Kevin Quealy and Ben Shpigel offer “Four Reasons the N.F.L. Shattered Its Scoring Record in 2020”:
No. 1: No fans meant (essentially) no home-field advantage
With fans either barred or permitted at diminished numbers because of public-health concerns, the normal in-game din dropped to a murmur or — at some stadiums — to a near silence. That functionally eliminated any edge that a packed stadium full of screaming fans might provide to a home team. That gap has been steadily closing over the years, but visiting teams never scored more, on average, than they did in 2020.
No. 2: Referees called fewer offensive penalties
A significant force driving the scoring eruption didn’t even involve players. On-field officials, adjusting the standard by which they enforced penalties, called the fewest offensive holding penalties since at least 1998. . . . On the other side of the ball, penalties for defensive pass interference increased for the third consecutive season, to its highest levels since at least 1998, which also extended possessions.
No. 3: Coaches Were Smarter on Fourth Down
At the same time, if teams weren’t successful on third down, more of them recognized the value of going for it on fourth down. Teams went for it 658 times, up from 595 last season, especially on 4th-and-1 . . . Instead of being aggressive solely in the second half, when score and clock decay might dictate it, teams went for it before halftime more than 200 times, significantly more than they did in previous years.
No. 4: The N.F.L.’s quarterback evolution accelerated existing trends
At a position long defined by pocket proficiency, the best of this next generation marries cherished passing attributes — accuracy, arm strength and downfield vision — with mobility, elusiveness and an aptitude for extending plays. . . . Unlike defensive players, who couldn’t simulate tackling drills as they trained away from their teams’ shuttered facilities, many quarterbacks improvised by gathering running backs and receivers— and even some linemen — in parks or at school practice fields to master the scheme and build chemistry.
This is great stuff. A few years ago I complained about a bad sports analysis from Quealy, so I’m really happy to see this new piece, which is thoughtful without being gimmicky.
A research question
There are lots of things above that could be studied further. Here I want to focus on Quealy and Shpigel’s first point, “No fans meant (essentially) no home-field advantage.” They continue:
“You don’t have to worry about the noise levels,” Steelers linebacker Avery Williamson said in an interview in October, when he played for the Jets. “You don’t realize how quiet it actually is on the field when you get out there. You could hear coaches talking across the field. It’s super weird.”
The subdued atmosphere created a more forgiving atmosphere for road teams, reducing the need for quarterbacks to use silent counts and allowing masters of the hard count, like Rodgers, to use his voice to draw opponents offside. Offensive linemen, in turn, could hear the calls more quickly and clearly. False starts dropped to a record low in 2020.
So here’s my question.
How can we study the effects of crowd noise on home-field advantage? The above point no. 1 is a before-after study, which could be thought of as an observational study with two data points, comparing NFL in 2020 to NFL in previous years.
There are various ways to expand the analysis:
1. Within games, focus on particular game situations where crowd noise would be expected to be more of a big deal.
2. Within the NFL, look at interaction with crowd size or crowd noise: if the above story is true, you’d expect to see larger home-team / visiting-team spreads in noisier stadiums.
3. Look at other sports.
There are probably some other ideas I haven’t thought of.
P.S. Jonathan Falk writes:
As someone who’s done a couple of studies of home field advantage I find this interesting, but I’m dubious. First, you’re right that this is kind of a two datapoint causal analysis. That’s hard to do convincingly! But second, it is unsurprising that better teams have higher crowds and therefore louder ambient noise. Causality is at least partly two-way, which makes identification critical and… well, identification is mostly rhetoric, right? That said, I’m sure there’s *something* there in football, because if silent counts were equally effective, why wouldn’t teams use them both at home and on the road? It’s one of the very few examples where road teams actually play the game differently in any sport. I am much less convinced that crowd noise has any effect in, say, baseball, because the noise level is high at critical moments irrespective of whether the home team is batting or pitching.
Teams want to sell tickets, and the notion that fans can actually contribute to the probability that their team wins just by showing up and being enthusiastic is a romantic one which lines up nicely with the profit interests of the teams. But there are lots of causes for home field advantage that would have to be eliminated to confidently assert anything about crowd noise: travel jet lag/time zone/circadian rhythm effects, hotel living versus home living, unique conditions to which home teams can both accustom themselves and differentially field a team capable of exploiting (unique stadium sizes in baseball, wind tunnel effects effects in football, dead spots in the floor at Boston Garden) and, in a few sports, actual rules advantage for the home team (last ups in baseball, last change in hockey).
FiveThirtyEight published an analysis on this for the NBA. https://fivethirtyeight.com/features/after-this-weird-nba-season-we-have-a-better-idea-of-how-much-fans-matter/
During the 2021 summer Olympics, there were no fans. Consider track and field. There are: no coaches (on the field), no play calling, no referees, and no teammates (for almost all events). This, therefore, is a chance to use a linear, fixed effects model to test your assumptions independently.
Shouldn’t you take the teams with the biggest home field advantage and see if those teams lost their advantage. I am suspicious that some of these teams (e.g., the Packers) have a home field advantage in part because quarterbacks like Aaron Rodgers know how the wind effects the ball in parts of the stadium. It would also be interesting to look at some teams and outdoor stadiums. That might shed light on whether their are stadium effects other than noise. Also, there is a travel effect. West Coast teams do poorly traveling to the East Coast. You need to adjust for that. If the West Coast teams did better traveling that might really support the notion that crowd noise has a big impact.
What you’re testing against, for the dependent variable, is random chance. In my example, because there is no play calling, etc., you simply can use fixed effects to control for the dependent variable. In your example, you can’t. It’s still possible that a hidden injury, food poisoning, etc., many random variables are at play and very difficult to account for. For instance, it’s possible that one coach, when playing against another coach, simply knows how to read him and is a better play caller for this one game only.
To be clear, the fixed effects, in my example, is simply the time difference, between when a crowd is present and when a crowd isn’t. That is, the linear equation is testing how correlated an athlete’s time is to the presence of a crowd. Than, the dependency of these variables can be compared to the dependency described in this blog post.
Seems to me that to gain much understanding you’d have to break down the causal mechanisms a bit.
For example, is there a difference in point differential as much as there is in the effect of home field on won/loss records? Maybe home teams are better at winning close games – which would have a limited impact on point differential. I’m thinking about Toronto in the AL East this year, which had a much better point differential than the Yankees, but the Yankees made the playoffs.
Maybe the impact would be seen more clearly on offense as opposed to defense? Is there a clear signal of home field advantage on yards gained, maybe more so than yards allowed?
How about coaches? Do they make decisions differently at home – ala “play for the tie at home.” Of course, that would run counter to the narrative that coaches are now listening to statisticians more and going for it more on 4th down.
Do field goal kickers perform better on home field (maybe because they understand the winds better)? That could connect with a stronger signal in win/loss versus point differential or yards gained/lost.
Maybe punters are better at home for the same reasons? And that would be a tricky one because maybe it wouldn’t show in net yards advanced from a punt, but in the ability to pull off a coffin corner kick?
And of course, I think you’d be better off analyzing fans’ rituals? Maybe lucky shirts and sitting in the right spot on the couch have a stronger effect on home field since the distances that the voodoo waves have to travel is likely shorter for home games.