Breaking down skill in the most common event type. This blog builds an expected pass model to alter this perception. I use an objective variable to measure pass quality on a continuous spectrum, to analyse the levels of risk involved in any pass based on previous pass data.
This is an article on my EPL Prediction series. You can check out the prediction for previous Game Week and how it held against the actual performance here.
Simulating the 2020 NFL Season 100,000 Times. Predicting the outcomes of the entire 2020 NFL season by tracking how often each simulated universe yields a given result for each team
EPL 2020/21 Season Analysis and Prediction. In this post, I try to analyze the performance of teams and try to predict the result of upcoming fixtures.
Improving a Famous NFL Prediction Model. Diving deep into the stats of the NFL to improve a famous model that has the potential to rival those in Vegas
Python for FPL(!) Data Analytics. Using Python and Matplotlib to perform Fantasy Football Data Analysis and Visualisation
Preprocess FIFA World Cup data with Python. The next FIFA's world cup is coming soon and will begin in june, so I wanted to make some python visualization to practice to use matplotlib and seaborn.
This article evaluated football/Soccer results (victory, draw, loss) prediction in Brazilian Football Championship using various machine learning models based on real-world data from the real matches.
In this article, I want to share my (possibly unconventional) visualization approach.
Who should I start in Fantasy Football? I will use very simple maths and a little bit of coding (Python) to help find the ultimate FPL starting team for this season.
A network analysis of the 2020 college football schedule using NetworkX and musings about difficult decisions in college football.
Why do more teams win the Super Bowl than the Premier League? This, despite post-match replays showing that Ji’s goal was incorrectly awarded despite being offside.
Iam going to show you the different ways you can build a football league table in Excel. Some of the methods are old school but others utilise Excel’s new capabilities.
Forecasting Football Fever: Exploring Seasonal Datasets in Deephaven.The hype seems to reach an unbearable level by the time the playoffs roll around.
The Spanish football league commonly known as La Liga is the first national football league in Spain, being one of the most popular professional sports leagues in the world.
Premier League 2019/20 Review Using Python, R, and Expected Goals.I returned, and saw under the sun, that the race is not to the swift, nor the battle to the strong, neither yet bread to the wise, nor yet riches to men of understanding, nor yet favour to men of skill; but time and chance happeneth to them all.
Sports analytics is a fascinating but enigmatic field. These are my tips for breaking into the field that I love. Sports analytics is a fascinating but enigmatic field.
Football analytics and modelling of the FIFA. In this post we will perform simple data analysis and modelling of the FIFA 2019 complete player dataset following the CRISP-DM process . The dataset has been collected Kaggle. Dataset contains 1 CSV file.
Predicting Match Ratings of Football Players using Machine Learning. Using Machine Learning Technique to predict the Match Rating of a Football Player with the help of Match Stats.
Introduction to Data Science for Football, The utilization of data in football (or soccer) has become very important to develop player skills or match analysis.