Monday, December 09, 2013

Do Western teams dominate in NFL night games?

You're getting ready for an NFL night game.  A team from the Eastern time zone is playing a team from the Pacific time zone.  How should you bet?

From 1970 to 2011, you should have bet on the West Coast team.  In games starting at 8:00 pm (Eastern) or later, they beat the spread 70 out of 106 times.  That's a record of 70-36, or .660.  The odds of something that extreme happening by chance (either way) is 1 in 806.  It's 3.3 standard deviations from the mean.

In a control sample of afternoon games, there was no such effect.  In fact, the Western teams went only 143-150 (against the spread) in those.

What's going on?  Well, the academic authors who found this result claim it's due to the circadian rhythms of the human body.  Physiologists and psychologists believe athletic performance peaks in the late afternoon.  So, for a game that starts at 8:00 pm Eastern time, the players from the West are actually playing at 5:00 pm "body time," which is why they perform better.

That result comes from a recent academic study: "The Impact of Circadian Misalignment on Athletic Performance in Professional Football Players," by Roger S. Smith, Bradley Efron, Cheri D. Mah, and Atul Malhotra.  Here's a Business Week rundown that actually just came out today.  Deadspin mentioned it here, and Brian Burke mentioned it here.

When I read the reports, I couldn't believe that the 70-36 could actually be accurate.  I downloaded the study ($8), and then went to Pro Football Reference to confirm for myself with their game finder.  And, yup, it all checks out!  


Wow, eh?  Could that actually be what's happening, that time-of-day effects on the human body are so big that they're almost twice the size of the home field advantage?  

Well, as you might expect, I'm skeptical.  I can think of a whole bunch of other things that might be going on.

Nothing of what I'm going to say is conclusive ... you should take this post not as a definitive rebuttal, but, perhaps, as a case for the defense, a "devil's advocate" kind of argument.


1.  There's no actual evidence that the West teams played better.  The only data we have is that they consistently beat the spread.  

It's just as possible, isn't it, that the bookmakers were shading the spread in favor of the east teams, at least in the night games?

I broke down the night games by day of week.  (They don't quite add up because I did everything manually, and probably screwed up somewhere.)

Sunday: 18-12
Monday: 46-19
Other:   3- 7

It turns out almost all the effect happens on Monday.

Does this support the "line shading" hypothesis?  I think it does, a little bit.  Monday night games, I'd imagine, get the most action from bettors ... if bookmakers shade the line when betting gets too heavy and unbalanced, it seems like Monday games should be the best candidates for when that happens.


2.  Night games are not random.  They're selected specifically because the NFL believes that they'll be the best games.  Maybe they're what the NFL thinks will be the games with the best teams, or the most exciting games, or the games with the most serious playoff implications.

For the most part, the NFL schedules the night games before the season starts (the exception: late-season Sunday games, which, in recent years, are chosen on the fly).  So, the league is, to some extent, guessing which the good teams are.  

Because of that, certain teams will appear on Monday nights more than others.  In this particular sample, the San Francisco 49ers appeared 28 different Mondays; the Seattle Seahawks, only six.

Could it be that there's something about the 49ers that caused them to beat the spread so much?  Perhaps the oddsmakers, and bettors, consistently underestimated San Francisco, those years.  For 16 consecutive years -- 1983 to 1998 -- the 49ers went 10-6 or better.  You'd think they'd have regressed to the mean at some point, but they didn't.  So, perhaps they were consistently lucky?

There's a bit of support for that -- every year from 1983 to 1989, the Niners had a winning record against the spread. Over their entire streak, they never went worse than 7-9.  Of course, a lot of that is due to their 19-9 record on Monday night ... but, still.


3.  Suppose that we assume that SOME of the effect is due to these kinds of factors.  Suppose that, because of shaded or incorrect spreads, the Western teams had a 53% chance of beating the spread, instead of 50%.

In that case, the odds of a 70-36 record now drop to only 1 in 225.  That gets a bit easier to accept as random chance.  

At 55 percent, you're down to 1 in 73.  


4.  If an effect actually exists, it's most likely a lot lower than what was actually observed.  

First, you need to regress the 70-36 to the mean, since, in nature, small effects are found much more frequently than large ones.  

Second, any effect smaller than 2 SD wouldn't have been published, which means, in general, effects that DO get published are overestimates.  

The study found the western teams beat the spread by an average of 5.26 points, with an SD of 1.33.  That means any result less than 2.66 points wouldn't have made it into print.  

