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How machine learning in sports analytics is disrupting the game

Big data from sporting games provides the perfect playing field for optimised sports analytics
Although an unexpected field for statistics, sporting games have a record of observable data which make it a prime target for analysis. This has led to the field of sports analytics which uses historical data on players and matches to predict outcomes in future games, as well as assist coaches with data-backed strategy decisions.

There are over two hundred recognised sports worldwide, hundreds of championships each year and countless matches between different sport teams. Many of these games are recorded both with real-time score keeping assigned to relevant players, as well as video footage of each game. Some teams are even introducing wearable technology on players in order to track their individual movement and heart rate throughout the match.

All of this data provides analysts with a bank of information to use in machine learning models for optimising sporting predictions and inferences. The capabilities of sports analytics ranges from predicting the outcome of a game to analysing team and individual performance in order to build new strategies.

Previously, coaches and players would have to spend hours rewatching game footage in order to visually analyse the tactics used by their team and their opponents. Sports analytics can provide teams with more efficient and accurate information.

It can also be used by sport bettors and betting organisations which try to predict the outcome of individual matches and tournaments, in order to understand how to place bets. The detailed probability that a machine learning model can produce, from analysing sporting events, can even be used to know how to price bets appropriately.

Just imagine if machine learning could predict who will win FIFA World Cup Final?

Sports analytics can transform the way viewers watch and interact with a game, while simultaneously giving players and coaches more control on their performance.

One can imagine sport teams deciding whether to sell or buy a player based on their data, or encouraging sponsorship investment with data-backed predictions. And in this way, taking the sport marketplace and the game itself to another level.

It is a relatively new field, but with the big data from sporting events and the ever-improving deep learning software, the potential of sports analytics has yet to be realised.

OLSPS Analytics is an international leader in Predictive Analytics, Artificial Intelligence and Machine Learning. Contact us today and we will develop the most accurate predictive model based on a structured and unstructured data.

OLSPS Analytics' press office