Just as in other sports, analytics has exploded in rugby. Across both League and Union, clubs at professional level are competing to find innovative and impactful ways to exploit the vast amount of data collected both in training and on matchday. James Bletsoe is the Head of Analysis at Leeds Rugby, a department that covers both Leeds Rhinos Rugby League and Yorkshire Carnegie Rugby Union. Working with a relatively small team, James also provides analysis for the many academy sides under the umbrella of the two professional sides, a demanding setup that necessitates some slick operating.
One of the things James notes about rugby league is that though players naturally have different roles, it is a sport in which you can compare contributions relatively easily. English rugby league is at a disadvantage, though, when compared to the likes of Australia. The salary cap is two or three times smaller than it is Down Under, and the talent pool in England is relatively limited, given that its primarily a northern sport. English teams are also limited to a relatively small squad, with 17-man match day squads picked from just 25. This all affects recruitment, promotion from the academies, and player retention.
Analytics can help coaching teams and scouting teams pick out the hottest prospects despite the limited pool. For this, James and his team use ‘game scores’ a system in which actions are attributed points or deductions based on their worth on the pitch. The points are weighted more to pressure situations like tight games, as opposed to ‘when the team is winning 70-0.’
The metrics collected are then assigned to positions - i.e., what is important for a player in that position to be good at - and from there they can begin to compare their options. This information, coupled with things like off the ball data (which James notes a lot of data collection agencies don’t cover), can give the Leeds Rugby team a solid picture of their personnel, and players have been moved on as a result of showing a decline. Each game is personally coded by James himself, which gives you an idea of the scale of the operations. Interestingly, each game will see the team award different values to different actions based on the game plan for that week, a dynamic way of measuring performance that by extension measures player adaptability.
Getting players on board with data has been a challenge for analytics teams across sports since it exploded a number of years ago. ‘This is probably the biggest challenge we had when we brought this in,’ James said. ‘We tried to make it really visual for players. A traffic light system is simple, I know it’s used a lot, but it’s effective. Players know if it’s a red then they’ve not been good enough, if it's a green they’ve played well. Simple. We base that on previous years’ data and worked out percentiles for where those traffic light boundaries were.’ James and his team also added a further bracket, blue, to signify the real top end of performances. Though a basic form of data visualization, being able to easily communicate performance reports to players improves buy-in.
James and his team also use data to build game plans. Using data to identify where points were won for opponents Castleford - in the 2014 Challenge Cup Final - and where their key strengths were, Leeds were able to pick them apart. By highlighting and mitigating one particular strength of their opponents’ game, Leeds won comfortably, something James still includes among his proudest moments in analytics.
Similarly, the team at Leeds Rugby identified a strong correlation between a team’s net line breaks - line breaks achieved minus line breaks conceded - and their final league positions. Then, by focusing on improving their probability of achieving a line break, and finishing the season with more than any other team, results saw an uptick and the team finished top of the league and won the Challenge Cup. It’s simple but effective implementations like this that make Leeds Rhinos such a successful side analytically. For James, the key things are ‘nailing the core fundamentals’, ‘not overcomplicating just because you can’, and ‘understanding your coaches and your players’ before you can offer insight that fits.