Behavioral Bias: The Ultimate Bracket Buster


Agonizing over March Madness picks? Scanning the regular season records and starting lineups to decipher who will surprise and who will choke? The ultimate bracket buster probably isn’t that upstart 12 seed lurking in the bottom of the bracket. A bigger barrier to office pool glory might be in your head.

Most of us spend a week in mid-March toiling over our bracket selections with a common goal: winning that sizeable office pot. In other words, our bracket is an investment. Unfortunately, when it comes to investment decisions the human mind is prone to mental miscues.

A growing body of behavioral finance research suggests behavioral biases cloud our investment decisions and often lead us to irrational choices. These same types of biases creep into our March Madness picks. We can help you weed them out.

At 361 Capital, we are dedicated disciples of behavioral finance and are attuned to how behavioral biases imperil investors. We want to help you avoid those mistakes this March. We’ve put together a list of 10 common biases that can quickly bust a bracket—and the tips to avoid them. We hope it makes this year’s tournament less maddening.

10 Behavioral Biases that Can Bust a Bracket

1. Familiarity Bias: This bias suggests that we subconsciously prefer things we’re familiar with. In March Madness, it means putting too much faith in your alma mater or hometown team. The bias appears rampant in brackets: Home state fans pick their local team to win the national championship eight times more often than the rest of the country selects that team.¹

Tip: Identify the three tournament teams you have the most affinity for. Don’t pick these teams to beat a better-rated seed in the bracket. Pick upsets in the tournament, but not where your heart holds sway. To exploit familiarity bias, assess whether there’s a high proportion of graduates from a particular conference within your pool. If so, differentiate your bracket by picking against those teams.

2. Anchoring: Anchoring occurs when we tether an opinion to an original reference point and fail to adjust that opinion when new information becomes available. For casual college basketball fans, we might watch just a few games all season. Be wary of assigning too much good or bad will to the one team you watched one time. It’s better to look at the full body of work.

Tip: If you only watched a handful of games this season, make sure they aren’t the sole reason behind predicting a deep tournament run. If you’ve selected a team beyond the Sweet 16 based solely on one game, find at least three more pieces of information to support the pick. Can’t find them? Then ditch it. To take advantage of others who might anchor predictions to a single game, know that the most-viewed game this season was the March 3 contest between Duke and North Carolina.

3. Loss Aversion: The principle behind loss aversion is that losses affect people more emotionally than gains. In short, we are more fearful of looking stupid than we are determined to be right. Loss aversion can lead basketball fans to always choose the top seeds. While top seeds are good teams, they aren’t unstoppable: One seeds only advance to the Final Four 40% of the time.² Don’t let loss aversion keep you from defying conventional wisdom when you sense an upset.

Tip: Don’t be scared to pick several big upsets. History shows there’s an average of six upsets among teams seeded 10-15 each year. The 12/5 seeds are particularly ripe for upsets, with 28 of the last 32 tournaments featuring at least one 12/5 upset.

4. Information Overload: Rebounding margin, road win percentage, coaching experience, defensive efficiency ratings, RPI and BPI … statistics offer endless ways to analyze a basketball team. When faced with so much information it’s easy to fall prey to information overload—which may mean taking a mental shortcut to simplify the decision. For March Madness, you could mistakenly resort to using a single metric as the measuring stick for teams.

Tip: The amount of basketball data available is overwhelming, but don’t resort to using just a single statistic to simplify decisions. Rely on at least several statistics to guide selections. In a video explaining his own process, ESPN Analyst Jay Bilas suggests a few key statistics to guide picks: RPI, teams in the top 20 in offensive efficiency and top 15 in defensive efficiency and teams with an offensive rebounding rate above 30%. (Caveat: while helpful, these factors did not correctly predict last year’s champion.)

5. Herding: The principle behind herding is that we fear being wrong in isolation more than we crave being right. As a result, we make a consensus choice even if it goes against our gut. During March Madness, fans can’t see other brackets in their pool until the opening tipoff. Fans herd instead by following the picks of a renowned expert. Be careful: the experts are often wrong. Last year, only four out of 25 ESPN experts correctly predicted North Carolina would win it all.³

Tip: To avoid herding, don’t copy picks from a popular analyst everyone follows. Instead, aggregate picks from several analysts or use a computer-based model to analyze teams. This FiveThirtyEight article suggests several computer models: Jeff Sagarin “predictor” ratings; Ken Pomeroy Pythagorean ratings; Joel Sokol LRMC rankings; and Sonny Moore power ratings. To intentionally avoid the herd, be mindful that Jay Bilas, Andy Katz and Jeff Goodman are the most followed ESPN analysts on Twitter.

6. Recency Bias: Recency bias convinces us that newer information is more valuable and important than older information. For March Madness predictions, that means assigning too much weight to the conference tournaments that precede the big dance.

Tip: Don’t overweight the significance of conference tournaments that take place just before March Madness. Pay closer attention to the regular season conference record. Preseason polls offer another talent assessment that isn’t influenced by recent games.

7. Confirmation Bias: With many decisions, people selectively filter and pay attention only to information that supports their opinion, ignoring or rationalizing the rest. This bias presents itself in March Madness picks less in our actual choices, but more in the research we gather. If you filled out a bracket with a predisposed notion about the Final Four teams, make sure not to gather research that only supports those teams’ strengths.

Tip: Actively seek negative information about the teams you predicted to make the biggest upsets. Objectively weigh that negative information against the positive reasons you believe that team will win.

8. Overconfidence: This occurs when we overestimate the accuracy of our predictions. In a March Madness bracket, the bias manifests itself when we aren’t critical enough about our own picks. We might be convinced about the champion we select or an upset we pick without even asking why we are so sure.

Tip: Don’t let overconfidence influence your Final Four picks. Take a critical look at how each of those teams might be flawed and see if there is another team in their section of the bracket that would expose those flaws. For example, if your team is a poor rebounding team, could they potentially face a tall, strong rebounding team?

9. Gambler’s Fallacy: The gambler’s fallacy is a misconception that a random event is more likely due to the results of previous random events. For example, if a coin flip results in “heads” four times, someone could mistakenly believe the next flip is more likely to be “tails.” The odds actually remain 50/50. The gambler’s fallacy can trick us into thinking freakish results last tournament can’t happen again. For example, in 2017 three of the four 11 seeds upset six seeds. A 15 also upset a two seed. Those results don’t make similar upsets any less likely in 2018.

Tip: Simply put, don’t predict a team or particular seed winning just because “they’re due.”

10. Halo Effect: The halo effect means the brain allows a few positive traits to rosily impact the overall evaluation of something. It can happen in a bracket if you assign a higher probability of a team advancing because they have a likeable story. For example, a charismatic player with an interesting background may cause you to subconsciously inflate his team’s chances.

Tip: Don’t let a flashy player or Cinderella story influence your picks. A dazzling dunker or sizzling shooter can’t carry his team alone. As a rule, if the best player in the tournament plays on a 10-loss team, don’t expect him to suddenly lift his team to Final Four glory. Similarly, if a surprising team makes it into the tournament for the first time in ages, remember it doesn’t ensure they will advance.

Awareness of these biases won’t guarantee a winning bracket, but it can keep the selection process rational. To learn more about how behavioral biases affect professional investors and how we exploit those biases at 361 Capital, read our paper on the subject.