Tag Archives: Grantland

Do Low Stakes Hockey Games Go To Overtime More Often?

Sean McIndoe wrote another piece this week about NHL overtime and the Bettman point (the 3rd point awarded for a game that is tied at the end of regulation—depending on your preferred interpretation, it’s either the point for the loser or the second point for the winner), and it raises some interesting questions. I agree with one part of his conclusion (the loser point is silly), but not with his proposed solution—I think a 10 or 15 minute overtime followed by a tie is ideal, and would rather get rid of the shootout altogether. (There may be a post in the future about different systems and their advantages/disadvantages.)

At one point, McIndoe is discussing how the Bettman point affects game dynamics, namely that it makes teams more likely to play for a tie:

So that’s exactly what teams have learned to do. From 1983-84 until the 1998-99 season, 18.4 percent of games went to overtime. Since the loser point was introduced, that number has up to 23.5 percent. 11 That’s far too big a jump to be a coincidence. More likely, it’s the result of an intentional, leaguewide strategy: Whenever possible, make sure the game gets to overtime.

In fact, if history holds, this is the time of year when we’ll start to see even more three-point games. After all, the more important standings become, the more likely teams will be to try to maximize the number of points available. And sure enough, this has been the third straight season in which three-point games have increased every month. In each of the last three full seasons, three-point games have mysteriously peaked in March.

So, McIndoe is arguing that teams are effectively playing for overtime later in the season because teams feel a more acute need for points. If you’re curious, based on my analysis this trend he cites is statistically significant, looking at a simple correlation of fraction of games ending in ties with the relative month of the season. If one assumes the effect is linear, each month the season goes on, a game becomes 0.5 percentage points more likely to go to overtime. (As an aside, I suspect a lot of the year-over-year trend is explained by a decrease in scoring over time, but that’s also a topic for another post.)

I’m somewhat unconvinced of this, given that later in the year there are teams who are tanking for draft position (would rather just take the loss) and teams in playoff contention want to deprive rivals of the extra point. (Moreover, teams may also become more sensitive to playoff tiebreakers, the first one of which is regulation and overtime wins.) If I had to guess, I would imagine that the increase in ties is due to sloppy play due to injuries and fatigue, but that’s something I’d like to investigate and hopefully will in the future.

Still, McIndoe’s idea is interesting, as it (along with his discussion of standings inflation, in which injecting more points into the standings makes everyone likelier to keep their jobs) suggests to me that there could be some element of collusion in hockey play, in that under some circumstances both teams will strategically maximize the likelihood of a game going to overtime. He believes that both teams will want the points in a playoff race. If this quasi-collusive mechanism is actually in place, where else might we see it?

My idea to test this is to look at interconference matchups. Why? This will hopefully be clear from looking at the considerations when a team wins in regulation instead of OT or a shootout:

  1. The other team gets one point instead of zero. Because the two teams are in different conferences, this has no effect on whether either team makes the playoffs, or their seeding in their own conference. The only way it matters is if a team suspects it would want home ice advantage in a matchup against the team it is playing…in the Stanley Cup Finals, which is so unlikely that a) it won’t play into a team’s plans and b) even if it did, would affect very few games. So, from this perspective there’s no incentive to win a 2 point game rather than a 3 point game.
  2. Regulation and overtime wins are a tiebreaker. However, points are much more important than the tiebreaker, so a decision that increases the probability of getting points will presumably dominate considerations about needing the regulation win. Between 1 and 2, we suspect that one team benefits when an interconference game goes to overtime, and the other is not hurt by the result.
  3. The two teams could be competing for draft position. If both teams are playing to lose, we would suspect this would be similar to a scenario in which both teams are playing to win, though that’s a supposition I can test some other time.

So, it seems to me that, if there is this incentive issue, we might see it in interconference games. So our hypothesis is that interconference games result in more three point games than intraconference games.

Using data from Hockey Reference, I looked at the results of every regular season game since 1999, when overtime losses began getting teams a point, counting the number of games that went to overtime. (During the time they were possible, I included ties in this category.) I also looked at the stats restricted to games since 2005, when ties were abolished, and I didn’t see any meaningful differences in the results.

