Do you understand the difference between accuracy and precision?

Temperature is another one. Unless you're doing experiments at absolute zero, 0 degrees K shouldn't be on your graph.

Not every graph needs to start at 0 though. A graph of temperature, for example, shouldn't ever start at 0 K unless you're dealing with temps in that range.

Do you know how long the NFL season is? It lasts from September until January, with all but one set of games being complete by the end of December. Your paper that looked from Aug-Dec includes all of the normal season games from the NFL, minus 16, but none of the post season games (13 games). Out of the total NFL games (269), your paper should include 240. 89% of the data set for the NFL is in fact the exact same games (aside from the potential cherry picking of data in your study, but we don't need to get into that).

Here's the real difference. Your paper is 20% NFL games, and 80% NCAA games. They lump all of the games with in person attendance together and judge that entire batch as a group. Now, from this more recent study, we know that games with <5000 people didn't show any trend towards increased Covid spikes. We don't have the attendance numbers for the NCAA games (a serious limitation of that study, but that's okay), but I really struggle to imagine that it was higher than the NFL games during that same period. If your data set is dominated by data that doesn't match the rest of the data, that can easily skew results.

Now, I can't prove that without doing a study of my own, but it's a perfectly reasonable explaination for why these studies got different results. If you read the conclusions of BOTH of these studies, they talk about limitations. One of the limitations of your study is exactly what has been stated here:

>First, owing to data limitations, we considered in-person attendance as a 0 or 1 binary variable. Specifically, while in-person attendance numbers were available for NFL games, they were not available for NCAA games. Explicit consideration of attendance numbers may change the estimation.

There are also additional limitations on this study that they specifically said should be followed up on:

>Third, we also did not account for the spillover effects to the counties adjacent to the ones hosting NFL or NCAA games.

This is one of the limitations that OP's study specifically was looking at. They also discuss your study and why they think they got different results:

>It is important to note that our study was distinct from and comes to different conclusions than a 2021 study that examined in-person attendance in NFL and NCAA games and detected no increase in COVID-19 cases in 3 ways. First, Toumi et al only included 19.1% of NFL games, whereas our study included every game. Second, our study examined both in-county and contiguous county COVID-19 cases whereas Tuomi et al only considered in-county spread. Third, our study examined the number of fans in attendance whereas Toumi et al6 only included a dichotomous measure indicating fan or non–fan attended games. Consideration of these factors may explain the differing results.

You're trying to spin this as bad science, and I guarantee you that the authors of your study would disagree. This is important expansion of previous work. There is no single source of truth in science, and you can have different results among similar studies; Often deeper dives will tell you why this occurs and gives a more complete answer. That's what OP's study is doing.

>51 NBA games happened this week with close to 20,000.

>Where are all the outbreaks? It's indoors and should be worse then NFL games and yet nothing.

Maybe because a lot of people have been vaccinated now? Weird, it's almost like vaccination works to help us get back to a normal life. How strange.

EDIT: I had a math error. Fixed it.

They also were initially making the assertion that the NFL played 1000 games in 2020, so using 269 games was "cherry picking". In reality, there were 269 NFL games played in 2020, and this paper used all of them.

> The same data was collected outside of the Beta outbreak in another paper and all of the correlation and inferred connections disappeared.

I'm real curious how 2 papers can collect data from the same set of NFL games (2020 season), but only one of those sets of games occurred during the Beta outbreak. Care to explain it?

Wait, is this what happened? You got confused. Your "better study" is actually the one that is using (potentially) cherry picked data. They are only analyzing 101 of the NFL games over their time period. Is this where you got the idea that the OP study was only analyzing 100 games?

Ironically enough, OP's study actually discusses this study and why it got different results. It might help if you actually read the study before criticizing it.

What are you talking about? Are you looking at a different article than the rest of us? They talked through the methods that they used to pull the data. It's all from public sources, not from another paper.

First off, your link is broken, but I think I was able to navigate to what you're trying to point at. I'm still not seeing where they used the data for only 100 games though. Can you quote something specific?

>They did have 269 games but the data used is only from 100 games.

Where do you get this idea from? Here's what the paper says:

>This included a total of 269 NFL game dates. Of these games, 117 were assigned to an exposed group (fans attended), and the remaining 152 games comprised the unexposed group (unattended). Fan attendance ranged from 748 to 31 700 persons. Fan attendance was associated with episodic spikes in COVID-19 cases and rates in the 14-day window for the in-county (cases: rate ratio [RR], 1.36; 95% CI, 1.00-1.87), contiguous counties (cases: RR, 1.31; 95% CI, 1.00-1.72; rates: RR, 1.41; 95% CI, 1.13-1.76), and pooled counties groups (cases: RR, 1.34; 95% CI, 1.01-1.79; rates: RR, 1.72; 95% CI, 1.29-2.28) as well as for the 21-day window in-county (cases: RR, 1.49; 95% CI, 1.21-1.83; rates: RR, 1.50; 95% CI, 1.26-1.78), in contiguous counties(cases: RR, 1.37; 95% CI, 1.14-1.65; rates: RR, 1.45; 95% CI, 1.24-1.71), and pooled counties groups (cases: RR, 1.41; 95% CI, 1.11-1.79; rates: RR, 1.70; 95% CI, 1.35-2.15). Games with fewer than 5000 fans were not associated with any spikes, but in counties where teams had 20 000 fans in attendance, there were 2.23 times the rate of spikes in COVID-19 (95% CI, 1.53 to ∞).

They looked at all of the 269 games. 117 were part of the exposed group and 152 was the unexposed group.

Way to just edit out all of your mistakes. Do you agree that they aren't cherry picking data now? Why even leave this comment up if the main pillar of your criticism is gone?

There's no cherry picking here. They used the data from all the games in the 2020 season.

Do teams play solo in your version of the NFL? Each game should have 2 teams, unless I'm seriously misunderstanding football.

Also, here's the Wikipedia article for the 2020 season. https://en.m.wikipedia.org/wiki/2020_NFL_season

Where are you getting 1000 games from? They were only looking at the 2020 season, which only had the 256 games plus playoffs which is 13 games. Am I missing something?

Minimum wage will still apply. I'm not sure why you think it wouldn't.

But that guy is on the left.