Suppose that, unbeknownst to us, the actual circadian effect is 2.5 points.  If every study takes a different random sample of 106 games, fewer than half the studies will find statistical significance.  And ALL of those studies that *do* find significance will overestimate the real effect, because the minimum significant effect is 2.66.

That wouldn't be a problem if the SD was, say, 0.01, or something, because then almost ANY real effect would be found.  But, in this case, when the bar is set so high, the selectively-sampled observed effects are likely to be inflated by luck.  


5.  The effect for home games and road games is almost the same.  That is, no matter which of the teams is jet-lagged, the West team has the same advantage.  

That's fine, if the theory that only time of day matters.  

It does imply, though, that jet lag, or adjusting to a new time zone, doesn't matter much at all.  Which may be true, but I've seen other psychologists argue the opposite.  


6.  If there's such a huge effect for a three-hour difference, you'd expect to still have a substantial effect for a two-hour difference.  So I checked west-coast teams playing night games on the road in Central Time.  In those games, the effect disappeared.  The Western teams went 17-26 against the spread.


7.  If the effect does depend on time of day, then the effect should be similar for the fourth quarter of late-afternoon games, right?  Those games might end at 7:00 pm, while the night games start at 8:00 pm.  Not much difference there.  

Does that happen?  I haven't checked, but that would be a good test.  You could also see if the effect diminishes as the night game goes on ... by the end of the Monday night game, the West team is playing at 8:00 or 9:00 pm circadian time.  Of course, the East team is at the actual time of 11:00 pm to midnight, but, as far as I read, the paper doesn't posit that there should be a big difference between early evening and late evening.

(UPDATE: One author says the effect is based on distance from the 3:00 am physiological low point.  Going with that ... an 8:00 game is 10 hours benefit for the PST team, and only 7 hours benefit for the EST team.  But, then, an afternoon 1:00 game would be the opposite, 7 hours to 10!)


8.  You could also check late-afternoon games in general.  The East team is on 4:00 time, while the West team is on 1:00 time.  So East should have the advantage.  But, the authors explicitly say (in the Business Week article) that the "ramp up" effect is smaller than the "ramp down" effect, so maybe you wouldn't see anything.  

And, while we're here ... Daylight Savings Time.  The effect should be different the week the clocks change, right?  Instead of the West team playing at 5:00 and the East playing at 8:00, it's really (from a circadian standpoint) 6:00 and 9:00.  


9.  The author published a similar study in 1997, with similar results.  But the effect continued -- which suggests that bettors didn't react to it, and bookmakers didn't bother adjusting their lines.  

It's possible that the betting community was just shortsighted in not believing the paper's claims, but ... sharp bettors are usually quick to seize on inefficiencies like this.  To me, that's at least a bit of evidence that it might be something else.


10.  There are afternoon games in many other sports -- college football, NBA, NHL, major-league baseball.  You could check to see if this happens there.  

Even better, you could check sports in which *actual* performance can be measured, not just performance relative to another team.  Do golfers hit better in late-afternoon?  Do Rubik's-cube solvers have better times in events that take place later in the day?  What about bowlers, or dart-throwers?  There should be lots of ways to check.  


11.  In fairness, My view is that someone would have noticed if there were large time-of-day effects in other sports.  

From my own introspection, I think I'm better certain times of day than others.  I tend to get drowsy late in the afternoon, and I wouldn't be surprised at all if my (extremely minimal) athletic ability drops during that time, and other times I'm tired.  

But, I *notice* my tiredness.  Shouldn't professional athletes have noticed something, too, especially when they're so focused on their bodies and their performances?

Maybe it's possible for a team to drop from .500 to .333 without noticing the physiological changes that caused it, just like they may not notice any difference when they play worse on the road.  But ... I dunno, my gut says that's just too big an effect that nobody even *suggested* it before the academics.


12.  Oops!  As I was doing the final edit for this post, I remembered an NBA study that found Western teams travelling east had an advantage.  I checked, and the advantage was huge, just like this one.  And most NBA games are at night.  So ... hmmm.  

However, that study wasn't as clean as this one, with a complicated regression.  And it was denominated in actual winning percentage, rather than against the spread.  But, still ... hmmm.

In fairness, I have to say that study supports the pro-circadian argument, to some extent.


My completely arbitrary, intuitive, Bayesian guess as to what's actually causing this effect?  I'd say ... 20 percent line shading, 75 percent luck, and maybe 5 percent physiology.  

I'd also guess -- again, without any justification other than my gut -- that there's a 35 percent chance that there's no real measurable effect of circadian physiology at all, and a 65 percent chance that there's a measurable, but small, effect.  (I had it at 50/50 before I recalled the study in #12.)

