EPL Fantasy GW4 Recap and GW5 Algo Picks

EPL Fantasy GW4 Recap and GW5 Algo Picks Our Moneyball approach to the Fantasy EPL (team_id: 2122122)

The EPL is one week away and our FPL Algorithm 2.0 is ready to play

Our Moneyball approach to the Fantasy EPL (team_id: 2122122). This year a new EPL enthusiast — Pulkit Chhabra — joined the team and added lots of fresh ideas and optimization suggestions to the Algorithm.

My findings on using Machine Learning for sports betting

One afternoon, in the middle of my holidays the thought of using machine learning to predict football results in the premier leagues came to my mind.

Making up the Odds: From Bayes to Betfair - A Short History

From Bayes to Betfair: How Has This Happened? This article is for educational and entertainment purposes only. If you want to use the presented model for real bets, do so at your own risk.

The Shady or Not so Shady World of Tipsters

The Shady or Not so Shady World of Tipsters. This article delves into the world of tipsters and the sports betting industry from the perspective of a potential investor.

Optimisation in Python to Reduce Mean Squared Error

Optimise our model’s inputs using scipy.optimize library. Optimisation in Python to Reduce Mean Squared Error. We have our Python Basketball model, which we are using to forecast the win probabilities off the initial spreads. This is our estimator. The win probabilities that we obtained from the betting markets (in our case, Pinnacle Sports) are our observed values, in other words, values which are taken to be true (now, they may or may not be “true” but… let’s not worry too much about that at the moment).

Predicting Basketball Results Using Python and Docker

Build a sports prediction model in Python. Python is great for building predictive models. The article describes the process of building and testing a basketball model against bookmaker ...

How Machine Learning could help on Horse Racing Betting

Utilizing Machine Learning on Horse Racing Betting Strategy. Machine learning has been widely used in many time series analysis and forecasting. With the help of a large amount of historical data and computing power nowadays, ML models can sometimes produce extremely useful insight and guidance to sports betting decision making.

Predict NBA Player Lines with Monte Carlo Simulation

I do not in any way encourage gambling. I do not encourage the use of my model, in fact, I actively discourage it. This is purely for educational use and should not be used or relied upon with any real money. Seriously.