OK, I’ll admit the blog has been sports-heavy lately. Now that the Super Bowl is over, hopefully I can diversify some. But for now, one last football example…

This week, the sports blog Deadspin featured an article titled: “Does The Success Of An NFL Replay Challenge Depend On Which TV Network Is Broadcasting The Game?” From the title, I was immediately hooked, since this exactly the type of question we ask in AP Stats when discussing chi-squared distributions. (Web note: while this particular article is fairly vanilla, linking to this site at school is not recommended, as Deadspin often contains not-safe-for-school content.)

The article nicely summarizes the two resolution types used in NFL broadcasts, and the overturn/confirmation rates for replay challenges in both groups. For us stat folks, the only omission here is the disaggregated data. I contacted the author a few days ago with a request for the data, and have yet to receive a response. But playing around with Excel some, and assuming the “p-value” later quoted in the article, we can narrow in on the possibilities. The graph below summarizes a data set which fit the conditions and conclusions set forth in the article.

By the time Chi-Squared distributions are covered in AP Stats, students have been exposed to all 4 of the broad conceptual themes in detail. We can explore each of them in this article:

- Exploring data: What are the explanatory and response variables? What graphical display is appropriate for summarizing the data?
- Sampling and Experimentation: How was this data collected? What sampling techniques were used? What conclusions will we be able to reach using complete data from just one year?
- Anticipating Patterns: Could the difference between the replay overturn rates have plausibly occurred by chance? Can we conduct a simulation for both types of replay systems?
- Statistical Inference: What hypothesis test is appropriate here? Are conditions for a chi-squared test met?

The author’s conclusions present an opportunity to have a class discussion on communicating results clearly. First, consider this statement about the chi-squared test:

“A chi-square analysis of the results suggested those differences had an 87 percent chance of being related to the video format, and a 13 percent chance of being random. Science prefers results that clear a 95 percent cutoff.”

Having students dissect those sentences, and working in groups to re-write them would be a worthwhile exercise. Do these results allow us to conclude that broadcast resolution is a factor in replay challenge success? Has the author communicated the concept of p-value correctly? What would we need to do differently in order to “prove” a cause-effect relationship here?

One final thought. While I can’t be sure if my raw data is correct, the data seem to suggest that broadcasts in 720p (Fox and ESPN) have more challenges overall than 1080i (CBS, NBC). And it seems to be quite a difference. Can anyone provide plausible reasons for this, as I am struggling with it.

## One reply on “NFL Replays and the Chi-Squared Distribution”

The difference in the television stations might be due to the importance of the games. Monday night football games are planned out to be more important/exciting games i.e. a division rival, as well as FOX having America’s game of the week etc. This would most likely have games with closer scores, and therefore result in more challenges due to the importance.