Regardless, I definitely don't want to imply that this study isn't important.  Any time you find a huge, 70-36 result, after a prior prediction with a plausible mechanism ... well, that's something you definitely want to put out there for serious consideration.  I'm just not as confident as the authors that what they've found is an actual thing.

Prove me wrong, somebody!

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At Tuesday, December 10, 2013 7:36:00 PM, Blogger Don Coffin said...

Wouldn't the "best" place to look be in baseball, because of the much larger number of games in a season? I recognize that it's complicated, because it's not just 1 game a week, but (usually) 5-7 games a week. Still...not that I'm going to do the work...Although I think I remember reading somewhere research about whether there was a "first game" following a long trip effect...

At Saturday, January 04, 2014 5:02:00 PM, Anonymous Anonymous said...

I am late to the game here, but I am definitely in the same camp as Phil - quite skeptical.

It would have been nice if the authors of this NFL study used an unbiased measure of performance rather than just "performance against the spread" where they presume that the Vegas odds are accurate and unbiased (which may not be the case, as Phil points out, for various reasons, including unknown ones).

I will definitely look into this in MLB. The problem with MLB might be that since most games are night games, unlike in football, players may have adapted to playing so many games far from their natural peak time of the day.

I will study this and report to Phil, though, and perhaps he can post an update. I already have some code where I can look at almost any "split" I want and compare raw, adjusted performance from one condition to another. I use it for DH, PH, day game after night game penalties, etc. It would be easy to compare performance at different times of the day.


At Saturday, January 04, 2014 5:23:00 PM, Blogger Phil Birnbaum said...

MGL: if you do this, I'll definitely post it! You'd have to adjust for pitching, though, right? Otherwise, too much randomness. Unless you hav a HUGE sample, which maybe you do.

At Sunday, January 05, 2014 2:58:00 AM, Anonymous Anonymous said...

I happened to Google some of the key words for this concept and came across a study posted on Sports Insights that showed the exact opposite, I think (only since 2005):

With our measure of performance defined, we compiled ATS records for the four NFL teams located in the Pacific Time Zone (San Francisco 49ers, Oakland Raiders, San Diego Chargers and Seattle Seahawks) when traveling to play in the Mountain, Central and Eastern Time Zones.

The table below displays the results, since 2005:

Mountain 22-10 68.8%
Central 37-44 45.7%
Eastern 44-57 43.6%

Phil, in the study you cite (which I am going to purchase), did they look at West Coast games (agsinst East Coast teams), East coast games (versus West Coast teams of course), or both?

Also, my computer is whirring away looking at MLB trends in this regard.

At Sunday, January 05, 2014 5:40:00 AM, Anonymous Anonymous said...

Phil, I did read the study and I see that they used any game in which the East Coast time was 8:00 or later (I'm not sure whey they made the cutoff 8:00 and not 7:00). So that is East Coast night games and West Coast night games (5:00 or later).

That is fine. I ran into some problems with my MLB research so it might take a day or two to get some results.

Again, notice that the study I cited from data starting in 2005 yields THE EXACT OPPOSITE RESULTS with a very large effect, although the sample sizes are small. (The Mountain sample is around 2 SD from the null, the Central around 1, and the Eastern around 1.5).

They do not say whether they used all games (day and night). I assume they did. Here is the link:


At Sunday, January 05, 2014 11:41:00 AM, Blogger Phil Birnbaum said...

They must have used day games too, since they have more games than the night-game study, and they're only since 2005 (the night-game study was since 1970, I think).

It's probably safe to assume the night-game study authors "cherry-picked" their criterion, in the sense that they would have tried several different possibilities. I can't imagine they'd do the night game study and then not immediately look at day games to see if the results were similar.

At Monday, January 06, 2014 12:26:00 AM, Anonymous Anonymous said...

"It's probably safe to assume the night-game study authors "cherry-picked" their criterion, in the sense that they would have tried several different possibilities. I can't imagine they'd do the night game study and then not immediately look at day games to see if the results were similar."

No, I don't think that is right. They did look at day games as a control. They didn't cherry pick the night games though. They used night games because their hypothesis was that West Coast teams were closer to their peak cycle than East Coast teams. For day, games that would not be the case. In fact, that would be the opposite (East Coast teams would be closer to THEIR peak).


At Monday, January 06, 2014 12:41:00 AM, Blogger Phil Birnbaum said...

OK, you may be right. I was assuming they would have looked at a few different things (since there are probably different theories of how body clocks work), and then tried to figure out which theories supported the observations.

But, if the "4pm" theory is really the main one, then I should take that back.


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