Last week, the NFL Player’s Association conducted a survey on the players in order to aid them in choosing teams in free agency. Players were asked to rate their team in terms of eight categories that included weight room, treatment of family, and training staff. An average of approximately 41 players (out of a possible 53) per team responded to the survey. Here are the results:

It is quite an innovative idea from the NFLPA, and we will see if it has any impact on this year’s 2023 free agency class. The survey begs another question, though: how do these factors impact the success of a team? Does better travel lead to more wins? What about better nutrition? These are the types of questions that I attempted to answer in terms of statistical correlation. To do this, I used R Studio to find the correlation coefficient and make corresponding scatterplots of one factor against the team’s league rank. I include the R-value of each correlation for all the statheads out there.
Overall Ranking

R = .038
There is a very weak correlation between the overall survey score and team success. Looking at the raw results could even help determine this. The AFC finalists, the Chiefs and the Bengals, finished 29th and 27th in the survey, respectively. Doing well in this survey didn’t seem to indicate team wins. Well, how do the individual categories stack up?
Categories with a Slight (and I Mean Slight) Correlation to Team Ranking
Nutrition R = .288 | Weight Room R = .184
Nutrition and Weight Room have the highest correlation to team ranking, but even this figure is very low.
Categories with a Non-Existent Correlation to Team Ranking
Locker Room R = .016 | Strength Staff R = .061 | Treatment of Family R = .111
These categories have virtually no correlation with team success. The strength staff plot is interesting, as it shows the fact that players were generally reluctant to give harsh scores to their guys.
Categories with a Negative Correlation
Training Staff R = -.163 | Training Room R = -.167 | Travel R = -.153
A negative correlation in this situation would mean that an increase in travel score would make for a decrease in team ranking. I’m not actually saying that better travel makes a team play worse, but it is evident that there is no clear correlation between these three factors.
Conclusion
The results of this survey seem to point to the conclusion that these eight factors do not inherently lead to more wins for a team. At the end of the day, it’s about the guys out there on the field. If a franchise drafts well, uses its cap space correctly, and hires competent coaches, it can succeed without a top-notch facility.
Additionally, the survey itself has some flaws. The points of reference for the surveyed players vary so much from case to case. For example, rookies come from many different backgrounds. 2022 draftee Cole Strange of the Patriots came from Chattanooga, which is a small-time FCS school. In the same Pats draft class, Tyquan Thornton came out of Baylor, a football powerhouse. The resources these two young men had seen before New England were vastly different. On top of this, these two young men have not played for a professional squad outside Foxborough, nevermind seen many NFL facilities. Is it really fair to include these perspectives in this survey? In addition, non-response bias is always a concern, as an average of 12 players per team declined to answer the survey.
Nevertheless, this report card could have a large impact on the league. The correlation between team wins and these factors may increase not because they actually matter to winning, but because players are now more aware of what teams treat their players the best. If we see a Vikings-Dolphins Super Bowl in the near future, just know it was this NFLPA survey that caused it.