21/03/2016 06:56 GMT | Updated 22/03/2017 05:12 GMT

Lifting the Lid on Rugby's Data Revolution

I previously wrote on how rugby is at the forefront of a data analytics revolution in sports. Coaches, players, and fans are all enjoying the benefits of new insights generated by Accenture's analysis -- we process nearly 20 million rows of data to determine what is useful to store for further analysis, which ends up being typically two million rows of data per match. But how does this all work? What is the technology behind the stats, and how do we bring it to life?

We work with Opta, the official data company for the RBS 6 Nations, who provides us with the numbers to crunch as each game plays out. The data that Opta gathers is coded live and shared immediately with Accenture for real-time analysis. We then analyse the game data alongside historical data stretching back for more than 15 years to score how important key events are to winning or losing a game. For example, were the number of lineouts in the opposition's 22 more important than the distance kicked?

Once the data is gathered, analysed, and ranked using our own statistical models, the insights are then shared with our sports experts to review and add their assessment. For example, the data may show that two teams kicked the ball an equal number of times during their previous matches. However, it will not show why these kicks were made. Some teams kick for territory, regardless of the position of the opposition. They aim to move the ball downfield as quickly as possible, so that they can apply pressure in the opposition 22. Others use kicks to attack directly, aiming for specific targets, using grubbers to win one-on-one situations, or to rattle a weak link among their opponents.

Only an expert, using the data provided, can apply this context and broader appreciation of how different teams play. Aspects not shown by the data could include the influence of a coach, both on playing style and culture, the impact of public pressure, or the inspirational qualities of a player dropped for not measuring up on a statistical basis.

The expert review step can be an oft-overlooked aspect of data analytics, and one where companies can go awry. It's very important to have the skills to interpret the insights so that more effective and confident data-driven decisions can be made.

The final stage is to bring the insights to life through visualisations that can help tell the story of the game and frame some of the key insights that have been drawn from the analytics process. Like the use of experts, this can often be a forgotten step when using data analysis. However, it is vital in ensuring the outcomes are understood by different audiences, from players and coaches, and to the fans accessing insights on the RBS 6 Nations app.

At Accenture, we combine deep technical knowledge of data platforms, advanced data analysis capabilities and the expertise to interpret the analytics. I'm looking forward to continuing to use this winning combination to provide deeper insights to rugby fans in the final round of a tightly fought 6 Nations championship.