As it turns out, 24.0% of interconference games have gone to OT since losers started getting a point, compared with…23.3% of intraconference games. That difference isn’t statistically significant (p = 0.44); I haven’t done power calculations, but since our sample of interconference games has N > 3000, I’m not too worried about power. Moreover, given the point estimate (raw difference) of 0.7%, we are looking at such a small effect even if it were significant that I wouldn’t put much stock in it. (The corresponding figures for the shootout era are 24.6% and 23.1%, with a p-value of 0.22, so still not significant.)

My idea was that we would see more overtime games, not more shootout games, as it’s unclear how the incentives align for teams to prefer the shootout, but I looked at the numbers anyway. Since 2005, 14.2% of interconference games have gone to the skills competition, compared to 13.0% of intraconference games. Not to repeat myself too much, but that’s still not significant (p = 0.23). Finally, even if we look at shootouts as a fraction of games that do go to overtime, we see no substantive difference—57.6% for interconference games, 56.3% for intraconference games, p = 0.69.

So, what do we conclude from all of these null results? Well, not much, at least directly—such is the problem with null results, especially when we are testing an inference from another hypothesis. It suggests that NHL teams aren’t repeatedly and blatantly colluding to maximize points, and it also suggests that if you watch an interconference game you’ll get to see the players trying just as hard, so that’s good, if neither novel nor what we set out to examine. More to the point, my read is that this does throw some doubt on McIndoe’s claims about a deliberate increase in ties over the course of the season, as it shows that in another circumstance where teams have an incentive to play for a tie, there’s no evidence that they are doing so. However, I’d like to do several different analyses that ideally address this question more directly before stating that firmly.

Or, to borrow the words of a statistician I’ve worked with: “We don’t actually know anything, but we’ve tried to quantify all the stuff we don’t know.”

A Reason Bill Simmons is Bad At Gambling

For those unaware, Bill Simmons, aka the Sports Guy, is the editor-in-chief of Grantland, ESPN’s more literary (or perhaps intelligent, if you prefer) offshoot. He’s hired a lot of really excellent  writers (Jonah Keri and Zach Lowe, just to name two), but he continues to publish long, rambling football columns with limited empirical support. I find this somewhat frustrating given that the chief Grantland NFL writer, Bill Barnwell, is probably the most prominent data-oriented football writer around, but you take the good with the bad.

Simmons writes a column with NFL picks each week during the season, and has a pretty so-so track record for picking against the spread, as detailed in the first footnote to this article here. Simmons has also written a number of lengthy columns attempting to construct a system for gambling on the playoffs, and hasn’t done too great in this regard either. I’ve been meaning to mine some of these for a post for a while now, and since he’s written two such posts this year already (wild card and divisional round), I figured the time was right to look at some of his assertions.

The one I keyed on was this one, from two weeks ago:

SUGGESTION NO. 6: “Before you pick a team, just make sure Marty Schottenheimer, Herm Edwards, Wade Phillips, Norv Turner, Andy Reid, Anyone Named Mike, Anyone Described As Andy Reid’s Pupil and Anyone With the Last Name Mora” Isn’t Coaching Them.

I made this tweak in 2010 and feel good about it — especially when the “Anyone Named Mike” rule miraculously covers the Always Shaky Mike McCarthy and Mike “You Know What?” McCoy (both involved this weekend!) as well as Mike Smith, Mike “The Sideline Karma Gods Put A Curse On Me” Tomlin, Mike Munchak and the recently fired Mike Shanahan. We’re also covered if Mike Shula, Mike Martz, Mike Mularkey, Mike Tice or Mike Sherman ever make comebacks. I’m not saying you bet against the Mikes — just be psychotically careful with them. As for Andy Reid … we’ll get to him in a second.

That was written before the playoffs—after Round 1, he said he thinks he might make it an ironclad rule (with “Reid’s name…[in] 18-point font,” no less).

