“Football Freakonomics”: Is Momentum a Myth?

The following is a cross-post from NFL.com, where we’ve recently launched a Football Freakonomics Project.

Is momentum a myth? That’s the question we ask in our latest installment of Football Freakonomics. It’s the kind of topic that academic researchers are increasingly interested in – and  the kind of topic that makes a lot of sports fans hate academic researchers.

Why?

Because they take all the fun out of our arguments! Do we really want to haul out a spreadsheet to talk about whether Mike Smith was a bonehead for gambling on 4th down? Or whether icing the kicker is a good idea?

As someone who has one foot in both camps (fandom and academic research), I can see both sides of the argument. In the case of momentum, however, I really want to know the truth – perhaps because it’s the kind of phenomenon that is harder to prove than most.

The best place to start is with a famous (for academia) paper from several years ago, called “The Hot Hand in Basketball: On the Misperception of Random Sequences.” As you can glean from that snazzy subtitle, the authors come down against momentum, arguing that a “hot streak” is really just a random sequence that we misperceive to be more meaningful than it is. 

Ever try flipping a coin 100 times? You’ll be surprised at how many long, unbroken sequences of heads or tails you get. It’s easy to mistake that for a pattern, suggesting some kind of meaning or momentum, but it’s really just a pure illustration of randomness itself. The fact is that if you get 10 heads in a row, the next flip is no more likely to be heads (or tails, for that matter).

And so it is, for the most part, with hot hands and hot streaks and hot quarterbacks. In our Momentum video, you’ll hear Toby Moscowitz, the academic co-author of Scorecasting, discuss how pretty much everyone in football believes in momentum. But, having looked at a lot of NFL data, Moscowitz reaches a sobering conclusion: “There is a much stronger belief in momentum than is warranted by what we see in the data.”

In other words, just because a team has driven down the field three times in rapid fashion to set up a dramatic comeback doesn’t necessarily mean the fourth drive is sprinkled with fairy dust.

Here’s the takeaway: we should be leery of announcers (and coaches and players and fans) talking about “the Big Mo” as if it were a twelfth man who suddenly snuck onto the field and is about to streak, uncovered, into the end zone.

Why, then, do so many of us believe that the Big Mo is a monster?

Consider one example in our video, the Buffalo Bills’ redonkulous 32-point comeback against the Houston Oilers in 1993. As Chris “Mad Dog” Russo puts it: “You’re gonna tell me momentum had nothing to do with that game?!”

Okay, Chris, I’ll take a shot at telling you exactly that. You know why we’re still talking about that game? Because it was a massive anomaly – the kind of comeback that almost never happens. It was so rare that our brains have an easy time recalling it. (We do this with all anomalies – dramatic plane crashes, mass murders, and so on.) And when we recall something so easily, we tend to believe it’s far more common that it actually is.

The truth is that you’re bound to get a wild 32-point-comeback once in a while, just as you’re bound to get a streak of 10 or 12 heads too. But just as the physical world cannot escape gravity, the statistical world cannot escape what’s called “regression to the mean.” Those wild streaks, as fun as they were, have very little bearing on what happens next.  

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  1. Otto says:

    I don’t see why momentum explains “the Buffalo Bills’ redonkulous 32-point comeback against the Houston Oilers in 1993.” If there were momentum, then wouldn’t the Oilers just continue to build on their lead?

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  2. RGJ says:

    Coins don’t have lossed and bursts of confidence. Whoever wrote this hypothesis mustn’t have engaged in competive athletic endeavors much. Or golf. Or darts.

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    • Erik Jensen says:

      The point of the article is not whether or not people gain or lose confidence in the course of a game. The point is that it might not matter to measurable performance.

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  3. JonE says:

    I just don’t believe momentum has THAT little to do with it. I agree that random chance can explain many streaks, but in games so heavily dependent upon a human element, the psychological factor has to be accounted for.

