This project analyzes betting strategies in a best-of-three and best-of-five series between the Boston Red Sox and the New York Yankees. The analysis evaluates the probability of winning the series, expected net wins, and the effectiveness of different betting strategies. Statistical methods and simulations are used to draw meaningful insights into the profitability and risks of the betting strategy.

1. Evaluate Probabilities:
   
   • Use theoretical probabilities to calculate series outcomes for the Red Sox.
2. Construct Net Win Distributions:
   
   • Calculate expected net win, variance, and standard deviation for various scenarios.
3. Simulations:
   
   • Run 10,000 simulations to model the risk and validate theoretical results.
4. Goodness-of-Fit Tests:
   
   • Use chi-squared tests to determine how well observed results align with theoretical distributions.
5. Summarize Insights:
   
   • Compare strategies to assess which is most favorable and under what conditions.

• Data Analysis: Microsoft Excel for calculations, simulations, and visualization.
• Statistical Methods: Probability distributions, confidence intervals, chi-squared tests.
• Simulations: Monte Carlo methods using Excel’s RAND() function.

• Probability of Red Sox Winning: 56.64%
• Expected Net Win: $57.89
• Risk: High standard deviation of $795.15 reflects substantial variability in outcomes.
• Simulation Results: Confidence interval [44.25, 75.59] includes the expected value.

• Probability of Red Sox Winning: 56.09%
• Expected Net Win: $76.35
• Risk: Even higher standard deviation of $1024.73 highlights significant variability.
• Simulation Results: Confidence interval [39.98, 80.43] aligns with theoretical expectations.

├── Data/ │ ├── Betting_Strategy_Data.xlsx ├── Analysis/ │ ├── Probability_Calculations.xlsx ├── Visualizations/ │ ├── Simulation_Charts.png ├── Reports/ │ ├── A_Sports_Betting_Strategy.pdf ├── README.md

• Best-of-Three Strategy: Slightly favorable with an expected win, but high risk due to variability.
• Best-of-Five Strategy: More favorable with a higher expected win, though the risk remains significant.
• Insights:
  
  • High Standard Deviation: Indicates caution due to the variability in outcomes.
  • Simulation Alignment: Observed results align well with theoretical expectations, as confirmed by the chi-squared goodness-of-fit test.

1. Explore the Report:
   
   • Download the full report here.
2. Simulate Scenarios:
   
   • Use the provided Excel files to replicate simulations or customize probabilities.
3. Visualize Data:
   
   • Review the simulation results and probability distributions in the included visualizations.

If you’d like to contribute to the project, suggest improvements, or have any questions, feel free to open an issue or please reach out via LinkedIn

Author: Syed Faizan
Master’s Student in Data Analytics and Machine Learning