Now, these coaches certainly have a reputation for performing poorly under pressure and making poor decisions regarding timeouts, challenges, etc., but do they actually perform worse against the spread? I set out to find this out, using the always-helpful pro-football-reference database of historical gambling lines to get historical ATS performance for each coach he mentions. (One caveat here: the data only list closing lines, so I can’t evaluate how the coaches did compared to opening spreads, nor how much the line moved, which could in theory be useful to evaluate these ideas as well.) The table below lists the results:

Playoff Performance Against the Spread by Select Coaches
Coach Win Loss Named By Simmons Notes
Childress 2 1 No Andy Reid Coaching Tree
Ditka 6 6 No Named Mike
Edwards 3 3 Yes
Frazier 0 1 No Andy Reid Coaching Tree
Holmgren 13 9 No Named Mike
John Harbaugh 9 4 No Andy Reid Coaching Tree
Martz 2 5 Yes Named Mike
McCarthy 6 4 Yes Named Mike
Mora Jr. 1 1 Yes
Mora Sr. 0 6 Yes
Phillips 1 5 Yes
Reid 11 8 Yes
Schotteinheimer 4 13 Yes
Shanahan 7 6 Yes Named Mike
Sherman 2 4 Yes Named Mike
Smith 1 4 Yes Named Mike
Tice 1 1 Yes Named Mike
Tomlin 5 3 Yes Named Mike
Turner 6 2 Yes

A few notes: first, I’ve omitted pushes from these numbers, as PFR only lists two (both for Mike Holmgren). Second, the Reid coaching tree includes the three NFL coaches who served as assistants under Reid who coached an NFL playoff game before this postseason. Whether or not you think of them as Reid’s pupils is subjective, but it seems to me that doing it any other way is going to either turn into circular reasoning or cherry-picking. Third, my list of coaches named Mike is all NFL coaches referred to as Mike by Wikipedia who coached at least one playoff game, with the exception of Mike Holovak, who coached in the AFL in the 1960s and who thus a) seems old enough not to be relevant to this heuristic and b) is old enough that there isn’t point spread data for his playoff game on PFR, anyhow.

So, obviously some of these guys have had some poor performances against the spread: standouts include Jim Mora, Sr. at 0-6 and Marty Schottenheimer at 4-13, though the latter isn’t actually statistically significantly different from a .500 winning percentage (p = 0.052). More surprising, given Simmons’s emphasis on him, is the fact that Reid is actually over .500 lifetime in the playoffs against the spread. (That’s the point estimate, anyway; it’s not statistically significantly better, however.) This seems to me to be something you would want to check before making it part of your gambling platform, but that disconnect probably explains both why I don’t gamble on football and why Simmons seems to be poor at it. (Not that his rule has necessarily done him wrong, but drawing big conclusions on limited or contradictory evidence seems like a good way to lose a lot of money.)

Are there any broader trends we can pick up? Looking at Simmons’s suggestion, I can think of a few different sets we might want to look at:

  1. Every coach he lists by name.
  2. Every coach he lists by name, plus the Reid coaching tree.
  3. Every coach he lists by name, plus the unnamed Mikes.
  4. Every coach he lists by name, plus the Reid coaching tree and the unnamed Mikes.

A table with those results is below.

Combined Against the Spread Results for Different Groups of Coaches Cited By Simmons
Set of Coaches Number of Coaches in Set Wins Losses Winning Percentage p-Value
Named 14 50 65 43.48 0.19
Named + Reid 17 61 71 46.21 0.43
Named + Mikes 16 69 80 46.31 0.41
All 19 80 86 48.19 0.70

As a refresher, the p-value is the probability that we would observe a result as or more extreme as the observed result if there were no true effect, i.e. the selected coaches are actually average against the spread. (Here’s the Wikipedia article.) Since none of these are significant even at the 0.1 level (which is generally the lowest barrier to treating a result as meaningful), we wouldn’t conclude that any of Simmons’s postulated sets are actually worse than average ATS in the playoffs. It is true that these groups have done worse than average, but the margins aren’t huge and the samples are small, so without a lot more evidence I’m inclined to think that there isn’t any effect here. These coaches might not have been very successful in the playoffs, but any effect seems to be built into the lines.

Did Simmons actually follow his own suggestion this postseason? Well, he picked against Reid, for Mike McCoy (first postseason game), and against Mike McCarthy in the wild card round, going 1-0-2, with the one win being in the game he went against his own rule. For the divisional round, he’s gone against Ron Rivera (first postseason game, in the Reid coaching tree) and against Mike McCoy, sticking with his metric. Both of those games are today, so as I type we don’t know the results, but whatever they are, I bet they have next to nothing to do with Rivera’s relationship to Reid or McCoy’s given name.