest is the Grizzlies at 13 percent). Last year, they were up +20 points only eight percent of the time. The argument in favor of trading for Karl-Anthony Towns and Mikal Bridges was that it raised the team’s ceiling. Early indicators suggest it did just that.
The Hornets, despite being a bad team, are rarely down +20 points compared to other bad teams. I think you can attribute a lot of this to good coaching. Keeping players motivated enough to not drop the rope even when they’re likely going to lose is a difficult, but important part of a coach’s job. Charles Lee has succeeded on that front.
The Wizards are ass.

A Refreshing Interview with Krishna Narsu, creator of LEBRON

To round out my series of Q&As with the creators of the most popular all-in-one player impact metrics, I reached out to Krishna Narsu, creator of LEBRON1.

Narsu is from Rhode Island and grew up a Red Sox and Patriots fan. He made it a point to tell me he was never a Celtics fan. An internship with ESPN jumpstarted Narsu’s interest in sports analytics. Initially, he started off writing about football analytics. Eventually Narsu made the jump to basketball analytics and was a regular contributor at Nylon Calculus from 2014 to 2019.

Now, Narsu is part of the team over at the bball-index (BBI) which has created a host of data products to help fans better understand the league.

I talked to Narsu about the decision to name his metric LEBRON, his thoughts on three-point defense, and what he can’t live without during the NBA season.

This Q&A has been edited for length and clarity.

F5: How do you test to see if LEBRON is keeping up with the EPMs and DARKOs of the NBA analytics world?

KN: It is an uphill climb because EPM and DARKO are great metrics. They are the Steph Curry of metrics. But maybe LEBRON is better?

I am pretty much always testing how our metrics do. I actually have published tests here, here, and here. Our metrics are not always first but I think it’s important to be honest about your metric. And for me, it’s just about always trying to improve the metric. That’s the fun part about developing a metric.

Also going to admit that I think my testing is flawed. The best way to test how good a metric is would be to predict game level outcomes. You do need a multi-year metric with values for each day to be able to conduct that test though. That is the next test I would like to attempt at some point.

I’ve actually been working on a new metric (called BBIPM or BBI Plus-Minus) which would incorporate our talent grades at bball-index plus some play-by-play stats in the box score prior. It’d be the same structure as LEBRON but a big improvement on LEBRON. So keep an eye out for that. The goal is to have this become our flagship metric.

I like a lot of the stuff bball-index out on social media but a lot of it also feels black-boxy. Why should anyone trust that these types of metrics have merit?

That's a very valid question, and one we welcome! In addition to many stats NBA fans will be familiar with, we've branched out into a realm of less traditional metrics that attempt to quantify skill sets. We know the same player can be varying levels of impactful based on how well they do their jobs on offense and defense, as well as scheme and alignment fit, align with their skill sets. By attempting to quantify the skill sets themselves, as well as impact, we're then able to open new doors looking into player optimization, skill age growth curves, and role fit.

Dean Oliver once told me "it's always better to try to measure something than to not do it at all." That's what we attempt to do. Almost all of our talent grades are highly correlated year to year, though I realize that alone doesn’t validate a metric's merit.

Current and prospective BBI users will be happy to hear we've invested substantial time into developing a comprehensive glossary of 692 definitions for metrics found at the site. As we re-launch on a new website (stay tuned), those definitions will appear when users hover over stat names. Explainer videos, podcasts, and articles are and will be a focus moving forward as we attempt to socialize concepts that are familiar to basketball fans but new to the data. We've also named metrics in ways with strong face validity whenever possible to make understanding them a bit easier.

Do you have any regrets about naming your metric LEBRON.

Yes, absolutely. I you are going to name a metric after a player, you definitely should not name it after the most popular player. It can get very confusing.

But it was fun brainstorming backronyms. There’s so many jokes and memes you can do with a metric named LEBRON. And I guarantee you those jokes and memes are better than DARKO or 538’s now retired CARMELO. But the end comes for us all and if I did have to do it again, I would call it BBI Plus-Minus which as I mentioned earlier, will be our future improved version of LEBRON.

Do you have a favorite guilty pleasure player? Maybe someone that doesn’t grade out well in LEBRON but you like watching nonetheless

Tyrese Maxey. He just seems to always be having fun on the court and his bucket getting is fun. All of last year was me asking myself, “why is Maxey’s LEBRON not higher?” So instead, I’d just use his EPM in any arguments. Gotta serve your agendas right? In all seriousness tho, I do understand why Maxey’s LEBRON is not higher. LEBRON tends to favor great playmakers and Maxey is a bit lacking there.

Are there any strategies (in-game or otherwise) that you wish teams would try more?

It always drives me crazy when I see teams that are up three that don’t foul. It just seems like the most obvious correct strategy. And yet, it’s very boring to watch and when teams do it, the end of games feel like they take 20 minutes. Take that Cavs-Celtics game for example. I swear it must’ve taken 5-10 minutes for the last 20 seconds to be played. And yet while I was watching, I was like “Yes, the Cavs are playing this perfectly!”.

I think you’re firmly on the side of three-point defense isn't real. What would you have to see to change your mind on that topic?

I don’t want to say I’m firmly on the side of 3-point defense isn’t real. I just think it’s effect gets overstated and I do think it makes sense to correct for it (i.e. like the luck adjustments we do in LEBRON).

The one thing I would love to see is what is the impact of contests on threes? Especially from longer defenders.

In prior research, I have found there is some effect but also the majority of threes did not fit that definition and I think there is much better data now.

I think Todd Whitehead has had some interesting research recently so I’m definitely open to changing my mind as we learn more. I also think some of these studies done at Nylon Calculus from 7-8 years ago probably should be updated with newer data given the three-point attempt boom.

Is bball-index your day job?

I am trying to make it my day job. We have an exciting merger coming up with FanSpo so our site design will hopefully be a ton better now and it should be a lot easier to use. And eventually, I’m looking forward to being able to integrate our metrics into the FanSpo trade machine. I think there’s a lot of potential there besides showing team A gained 1.1 LEBRON WAR from this trade.

Whats one thing you cant live without during the NBA season.

pbpstats.com. I’m just always on the site. And I also have to mention I absolutely love the Thinking Basketball videos. I’m so starved for some good basketball video content and no one does it better than Ben Taylor. Also really enjoy Sam Vecenie’s film breakdowns on YouTube.

Luck-adjusted player Estimate using a Box prior Regularized ON-off.