The Behavior Of Football

Whether it is individuals or groups of people, our environment has the greatest influence over our behavior. Our behaviors function as a way of helping us adapt to the world around us. Our goal at Football Behavior is to help sports bettors better understand the environment NFL teams behave in, how they behave, and most importantly, how to predict how they will behave in the future.

Like behaviorist B.F. Skinner established with his pigeon experiments all those years ago, living things are prone to superstitious behavior. Sometime it only takes a minimal amount of reinforcement (like winning just a few bets out of many) to keep you coming back for more. When that happens we can fall into a pattern of flawed decision making.

Football Behavior hopes to remove the superstition from your sports betting behavior.

Why Sports Betting Models?

Bettors typically place bets when they have the greatest understanding of all of the different variables that could impact the environment of a particular game.

To do this, bettors often seek out sports betting models for projections and predictions that have strong correlations with actual outcomes.

To have weekly access to predictions from the Pigeon Picks Prediction Model, which hit 67% of the time in 2022 on 300+ bets, with a 91% ROI, upgrade your subscription to receive:

• Weekly behavioral profiles for every team

  • Improvement Index

  • Risk Assessments

  • Margin Of Error Scores

• Final Score Predictions for every game, every week

• Matchup Risk assessments for every game, weekly

• Quarterback Prop Predictions

What is a Sports Betting Model?

Sports betting models take into account an incredible amount of data points relative to the outcome they are trying to project. Likewise, some betting models only select specific data points that align with what they believe to be most valuable to the outcomes they are predicting. In football, for example, those data points could be things such as yards gained, yards given up, penalties, starting field position, points scored, dewpoint at kickoff, etc.

They could also be standardized subjective analytics that have been created along the way like EPA, DVOA, WAR, etc.

Those who create models attempt to place relevant values on those data points to dial in their model at a level of accuracy suitable for them to make confident predictions.

As a behaviorist, I attempt to pinpoint specific observable team behaviors as objective data points to include in my Pigeon Picks model. Things like Scoring Behavior Rate (SBx) and Score Prevention Behavior Rate (SPBx), among many other things.

At Football Behavior, the Pigeon Picks Prediction Model uses dozens of individualized behavioral data points for each team to project winners along the moneyline, against the spread (ATS), dutching winning margins, over/unders, prop bets, etc.

Using Applied Behavior Analysis To Help in Sports Betting

B.F. Skinner is widely considered the father of applied behavior analysis (ABA). Today, ABA is often incorrectly exclusively associated with a therapy model for individuals with Autism. However, Skinner considered applied behavior analysis a natural science for understanding the behavior of all living things.

The science is based on collecting data on purely observable events, charting that data, and searching for trends that lead to projections of future behavior.

Football players and teams are living things. They have behaviors that are greatly influenced by the environment they are expected to perform in. ABA can help us understand them better.

As a behaviorist and the creator of the metrics for Football Behavior, I work directly with several NFL players on technique and movement behavior for their positions. Working with them and their coaches has given me a front row seat to what they feel truly matters in deciding the outcomes of football games.

Taking that knowledge, and then observing the team behaviors of all 32 teams in all 32 different environments that they operate in on a weekly basis, we have learned that some of those behaviors are more valuable than others in determining winners and losers.

We've taken the data collected in our observations and put them in a model using a Standard Celeration Chart (SCC), which is a semi-logarithmic chart measuring the speed at which something is getting better or worse.

This model gives me projections for expected behaviors of the teams in a few different areas that we use to bet against the spread, the moneyline, over/unders, dutching winning margins, and even some parlays. All of it is predicated on the principles of behavior analysis.

You can follow our model’s success every week by following me on Pikkit and upgrading to Pigeon Picks.

Explaining The Key Terms That Matter

Adhering to principles of applied behavior analysis partly means knowing what it is we are looking at when we analyze trends, projections, and expected outcomes. It is very important that we know the definitions of key terminology being used, not just for the person doing the modeling but perhaps even more importantly for you, the audience.

Some of the core elements of applied behavior analysis we look at are:

• Group behavior dynamics

• Environmental control of behavior and the impact of environmental changes

• Temporal Extent

• Repeatability

• Temporal Locus

Football Behavior has prepared a Glossary of Terms that include definitions and examples of key terms and Football Behavior’s proprietary metrics and analytics. All of these are very helpful to sports bettors, as well as give insight into what makes the Pigeon Picks Prediction Model a winning sports betting model.

Frequently Asked Questions

Can you use this model to bet every single game played?

The short answer is yes. However, remember the bounce rate. We personally will not place a wager on a game where a team has a bounce rate over x3 or if a team has a celeration in either direction over 2. This indicates high levels of chaos and outlier possibilities. If you follow me on Pikkit, we will always say which games we are betting on and what those numbers are as to how we selected those specific games. If we deviate from that, we’ll always be transparent about that.

What does a 90% confidence level for Bounce Rate mean on the chart?

This represents how “confident” we are in calculating this particular bounce rate. 90% is the standard for calculating a bounce rate, meaning that we are 90% confident that this is the correct range of outcomes for a projection. Anything that comes in outside of that range would be considered an outlier. Anything significantly out of that range would be considered an “extreme” outlier.