Basketball Statistics Question: How Important Is a Team's "Momentum" Heading into the NCAA Tournament?
It’s March, which means it’s the time of year when the country's sports fans focus their gaze upon college basketball. And since there are still a few weeks until the brackets come out, people will be trying to determine which teams are poised for a deep run in the tournament. One of the criteria people use to determine a team's potential is “momentum.” Everybody says you want your team to be “peaking at the right time.” But is this really important? We just saw the Baltimore Ravens win the Super Bowl despite losing 4 of their final 5 regular-season games.
So how important is it for NCAA basketball teams to be on a winning streak going into the tournament? Let’s open our statistical software and do some data analysis to find out!
I took every single NCAA tournament team from the last 5 years and obtained
- their winning percentage in the last 10 games before the tournament
- their seed, and
- their number of wins in the tournament.
I also calculated their expected number of wins based on the seed. So seeds 9-16 are expected to win 0 games (unless they were in a play-in game, in which case I made it 1), seeds 5-8 are expected to win 1 game, 3-4 are expected to win two, 2 seeds are expected to win 3, and 1 seeds are expected to win 4 (any victories after they reach the Final Four are bonus).
But before we dive too deep into the data, let’s just see how often teams are “hot” coming into the tournament.
We see that in the last 5 years, only 14 teams have made the tournament with a losing record in their last 10 games. The team that lost 7 of their previous 10 was Villanova in 2011. Most teams in the tournament won 7 or 8 of their previous 10 games. And 21 teams have been as “hot” as you can be going into the Big Dance, winning each of their last 10 games.
Next, let’s use a Bar Chart to break down the winning percentages by seed to see if higher seeds are playing better going into the tournament than lower seeds.
Going into the tournament, 1 seeds are playing the best basketball, winning on average 8.6 of their last 10 games. This number drops as the seeds get lower, bottoming out at the 10 seed. However, things start to climb again as you get into the teens. This is because those teams represent smaller conferences, where often the team is given a poor seed despite a great record in their conference. For example, last year Detroit finished the year on a 9-1 streak which included a 20-point win in the Horizon League Tournament Championship Game. For their efforts, they were given a 15 seed and were promptly beat by Kansas in the first round by 15 points.
But do any of these winning streaks actually lead to success in the tournament? I’ll use Minitab to create a scatterplot between winning percentage in a team’s last 10 games and wins in the tournament.
The points appear to be randomly scattered around the plot. There doesn’t appear to be much of a relationship between tournament wins and winning percentage at all.
But wait...we just saw in the bar chart above that seeds 13-16 have a high winning percentage going into the tournament, but aren’t very likely to win any games. So I’ll remove them and plot the data again.
Again, the points don’t appear to fall in any pattern. I’ve pointed out some instances where teams have bucked the “you have to be peaking at the right time” trend. Last year Florida lost 6 of their last 10 games in the tournament, and then nearly went to the Final Four. The VCU team that went to the Final Four in 2011 actually lost 5 of their last 10 games going into the tournament. And the Connecticut team that won the national championship the same year lost 4 of their last 10. Sure, you can say they got “hot” during the Big East Tournament, where they won 5 straight games. But going into the Big East Tournament, they had actually lost 7 of their last 11 games, including 4 of their last 5. They looked about as bad as you can be going into their conference tournament, and yet won 9 straight games to win the national championship.
On the flip side, in 2010 Temple won straight 10 straight games going into the tournament and got a 5 seed. What did they do with all that momentum? They lost in the first round to Cornell by 13 points.
Let’s look at one more plot. This time, instead of just using tournament wins we’ll use “Wins over expected.” That is, how many wins the team got compared to what's expected from their seed line. High seeds that get upset early will have negative values, whereas low seeds that pull upsets will have positive values. And teams that perform exactly how they’re expected (16 seed losing in 1st round or 2 seed losing in the Elite Eight) will get a 0. I’ll also include all the teams this time.
And once again we don’t see any kind of pattern in the scatterplot. VCU and Connecticut are back again as examples that show you don’t have to be “hot” to make a big run. The 2010 Michigan State team is another example, as they went .500 down the stretch and then went the entire way to the Final Four (and 2 points shy of the championship game).
But it doesn’t hurt to be on big winning streak, either. The two Butler teams that made the championship game definitely won a lot going into the tournament. And the Davidson team led by Stephen Curry won 22 straight games going into their Cinderella run in 2008!
And there are times when winning streaks don’t mean much. The Kansas team in 2010 not only won 9 of their last 10, but actually won 32 of their 34 games that season! But that momentum didn’t help them as they bowed out in the second round to Northern Iowa.
And to drive the point home, we can use Minitab to calculate a statistic that will show the lack of association between winning percentage and tournament wins over expected. Since both variables are ordinal, we can calculate correlation coefficients by going to Stat > Tables > Cross Tabulation and Chi-Square, then clicking Other Stats and checking Correlation Coefficients for Ordinal Categories. This will give us a value between -1 and 1. Values close to 0 indicate no association between the two variables. The closer the value gets to -1 or 1, the stronger the relationship. Here are the correlation coefficients for the data in the scatter plot above.
Both values are just about 0, further emphasizing the point that there is no relationship between winning percentage in the last 10 games and NCAA tournament success.
So over the next few weeks, when you hear analysts say, “This team is peaking at the perfect time for the tournament!” or “This team isn’t making it past the first weekend with the way they’ve been playing recently,” know that it doesn’t matter. A team is defined by what they’ve done the entire season, not just what they’ve done recently. All that “momentum” doesn’t mean a thing come tournament time.
After all, they don’t call it March Madness for nothing!