4 Comments

Summary:

The first week of the NCAA tournament is in, and the results would suggest that Nate Silver is yet again the man when it comes to predicting the things Americans care about.

Nate Silver FiveThirtyEight SXSW speaking election data

This story was corrected at 4:17 p.m. because the author incorrectly stated that Michigan State, one of the Final Four teams selected by the SAP model, had been eliminated from the tournament.

OK, so your NCAA tournament bracket has officially been busted. Don’t feel so bad. ESPN college basketball analyst Jay Bilas, stat-geek superstar Nate Silver and even SAP’s vaunted predictive analytics software all missed the upsets, too. So did President Obama.

Three of the four correctly picked 11 of the Sweet 16 teams, while Bilas correctly chose 10. But despite the similariy in results between men and models, I’d follow Silver’s model-based forecast every time. Not only is it accurate, but it stands to make people a lot of money.

Just to be clear, though, Silver doesn’t actually pick winners and losers (at least not publicly, as far as I can tell). Rather, he uses a model that takes into account a number of variables — including a handful of popular computer rankings — and produces the probability of each team advancing through each round of the tournament. That’s what makes his forecast so effective if you’re a betting man: It’s easy enough to pick the winner and most of the final four by just choosing the top seeds (I’m looking at you, POTUS), but the way to accel past everyone else in points is to spot the Cinderellas.

If I were ESPN, I’d pay Silver a boatload of money to come on TV once a year and present his forecast to a March-Madness-obsessed nation. I’m fairly certain the network could extend the broadcast out to about three hours and charge Super-Bowl-like advertising rates. Here’s why.

It’s the probabilities, stupid

As I was saying, anyone, including Silver, can spot the best teams in the tournament by watching enough basketball, settling on some important data points to analyze or just following the NCAA’s seeding. Here are the seeds my experts, data analysts and the leader of the free world chose for the Sweet 16:

  • Bilas: 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 5, 5
  • Obama: 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5
  • SAP: 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 4, 5, 5, 6, 7, 8
  • Silver: 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5

Here are the actual seeds that advanced to the Sweet 16: 1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 6, 9, 12, 13, 15.

SAP's mid-seed-heavy bracket

SAP’s mid-seed-heavy bracket

The smart money is always on the higher seeds from a pure probability standpoint (although I have no idea how SAP built its model to get so many 5-8 seeds in the Sweet 16). But strange things can, and often do, happen in the NCAA tournament. This year, those strange things are called Wichita State (9-seed), Oregon (12-seed), LaSalle (13-seed) and Florida Gulf Coast University (15-seed).

So why am I so high on Silver if his Sweet 16 probabilities were just as off-base as the two non model-based human brackets and SAP’s model-based picks? Because if I were looking for a few upsets, he might have helped me spot them. Here some of his notable projections for lower-seeded teams most likely to advance:

  • Arizona (6-seed): 38.1 percent of reaching the Sweet 16 — they made it (SAP picked this correctly)
  • Florida Gulf Coast (15-seed): 3.3 percent chance of making the Sweet 16 — they made it
  • Oregon (12-seed): 17.5 percent chance of making the Sweet 16 — they made it
  • Minnesota (11-seed): 61.9 percent chance of winning its first game — it won (Bilas, SAP and Obama picked this, too)
  • California (12-seed): 32.8 percent chance of winning its first game — it won (SAP picked this correctly)

538bracket-3-blog480

And in my neck of the woods — Las Vegas — being smarter than the sportsbooks means big money. No. 12 Oregon and No. 13 LaSalle didn’t really sneak up on the oddsmakers (60-1 and 100-1 odds to make the Final Four, respectively), but No. 15 Florida Gulf Coast is paying out 1,000-1 should it reach the Final Four.

I wouldn’t count on that happening, though. Silver now gives those teams a 1 percent, 5.1 percent and 0.8 percent chance, respectively, of making the Final Four. Louisville, Florida and Indiana look like locks to make it, and one of them should win the tournament.

Men vs. models: Let’s call it a draw

If you’re looking at these selections as some sort of man-versus-machine competition, I don’t think you’ll find a clear winner. Although Silver comes out looking the best of the four brackets I analyzed, his projections aren’t that much different than Bilas’s picks. And although SAP’s picks fall apart in the end — two of its Final Four selections (including its national champion pick) are out — it did correctly pick a couple upsets. President Obama, well, he pretty much picked chalk. The jury is still out on SAP’s model, which has three Final Four picks alive but made what seems like a risky choice by choosing Michigan State over Louisville.

The better way to look at these results is probably as further evidence that man and machine need to work together more closely, something we highlighted heavily at our Structure: Data conference last week. Men create models, but men probably don’t crunch the numbers. And when there’s pride or money on the line, knowing which No. 15 seed has the best chances of making a run is probably what matters most.

Your chances of picking every upset without a little help: not good at all.

You’re subscribed! If you like, you can update your settings

  1. Derrick Harris Monday, March 25, 2013

    If I can add one caveat to this post, lest anyone think that knowing basketball teams doesn’t matter, it would be that information from someone like Bilas is probably more valuable if you’re in a place like Las Vegas betting on individual games against the spread. Predicting wins or Final Four appearances is one thing, but accurately analyzing point spreads seems to require some real knowledge.

  2. ESPN can hire all the Nate Silvers and all the supercomputers in the world to generate highly probable predictions. But as long as human greed and corruption can be a factor, then it won’t matter.

    Case in point: The recent global soccer rigging candle that just broke.
    http://www.huffingtonpost.com/2013/02/05/soccer-match-fixing-investigation-betting-scam_n_2622092.html

    Organized crime was fixing games. Who would of thunk?!? How long before we find that NCAA tournaments are also being manipulated. It doesn’t take much. Just a small number of corrupted players and refs will do it.

    Why anyone would bet as much as a dollar of their hard earned money on any such thing is beyond me. If you want to support your college team, then send your check your alumni assoc., not your bookie.

  3. They don’t need Nate Silver–Silver’s system is advanced but it hasn’t nearly performed the best over the last few years. If you want to highlight whose brackets have really excelled, look in one of two places. 1) Ken Pomeroy (kenpom.com); 2) the students at the Harvard Sports Analysis Collective (HSAC). Pomeroy and HSAC’s Survival Bracket have destroyed the competition.

    Really, what you need are good data and good models. These people just know how to get/make them, and they have the results to back it up.

    1. Thanks for the pointers. Admittedly, I don’t follow the sports analytics blogosphere too closely, but do follow Five Thirty-Eight. That being said, Nate’s a star now. So even if someone is better, Nate drives more ad revenue ;-)

Comments have been disabled for this post