The National Rugby League is undergoing something of a data revolution. Data has drastically changed both American sports and soccer, and it’s beginning to take hold in the NRL.
As teams and analysts embrace sophisticated metrics and machine learning, the sport is undergoing a renaissance in measuring performance, devising strategies, and recruiting players. This influx of data benefits not only coaches but also everyday betting enthusiasts who leverage opportunities like a Ladbrokes sportsbook offer.
Soccer’s Data Analytics
Soccer has been a catalyst for the data revolution, with clubs like Liverpool FC leading the way by hiring astrophysicists and data scientists. Ian Graham, Liverpool’s former director of research, played a crucial role in discovering talents like Mohamed Salah and Roberto Firmino using advanced data analysis. They also appointed Klopp, who went on to become a huge success, because of an algorithm. The club’s success, including winning the Premier League in 2020 after a 30-year drought, has been attributed in part to their innovative use of data. Now, it’s inspired global sports.
NRL’s Growing Embrace of Advanced Analytics
The NRL has partnered with data companies like Stats Perform, collecting around 14,000 data points per game. This vast dataset provides the foundation for advanced analytics in the sport (and it’s come at the right time of the AI revolution…)
Teams are developing new metrics and models to gain deeper insights. For example, the Eye Test Expected Points (ETxP) metric aims to measure the expected points a team should score based on field position (a bit like xG in soccer). Another metric, the Deception Score (DS), quantifies a team’s ability to create offensive deception by measuring “push supports” per play-the-ball.
Some other metrics include:
- Player Ratings and Projections: Analysts are working on developing rugby league equivalents to baseball’s Wins Above Replacement (WAR) metric.
- Expected Points Model: Still in development, this model aims to determine which team “should have won” based on underlying performance metrics.
- GPS Data Analysis: Teams use player GPS data to analyse performance, including metrics like lateral movement.
These tools are helping teams gain deeper insights into player and team performance. It isn’t to become a slave to it, but as a second layer of validation for strategic decisions and areas of improvement.
Video analysis has already become more commonly used to dissect previous games. But, AI is helping club’s speed up this process by automatically selecting key moments and highlights. Wearable technology has also been adopted to monitors vital signs and physical responses during games and training. Sport science has drastically changed over the past decade or so, and this is thanks to more health metrics being monitored.
The integration of these data sources allows teams to create comprehensive player profiles, but it also optimises training regimens. Over training is a huge problem for professional athletes, and this is their biggest tool.
Who Benefits?
The data revolution in NRL extends beyond professional teams. Everyday fans and bettors now have access to advanced statistics and analytical tools, allowing for more informed wagering. This democratisation of data has led to community-driven data projects and forums, where fans can discuss and analyse team and player performance using sophisticated metrics.
As the NRL continues to embrace data analytics, the sport continues to evolve and the players are given a platform to further improve. The fans benefit, of course, from a high standard of play.
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