Sports Analytics Weekly by kubeia.io - 16/2024

What the historical data shows about past teams performance means for the future

Football is a game that continues to evolve and transform with each passing season. While the fundamentals remain (score goals, don’t let them in), the strategies and approaches to succeeding in those objectives are shifting. From how teams utilise seemingly routine restarts like goal kicks and throw-ins, aerial duels going the way of the dodo, or distribution-breaking passing and dribbling tendencies. The very fabric of the sport is being reshaped through innovative tactics and rule changes, so we've been diving deep into the data to uncover what’s changing.

An outfield player taking a goal kick used to be a rare treat, a sign that the goalkeeper had pulled a muscle and needed a willing team-mate to launch the ball towards the centre circle.But since a tweak of football’s laws in 2019, the once-humble goal kick has become an increasingly integral part of how a club chooses to build up play. Some teams choose to have a defender pass the ball laterally to the goalkeeper, some ask the goalkeeper to play short to team-mates in the box, while some still prefer to go long and direct.

In this series of liveProjects, you’ll join up with four different computer vision companies to explore computer vision models powered by the latest deep learning architectures. You’ll utilize the groundbreaking transformer architecture, which forms the driving force behind ChatGPT, to develop a series of increasingly complex models. Starting with a classifier to detect brain tumors, you'll move on to a segmentation algorithm and an object detection application capable of detecting construction vehicles and structural flaws. Finally, you’ll take on the role of an MLOps expert, implementing model deployment and explainability in the systems you’ve developed.

Outliers can be the most informative parts of your data, revealing hidden insights, novel patterns, and potential problems. For a business, this can mean finding new products, expanding markets, and flagging fraud or other suspicious activity. Outlier Detection in Python introduces the tools and techniques you’ll need to uncover the parts of a dataset that don’t look like the rest, even when they’re the more hidden or intertwined among the expected bits.

PandasAI is a Python library that makes it easy to ask questions to your data (CSV, XLSX, PostgreSQL, MySQL, BigQuery, Databrick, Snowflake, etc.) in natural language. xIt helps you to explore, clean, and analyze your data using generative AI.Beyond querying, PandasAI offers functionalities to visualize data through graphs, cleanse datasets by addressing missing values, and enhance data quality through feature generation, making it a comprehensive tool for data scientists and analysts.

In the latest SBC Podcast I am joined by The Gambling Commission CEO Andrew Rhodes for an in-depth chat about the regulation of gambling in the UK.

‘The White Paper’ was published last year and this document has resulted in some fierce debate across the gambling world, with the Gambling Commission coming under fire as accusations of bias, secrecy and incompetence have been levelled at them.

This chat provides Andrew with the opportunity to refute those claims and to discuss some of the issues that are of interest to you – the punters.

I didn’t get to ask about every topic on our list (restrictions, Minimum Bet Liability (MBL), the debate around statistics in gambling and many more items were considered) but it was great to get some clarity on things like affordability, the black market and bookmaker behaviour.