Researchers have developed a groundbreaking mathematical framework to measure and compare the “depth” of various competitive interactions, from sports to social hierarchies.
Why it matters: This model could revolutionize how we predict outcomes across multiple industries and fields. It provides a universal way to measure inequality and competitive dynamics in both human and animal contexts.
- Traditional ranking systems lack a unified approach to compare different types of competitions.
Key finding: Human sports are surprisingly “shallow” compared to animal hierarchies, with basketball showing less than 1 layer of depth while hyena social structures exceed 100 layers.
“What we’re trying to do is build a general way of measuring inequality in a bunch of these different settings.”
Max Jerdee, University of Michigan doctoral student in physics
The process:
- Researchers analyzed data from various competitive interactions
- Created a metric that quantifies competition depth regardless of context
- Applied the model to predict outcomes between competitors who never met
Keep in mind: Shallow competition isn’t necessarily negative – it often indicates intentional design to maintain excitement and fairness.
Real-world impact: The model could transform:
- Sports betting and game predictions
- University ranking systems
- Consumer preference forecasting
- Corporate hiring practices
- Understanding social dynamics
TL;DR
- A new mathematical model can measure and compare the depth of any competition with winners and losers.
- Human-designed competitions are intentionally shallow to maintain excitement, while natural hierarchies are much deeper.
- The framework has practical applications across multiple industries, from sports betting to university rankings.
Read the Paper
Luck, skill, and depth of competition in games and social hierarchies