Opinion: Different types of biases at play for NFL teams, fans as football kicks off

Football has been played.

We saw it with our own eyes. There was tackling and a scoreboard and everything.

And with the return of football being played comes the return of reactions being made. No longer is the flow of information limited to who was at the Buffalo Bills practice and funneled through the lens of what drill the team was running. Not anymore. With a full week in between the Bills’ first preseason game and their second, there’s plenty of time for the normal narratives akin to those in the regular season to rise up in the space between contests and lend themselves toward setting the stage for the next exhibition clash.

And those reactions come with all the lessons, learned or unlearned, of previous seasons. Of preseasons long past, filled with undrafted free-agent stars and underperforming high draft picks. Across the league, fans are ready to cut and promote players and coaches before their teams even return to their respective practice fields. Such is the way of the National Football League machine.

But as we begin to react, now is the perfect time to discuss the seeds we may be planting. Specifically, the SEEDS.

The SEEDS bias model is a framework that’s used to help people understand biases, what causes them, and how to interrupt them. It was developed by the NeuroLeadership Institute with a goal of helping people “reprogram” their brains to counter the unconscious biases that may be affecting their decision making. Let’s go through each part of the acronym, use one or two examples of each, and identify their presence in the consumption of football for fans (and even the team):

S (Similarity Bias) “People like me are better”

In culture, we see this manifesting in the form of phenomena like racism and ageism, but in football, it shows up first in simple fan tribalism. “Bills fans are better than Dolphins fans.” It, like all biases, is a mental shortcut created to make us feel like the need for any actual mental work has been alleviated and that we can use a small piece of information to make judgments on the whole. If a San Francisco 49ers fan watches the Bills/Colts preseason game specifically to see one of their favorite draft prospects O’Cyrus Torrence and comes away with a less-than-favorable opinion, that opinion is minimized simply because they’re not a Bills fan, and Bills fans are better. You have a more positive opinion of person A you don’t know vs. person B you don’t know because person A, as a Bills fan, is considered by your brain to be “in-group” and person B, as a 49ers fan, would then be “out of group.” Because of this, the opinion of person A carries more weight than that of person B.

“Well Bruce, person A knows the team and has context while person B doesn’t.”

Context is not necessary to opine accurately on how O’Cyrus Torrence played in the preseason game against the Indianapolis Colts. If it was a matter of understanding tangential facts that could provide perspective on the issue at hand, that point would have merit. But the mere fact that the defensiveness of the leaning towards the in-group individual exists is proof of the similarity bias at play.

In coaching, we can see it in the “good ole boy” coaches network. Constructs like the Rooney Rule were specifically designed in an attempt to break similarity bias in coaching hires, but it shows up in more places than simply race. Coordinators getting promoted to a head coaching position often poach their previous teams’ position coaches because that person’s most recent experience matches their own, therefore it must be better. The fact that it was deemed “genius” and noteworthy that New York Giants head coach Brian Daboll actually made an attempt to hire the best coaches for the job rather than the ones whose experience most closely mirrored his own is simultaneously hilarious and enlightening.

E (Expedience Bias) “If it’s familiar and easy, then it must be true”

The most infuriating part of this model for me as the author is expedience bias, because it gives rise to the idea that wins are a quarterback stat. It’s an easy and lazy shortcut that you as a consumer are bombarded with from all angles at all times when ingesting content. Despite a litany of better ways to evaluate quarterback play, it’s easier and quicker to just use wins and losses and call it a day, accuracy be damned.

Expedience bias also leads to coaches and fans alike hanging onto old opinions long past their expiration date. “Josh Allen is a reckless and inefficient quarterback” hasn’t been a true statement since the beginning of 2020, but if you’re a Cleveland Browns fan who hasn’t watched Josh Allen play much since you were hoping your team wouldn’t select him first overall in 2018, you will use your evaluation of him from half a decade ago to make judgements on him now because it’s easier and that’s the data you are most familiar with.

Skipping over a meaningful sample size of recent data in favor of a more familiar sample size of data from a long time ago doesn’t just apply to fans though. This is why first-round NFL draft picks continually get more chances to prove their worth in the league than other players. Teams can remember their pre-draft evaluation of the player and place much more weight on that than the data that has been collected in the years since that initial prospect evaluation.

E (Experience Bias) “My truth is the right one”

The dreaded “eye test” rears its ugly head here. I have historically referred to experience bias as “intellectual arrogance,” and it shows up in football evaluation constantly. It must be fought against on all fronts, but it’s often the hardest to combat. Experience bias tells you that the way you perceive the world is objectively true.

When you watch a football game once through on the television from the broadcast angle, you might feel very confident that you know how a particular player played. But if you slow your brain down, you’ll realize that you don’t know how many snaps that player played, you don’t know where they were lining up on the field the majority of the time, and your opinions on their entire game have been heavily influenced by the few times they flashed on the broadcast and were brought up by the announcers. This is true more often for players in the defensive secondary because in many cases, they’re not even on the screen and you may only see them if they are in proximity to a targeted players’ location. The idea that you can be so incredibly sure about how a player played in these situations is insane.

