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A data-driven look at how ageing affects the modern NBA. How old are the league’s best players? Are modern players getting younger? Who’s getting playing time?
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.
How Many French Fries Do You Have to Eat to Finish the Tour de France? Find Out with Help from Wolfram|Alpha. The Tour de France is a multi-day bicycle race which ends in Paris on the Champs-Elysee, a very big street in the center of the city.
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
The fixed effects are quite large for some coaches — larger than the Win Share metric for superstars on All-Star seasons. Values range from -25 to +21, with the mean being 0.15. This means that a value of +10.0 indicates that the coach generates about 10 additional wins per season relative to the mean.
Building predictions with a model, data pipelines and a Monte Carlo simulation. Expected score is calculated by comparing the Elo ratings of two participants, and it's a value between 1 and 0. An expected score of 1 means the driver will always win a matchup, while an expected score of 0.5 means they'll win half the time.
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
I Was Better in the C-Suite Thanks to LGBTQ Flag Football. In some really interesting ways, the lessons I learned in that very busy volunteer role turned out quite handy in my career a few years later when I accepted a C-level job.
The online sports betting industry has seen so many ups and downs with the time, but recently, this industry has taken the whole world by storm. Various leading Sports Betting Companies are providing advanced service and offers to the users across...
In many team sports, in-depth analytics enable teams to have the edge in strategy, scouting, and performance benchmarking. Ensuring Racing Safety. Making Smarter Scouting Decisions. Enhancing Shooting Accuracy. Improving Strategy and Viewing Experience.
![This is image title](https://customerthink.com/wp-content/uploads/Trending-Sports-App-Ideas-696x331.jpg "This is image title") Want to build a sports mobile app for your startup and looking out for an exclusive idea? You are in the right place....
Audio Onset Detection: Data preparation for a baseball application using Librosa. Use the sound to identify batting timing in a video.
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.
Step by step guide to train and classify images in just a few lines of code. I will use it to build and train a deep learning model to classify different sports fields on Colab in just a few lines of codes.
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.
Moneyball, Machine Learning, and Why I Seek the Holy Grail of Sports-Tech.This is the story behind the inspiration of my mid-career vision quest in search of the holy grail of sports-tech.
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.
The corona crisis affects our daily lives in ways that we previously never thought possible. A couple of weeks ago, the Belgian first division soccer teams played their first games of the new season.