    I haven’t seen the data, but I would think that it’s going off of te “average” as te benchmark, but I feel that is wrong. ANY DATA included there, hot streak, cold streaks, “normal”times are factored into that, so of course the hot streak will merely look like a statistical anomaly.

    I guess my point is that it’s easy to test when you have a “true average” to use as a benchmark–like 50/50 for heads and tails, but for a shooting percentage, this is not as obvious. Even if you use multi-year, time-series data, I think it’s easy to underestimate the impact ending a season on a “high note” can have on confidence going into the next season.

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  4. Stuart Buck says:

    Here’s the thing: a 32-point comeback might indeed be so rare that it fits within a statistically normal distribution as several standard deviations above the mean. This does NOT mean, however, that a 32-point comeback was itself a matter of random chance — the 32-point comeback happened because of how a bunch of human beings performed on a given day, and that had a lot to do with their preparation, their skill, and their confidence level (the latter of which would be affected if either team started to think that the “momentum” was heading in a particular direction).

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    • Tom says:

      I’m pretty sure the good people at freakonomics aren’t naive enough to think there are no differences between a complex football game and a coin toss. I think the point they may be making is that more often than not we are mistaking a shift in a random sequence for a turnaround in momentum. I doubt anyone would argue that psychology never has anything to do with sports results but maybe it’s effect is exagerated by fans and pundits.

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    • Joel says:

      I think the coin-flip analogy makes sense in this case. If I see a bunch of good plays in a row, I always get it in my head that my team is on fire. It’s funny when I see something like this after watching a team suck for most of the game. I always get my hopes up and start to believe that even though the team has been terrible so far, they’re going to turn things around and start playing their best football all season.

      Usually when I get my hopes up like this, they come crashing down at some point before the end of the game. The results of the last couple plays never seems to predict anything about the next play. What does seem to matter is the team’s track record during the entire game or during the entire season. So when I watch the lions (except for this year-it’s an anomoly) and I see a couple good plays, I tell myself, they’re the lions, they’ll find a way to lose. And when I watch Green Bay and I see a couple bad plays, I tell myself, they’re the Packers, they’ll turn this game around soon enough.

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  5. Caleb b says:

    Malcolm Gladwell’s Blink discusses how increased adrenalin affects both vision and thinking speed. Police officers when firing shots can physically see bullets flying, have full thoughts in the matter of seconds, etc. The Zone is real and momentum is this zone. The distribution of the zone maybe perceived as random, but it is not the same as a coin flip.

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  6. Robert says:

    I think the point of these studies is not to equate humans with coin tosses, but to show that the outcomes of all these human interactions are much the same AS IF someone was tossing a coin (suitably weighted for factors existing beforehand).

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    • Mike says:

      Exactly. I’m surprised how many commenters are missing this simple point.

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      • Jack says:

        I agree that some people are oversimplifying things here, but to say “tossing a coin (suitably weighted for factors existing beforehand)” is absurd. The very point of making an analogy to a coin toss in any comparison is that you are saying, “This is completely random and will therefore follow a normal distribution if tested ad infinitum.” You are saying it is unbiased and unweighted. To qualify this by saying (suitable weighted for factors existing beforehand) renders the comparison redundant.

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  7. B-town says:

    I think momentum can manifest itself in the way it affects your opponent psychologically, causing them to make bad decisions and play on “tilt”.

    But, I’m not sure if that qualifies as momentum or just poor discipline.

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  8. Kevin says:

    Just wanted to point out that after “5 consecutive completions on a drive” the offense is going to be pretty close to the endzone. This is the easiest part of the field for a defense to defend. A lot less field with still 11 defenders means each defender’s zone is much smaller etc. We would expect the probablity of a completed pass to be less here than the average percentage of a completed pass.

    Part of statistics is “all things equal” and Dubner seems to have a real hard time seeing how one sequence of events can make the next event unequal to the average percents he quotes.

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    • James Briggs says:

      I don’t think that Dubner is being honest. If he is right then statistics are useless because the knowing what happened in the past tells us nothing about the future. We ought to fire them all because they are useless.

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