This also shows up over the course of the season in addition to inside a specific game. Every ranking or tiering of quarterbacks involves people arguing for a player they’ve watched every snap of and against a quarterback they may have caught a time or two on a primetime game while they were less focused. This is the reason why knowledge and usage of metrics is so important. Metrics can force us to shake loose from the intellectual arrogance of our own eyes and be confronted with data that can help us recognize that the way we perceive football is not an objective truth and is influenced by our emotional state, our history, and our preferences among many other factors.

The same applies to teams. Teams embrace analytics in part because it helps them make decisions without relying on their “gut.” They recognize that their gut is influenced by a lot of factors that may or may not be objectively true, and that having more and better data can help them make better decisions.

D (Distance Bias) “Closer is better”

The NeuroLeadership Institute provides as example of distance bias as follows:

One example of this bias is the “endowment effect”—our tendency to value things more if we own them than if we do not (Kahneman et al., 1990). For example, someone may say that she is willing to pay $1 for a neutral object, such as a bottle of water. However, if you give her a bottle of water (i.e., endow her with it), and ask how much she would be willing to accept as payment for this bottle of water that she now owns, she may say $2.

Teams and fans value their own players (that they like) more highly than an equivalent player on another team because “closer is better.” Bob (a “B” level player on my own team) is more valuable than Frank (a “B” level player on another team) because Bob is closest to me. Fans and teams are often on board with investing more to keep their own players (that they like) than an equivalent or even potentially better player with whom there is more distance. It’s important to note that this phenomenon is less frequent than most others stated in this piece due to the highly volatile and emotional aspect of football (hence my consistent use of the phrase “that they like” to describe a certain subsection of players). In many cases, the opposite effect can come into play. A player who would be considered to be a league-average starter on any other team may become vilified and an object for intense fan criticism disproportionate to their play due to a variety of factors like draft status and opinion of a player behind him on the depth chart.

The more common manifestation of this bias in fandom is simply believing that your team is a better and more morally upstanding organization because they are YOUR team. The Buffalo Bills are an intrinsically more moral entity that is worthy of fandom because you are emotionally tied to them. When Mike Florio of Pro Football Talk commented that he believed the Bills and running back Nyheim Hines, who suffered an ACL injury after a jet ski crashed into him, were “at odds” regarding the financial fallout from that incident, fans of teams that were not the Bills had very different reactions than fans of the Bills. Comments of the Bills being “cheap” or “shady” on social media almost exclusively came from fans of other teams, whereas the predictions that the Bills would pay Hines and resolve the situation in a way befitting an upstanding and decent organization came almost exclusively from members of Bills Mafia.

S (Safety Bias) “Safe is preferable to good”

The amount of brain space tied up in preventing loss is more significant than the amount of brain space devoted to creating gain. Because of this, a basic tenant of humanity is loss aversion. On average, if you tell a person that you will flip a coin and that tails will result in that person losing $10,000, they will have to be assured $20,000 if it comes up heads in order for them to agree to have you flip the coin and expose themselves to the results. In other words, losing $10,000 feels more negative than gaining $10,000 feels positive.

This risk aversion shows up more in coaching than it does in fandom, because fans don’t have to lose their jobs as part of the potential negative outcomes. A great example of this is a team that punts late in the fourth quarter from their own territory when they’re down by multiple scores. At this point, the idea that the team is trying to win has gone completely out the window. They are now trying to lose by less, and they’re hopeful that if they punt the ball away, the other team will utilize clock-running plays with less likelihood of scoring so the final score won’t look as bad as it would have if their team would have turned the ball over on downs in their own territory and potentially allowed more points. The team may have had a win probability of 10% at the time of the punt, but their behavior is that of a team that has a 0% chance of winning, because they place more value on the downside of losing by more than they do of the upside, however small, of winning.

Fourth-down aggression decisions in the NFL have consistently lagged behind win probability models also due to this reason. If you have a job, your first priority is keeping that job, and the human brain is wired to believe that not making a mistake is a much better way to keep your job than doing something great, regardless of if that is actually true.

And so we consume our football content, allow our biases to continue to exist unchecked, react the same way every year, finish off a season of football, go through an offseason, rinse, and repeat. But maybe if we can see how our brain is fundamentally wired to be biased, we can combat it as much as possible and lead ourselves to a more truthful state of football consumption.

...and that’s the way the cookie crumbles. I’m Bruce Nolan with Buffalo Rumblings. You Can find me on Twitter and Instagram @BruceExclusive and look for new episodes of “The Bruce Exclusive” every Thursday on the Buffalo Rumblings podcast network!