Data and the Big Dance
The largest driving factor in business today seems to be one thing, data. What’s the data tell us? Do we have the numbers to back it up? Reminds me of the scene from the Graduate when Mr. McGuire is giving Dustin Hoffman’s character advice on the future, “I just want to say one word to you. Just one word. Plastics.” Companies will not make any decisions without the data showing the way.
And as much as I agree that data is a critical part of any business decision or marketing campaign, it shouldn’t be the only driving factor. Data will get you close but there still needs to be the “eye test.” Nowhere is that more obvious than the NCAA Basketball Tournament.
Every year thousands of people pour over data. They analyze RPI’s, SOS, won/loss records against common opponents, quality wins, bad loses, etc. in the hopes of being able to project a champion out of a pool of 68 teams. The irony is no matter how much number crunching they do; their brackets seem to always be busted by the end of the first weekend. How does that happen? What did they miss? How could the data be so far off? Simple. As accurate as data can be at showing general trends, it does not take into account the outliers and one-offs. Sometimes you just have to go with your gut.
1983 NC State Wolfpack
The Wolfpack finished the regular season with a 17-10 record. Not a stellar performance and one that left them only one path to the NCAA Tournament; win the ACC conference tournament and secure an automatic bid. They proceeded to do just that defeating North Carolina, the defending national champions, and Virginia, who entered the tournament ranked second in the country.
NC State entered the tournament as a #6 seed and proceeded to beat a #11 seed, #3 seed, #10 seed (who themselves beat a #2 seed), #1 seed, #4 seed and another #1 seed to win the championship. And the tournament only had 52 teams at the time, which meant any team seeded four or higher had an automatic first-round bye.
Final Four Seeds
The final four has featured all four #1 seeds only once in the past ten years. Twice during that time period all four #1 seeds failed to make it to the final four and in 2011 the Final Four consisted of a #3, #4, #8, and #11 seed. Either the tournament committee does a horrible job of properly seeding the teams or the teams are not playing to match the data.
Understanding The Data
Upsets are much more common in sports than general business. But relying solely on cold, hard facts without evaluating the human side of the equation can have similar results. For example when analyzing the pre-tournament data, knowing when and where teams played each other during the season, which players were injured or sick, how tired or rested the teams were coming into the games can have an impact on the outcome. The 1983 NC State team played most of the season without Dereck Wittenburg, their starting guard. Wittenburg returned just in time for the ACC Tournament and the team proceeded to run the table. It shows having the data is essential. Understanding when and how it was collected and what may have changed in that time period is pivotal.
So what does this mean when it comes time to fill out this year’s NCAA bracket? Not a whole lot. You can check the data, crunch the numbers, as well as understand the trends, and look for teams that are peaking at the right time. Or do what my son did one year, just look at the mascots and decide which one would win in a fight. His logic was no one beats a Spartan. Except apparently a Tar Heel. (Michigan State lost to UNC in the championship game.) Go figure.
