Short Overview

Whenever I play Monopoly with my girlfriend, I feel like I spend most of the game stuck in jail. I wanted to test whether that was just bad luck or a structural bias in the game.

I modeled Monopoly as a Markov chain under official rules (rolling doubles,  jail mechanics, Chance/Community Chest movement) and computed the stationary distribution of landing probabilities.


Key Result

• Jail is the most frequently occupied state by a large margin 
  
• Orange properties are high-traffic zones
  
• Illinois Avenue (3rd red property) is among the highest probability properties
  
• Chance squares have low stationary probability because chance cards often force players to move

Note: Jail is excluded from the final heat map because its extremely high stationary probability compresses the color range, making meaningful variation across the remaining squares difficult to see.


What This Analysis Demonstrates

• Markov chain modeling
• Preserving ergodicity of the Markov chain 
  
• Transition matrix construction
  
• Stationary distribution computation
  
• Numerical linear algebra in Python