Anyone that knows me knows that I am the furthest thing from a sports fan. Although, while I have no basic understanding of sports, I do know technology and the many ways that data is changing the industry and becoming even more powerful in our daily lives. The use of analytics as a daily practice is growing at an unstoppable rate, so it’s no surprise that the sporting industry has also learned to take advantage of it as well. In the article below written for StraitsTimes, author Rick Scurfield, general manager, NetApp (APAC) discusses how unstructured data from live sporting events, such as tennis tournaments to F1 racing is analyzed and being used effectively to improve individual and team performance. Although most of the data mining is done behind the scenes at live sporting events, I see this in action everyday working for and with technology companies- Helping them find meaning in their data as well as storing, protecting and retrieving it when their team is counting on it.
In any sporting event, athletic excellence draws the fans. The climax is who hits the winning shot, such as Serena Williams' triumph at the BNP Paribas Women's Tennis Association (WTA) tournament in Singapore last weekend, or who crosses the finish line first, as in Formula One car racing. It all boils down to a split-second move.
But while fitness, training and nutrition are primary factors contributing to a player's performance more than ever today, technology is a vital part of the mix. More specifically, data analytics.
Vast amounts of data are generated in any event. Every second a ball is hit, or when an F1 car roars down the track, streams of unstructured data are generated.
Such data can yield useful statistics, information and insights - from individual performance to a team's ability to function together effectively.
The numbers game
OF COURSE, many spectators at the 10-day tennis fete at the brand-new Singapore Sports Hub were probably not overly aware of the vital behind-the-scenes role of data while they watched the biggest names in women's tennis battle for the coveted Billie Jean King trophy and a record purse of US$6.5 million (S$8.3 million).
But the ranking and value of the players they were watching were a result of analytic algorithms.
As well, more and more players are also using data analytics to improve their game. With big data analytics tools, coaches are able to drill down deeper into simple statistics such as aces, double faults, first-serve percentages and unforced errors to analyse player technique variations post-match point by point.
They can also analyse competitors' performance and behavioural patterns, and help develop an optimal strategy against each opponent, using predictive analysis. Information can be tailored specifically to the player's and coach's individual needs. And starting January next year, at WTA events, coaches will be able to give critical advice to players using real-time data analytics in between sets.
At big tennis events, fans enjoy the sport like never before by experiencing key player statistics on big screens. They can track the number of aces, unforced errors and double-faults at each tournament through real-time analytics tools.
In another highly competitive sporting arena, that of F1 car racing, a position change in the world championship has significant impact on points and leads to a multimillion-dollar rise or drop in prize money. Sometimes, more than 12 out of 24 cars are within one second of one another during qualifying rounds - 0.001 seconds can make you a winner or a loser.
F1 is a race against time - from development through to the chequered flag. The quality of design and development, the skill of the drivers, and not least a robust and high-performance technology infrastructure, contribute to the team's success.
More than 100 sensors sit on an F1 car, relaying gigabytes of data through telemetry to those who are involved. This includes real-time information about the tyres, engine, temperature and fuel usage which is used by the pit team to fine-tune in-race strategies. Knowing when to take the next pit stop can earn or cost precious points.
Data is also driving the design of the F1 car - teams analyse historical data, computational fluid dynamics simulations and wind tunnel testing results to shave off tenths of a second for the next race.
This year, with the sport undergoing the most disruptive rule changes in its history, new mandates include a move from V8 engines to greener 1.6-litre turbocharged V6 engines.
These rules require teams to leverage every single bit of intelligence they have to identify new opportunities for design breakthroughs. Every single component is individually designed for functionality and performance, and this relentless development is made possible only by analysing the approximately 1.5 billion samples of data generated in each race.
However, F1 fans have little access to such real-time data. Most have to rely on traditional commentary to comprehend the split-second manoeuvres happening throughout the track - it is even more difficult for fans watching the race live.
Competing in the tech arena
SPORTS have become a multibillion-dollar global business. Data analytics is no longer an option; it is now a necessity for the sporting fraternity.
A lot of advances have been made in this respect. For instance, companies such as SportingMindz and SportsMechanic have developed a range of data analytical solutions to help coaches, players and teams enhance performance. SportingMindz also provides interactive applications for fan engagement and data visualisation.
Sporting apps are already a big hit with fans. Every major sporting event is associated with a multitude of apps. These apps allow fans to watch live matches, check results, access statistics and background information of each player and his/her performance to date, and read or add comments about each game.
However, the main complaint is that much of what is provided on these apps is still not engaging enough. Imagine if a system could be developed that could give fans a true gauge of who is most likely to win - predictive real-time analytics could make all this possible.
The possibilities are limitless. For any data to be meaningful or useful, efficient and reliable data collation, storage, protection, retrieval and analysis is needed.
Technology will never be able to take the place of talent and teamwork, but it certainly can add some solid science to winning strategies. The future Roger Federer, for example, would be the player who can react better to real-time guidance. Even single-handed backhand maestros can gain an extra edge.