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You’re Nuts: Which statistic best measures how “good” a team’s offense is?

There are so many different ways to analyze scoring, but some methods leave out crucial context.

Syndication: The Columbus Dispatch Adam Cairns/Columbus Dispatch / USA TODAY NETWORK

Welcome back to another rousing rendition of “You’re Nuts” — basketball edition. With the college basketball season officially in the rearview mirror, we have the freedom to branch out and hit on some more abstract topics that we don’t have time to break down during the season. This week, we’re talking offense — specifically, which statistics illustrate a good offense and which fail to paint the complete picture.

Last week, we debated which of the Final Four teams would win the national championship. Connor picked Duke, while Justin picked Kansas. Justin was correct in that Kansas did win the natty, but Connor’s Duke pick won the poll, and therefore he wins the vote.

After 44 weeks:

Connor- 20
Justin- 16
Other- 6

(There have been two ties)

As stated earlier, we’re talking about offense and the statistics that describe them this week. Between points per game, field goal percentage, true field goal percentage, offensive efficiency, and many more, there are so many ways to measure an offense’s effectiveness. However, outside factors always play a role. A team’s pace of play may impact one measurement. A team’s rebounding or ball-handling (or lack thereof) could impact another. There will always be pushback when supporting an argument using one specific offensive statistic, because there’s a caveat to nearly every one.

So this week we’re each picking one offensive measurement and explaining why it’s the superior way to encapsulate a team’s offensive output. Justin went with a more black and white count, while Connor chose one of the more advanced ways of measuring offense. What say you? Do you think there’s one great way to judge a team’s offense, or do we need to take all of these things into account holistically?

Today’s question: What is the best way to measure how good a team’s offense is?

Connor: Offensive efficiency rating

NCAA Basketball: NCAA Tournament Second Round-Ohio State vs Villanova Geoff Burke-USA TODAY Sports

For those who don’t know, offensive efficiency or “adjusted offense” as Ken Pomeroy calls it, is the amount of points a team scores per 100 possessions. Last season, Ohio State was No. 13 in the country in adjusted offense, scoring 115.5 points per 100 possessions. Simple math tells you that Ohio State averaged 1.15 points per possession last season. The only two Big Ten teams with more efficient offenses than the Buckeyes last season were Purdue (121 points/100 poss.) and Iowa (120.5 points/100 poss.)

If you look at points per game, the Buckeyes averaged 72.8 and were No. 126 in the country. Does this mean that teams like Stony Brook (121), Idaho (118), and Central Arkansas (116) were better offensive teams than Ohio State? Well, no. That’s why offensive efficiency is such a nifty statistic.

Offensive efficiency successfully isolates a team’s offensive ability away from things like tempo (possessions per game, how fast a team moves, etc.) and defense/rebounding, which can impact how often a team has the ball and is actually able to score. It literally has tunnel vision on one thing only — how successful a team is at scoring the ball when they have it.

For a team that moves pretty slowly like Ohio State (No. 289 in tempo or game speed, whatever you want to call it) they’re never going to lead the conference in points per game. Their offense is predicated on getting the best look possible rather than speeding up the game and putting an opposing defense on their heels before taking the first possible shot.

The Buckeyes also struggled mightily with defensive rebounding last season, meaning that their opponents got the ball back more often and — to use a football term — dominated time of possession. When Ohio State had the ball they were scoring very efficiently, but the problem is that they did not have the ball in their hands as often as they wanted. You can criticize their rebounding certainly, but this was separate from their offense.

So in essence, offensive efficiency is a great tool to look at offenses because it cuts all the fat off the edges and focuses solely on how well a team puts the ball in the basket when given the chance to do so. That’s why there are teams who score a ton of points who aren’t as highly ranked in adjusted offense, as well as teams who don’t score in big numbers leading in efficiency — it’s all about what you do with the opportunities you have.

Justin: Points per game

Arkansas v Gonzaga Photo by Steph Chambers/Getty Images

Look, I get it. Analytics are important and I like them too. And offensive efficiency matters because it brings in multiple factors when analyzing the offense. But I am going to give a galaxy brain take here: If you score more points than the other team, you win the game. Simple as that.

I obviously realize that other things play a role in that and I like the analytics and the numbers just as much as anyone. However, points per game does mean more than people think. It shows consistency, it shows adapting to different defenses and it shows that as an offense, you can put up points on just about anyone.

The one caveat that you can give is the strength of schedule that a team faces. It easier to score points in the West Coast Conference (yes, Gonzaga) than it is in the Big Ten or the SEC. But in Division I college basketball, guys are talented in every conference and it is tough to score, no matter where you are.

In 2021-22, of the top 10 scoring offenses in the country, seven of those teams were tournament teams. Of the seven, three of them were top two seeds (Gonzaga, Arizona and Duke) and one team made the Final Four (Duke).

Scoring leads to winning and winning is good. Points per game is a simple stat, but it does the trick.


What’s the best way to measure a team’s offensive performance?

This poll is closed

  • 60%
    Offensive efficiency (Connor)
    (15 votes)
  • 32%
    Points per game (Justin)
    (8 votes)
  • 8%
    A different stat/method
    (2 votes)
25 votes total Vote Now