The latest articles on DEV Community by Kevin Zhou (@kevzho). https://dev.to/kevzho https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3777988%2Feb403799-6ea5-4771-8f9f-2771ba6f9e71.jpeg https://dev.to/kevzho en Kevin Zhou Tue, 17 Feb 2026 16:21:38 +0000 https://dev.to/kevzho/i-built-a-premier-league-predictor-with-20000-monte-carlo-simulations-heres-how-5f4o https://dev.to/kevzho/i-built-a-premier-league-predictor-with-20000-monte-carlo-simulations-heres-how-5f4o <p>Hey Dev.to community!</p> <p>I'm a high school junior who loves soccer and data science, so I decided to combine them. I built PLForecast – an interactive web app that predicts Premier League outcomes using Monte Carlo simulations and ELO ratings.</p> <p><strong>What it does:</strong><br> Runs 20,000 simulations of the remaining Premier League season<br> Calculates title odds, top 4 chances, and relegation probabilities<br> Updates dynamically as match results come in (manually updated for now, but will change that in v2)</p> <p><strong>Tech stack:</strong><br> • Python (pandas, numpy) for calculations<br> • Streamlit for the interactive dashboard<br> • Monte Carlo methods + ELO ratings for predictions<br> • Deployed on Streamlit Cloud</p> <p><strong>Current predictions (according to my model):</strong><br> • Arsenal title chances: 83.9%<br> • Tottenham relegation odds: 7.8%<br> • Relegation battle: 6 teams within 2% probability</p> <p><strong>Check it out:</strong><br> Live app: <a href="https://plforecast.streamlit.app/" rel="noopener noreferrer">https://plforecast.streamlit.app/</a><br> GitHub: <a href="https://github.com/kevzho/PLForecast" rel="noopener noreferrer">https://github.com/kevzho/PLForecast</a></p> <p>I'd love feedback from this community! What features would you add? xG data? Player injuries? Referee tendencies?</p> programming python simulation