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Analyzing “Luck” in College Basketball: Part 1

BasketballCollege basketball stat guru Ken Pomeroy uses advanced metrics to rank every NCAA Division I basketball team. Amongst the numerous statistics he tracks is one called "Luck."

This statistic is calculated as the difference between a team’s actual winning percentage, and what one would expect their winning percentage to be based on how many points they score and how many they allow.

What it really boils down to is close games. In theory, you should win about half of your close games and lose half. If you win most of your close games, you'll have a high luck statistic in the Pomeroy Ratings. Lose most of your close games, and your luck statistic will be low.

For example, take the Penn State basketball team. Out of 351 teams, they are ranked 333rd in Pomeroy’s luck statistic. And not surprisingly, they are 1-5 in 1-possession or overtime games. The most recent gut punch came last weekend, when Purdue hit a game-tying 3 pointer with seven seconds left, but only because the refs didn’t see Purdue's coach trying to call a timeout. Penn State then turned the ball over and fouled Purdue with 1 second left. A made Purdue free throw sent Penn State to their 5th loss in a close game.

But there are two ways to look at this. On the one hand, Penn State got unlucky that the refs missed the timeout and that Purdue hit the 3 (as a team, Purdue makes only 34% of their 3 point attempts). On the other hand, Penn State made its own bed by turning the ball over and then fouling. That wasn’t random luck, it was something they controlled. Perhaps the pressure is too much for them to handle, and that is why they are losing most of their close games.

But my curiosity isn’t just about Penn State. I want to look at the larger picture. Are close games really just completely random? Or do teams that continuously win close games have a “skill” for doing so, while teams that continuously lose close games do so because they can’t handle the pressure? With the help of Pomeroy’s luck statistic and Minitab Statistical Software, I plan on finding out!

The Luckiest and Unluckiest Teams in the Country

Through games of Sunday, January 19th, I collected the 20 luckiest and unluckiest teams in the country according to Pomeroy’s luck statistic. I also collected 20 teams right in the middle, with their luck being just about 0. I named the 3 groups “Lucky,” “Unlucky,” and “Neutral.”

For each team I noted their record in games decided by 6 points (2 possessions) or less, or games that went into overtime (regardless of the final score, since at the end of regulation it was obviously a close game). I also split out games decided by 3 points (1 possession) or less. Again, all overtime games were included regardless of the final score.

Each Lucky/Unlucky/Neutral group had over 100 games in their “2 possession” sample and at least 60 games in their “1 possession” sample. You can get all the data here (if you do look at the data, a final score margin of 99 means the game went to overtime).

Okay, now that the boring part is out of the way, let’s see what our data looks like!

Describe

Describe

It appears that the luck statistic does exactly what it says it should do. Lucky teams have a great record in close games, while unlucky teams have a terrible record in close games. And sure enough, teams in the middle have about a .500 record in close games.

We can use a dotplot to visualize the records of every team in the sample.

Dotplot

Dotplot

At the individual team level, the same trend holds up. Unlucky teams are terrible in close games. We see that in 2-possession games, not a single unlucky team has a winning percentage higher than 33%. And even worse, 12 of the unlucky teams haven’t won a single game decided by 1 possession or that went into OT! Combined, those 12 teams have a record of 0-30 in 1-possession or overtime games!

And one more quick note about the unlucky teams: I said I collected 20 teams in each group (and I did), but if you count the green dots you'll notice there are only 19 unlucky teams. That's because despite being the 6th unluckiest team, Dartmouth didn't play a single game decided by 6 points or fewer. Ergo, they don't have a winning percentage in close games yet this season. They are 0-4 in games decided between 7-10 points, so I guess that's unlucky? I dunno. Sometimes statistics are weird.

Anyway, on the flip side, lucky teams were very good in close games. Other than Utah Valley (who was ranked #17 in luck despite going 3-4 in 2-possession games), all the lucky teams won at least 60% of their 2-possession/OT games. And when you look at 1-possession or OT games, 9 teams were undefeated! Combined, those 9 teams have a record of 25-0 in 1-possession or overtime games!

Lastly, as expected, our neutral teams are mainly grouped in the middle.

And because I’m sure you’re dying to know, according to Pomeroy the luckiest team in the country is...Nicholls St! What? Who are they? I guess that was kind of anticlimactic. How about the unluckiest team in the country? That would be Temple! So don’t worry Penn State fans, not only are you not the unluckiest team in the country, you’re not even the unluckiest team in the state of Pennsylvania.

Wait, Weren’t You Going to Determine if Close Games were Luck or Skill?

Oh right, about that... We’ve taken 60 different teams and shown in the 1st half of the NCAA basketball season (okay, we’re a tad more than halfway through but close enough) a third of them are really good at wining close games, a third are really bad at it, and a third are pretty average. Now we’re going to see how those same 60 teams do in the 2nd half of the season. If there is skill involved at winning/losing close games, the unlucky group will continue to lose while the lucky group will continue to win. But if it is truly random, we would expect all three groups to look more like our “Neutral” group did above. That is, despite how good or bad your close game record is at this point, you’re still going to win about half of your close games going forward.

So if you were expecting an answer anytime soon, I apologize (hey, it does say “Part I” in the title!). But make sure to check back in March when we can see how all of our teams did. Until then, let's hope those unlucky teams can start turning things around so they avoid having tweets about them like this.

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