Data-driven decision-making has become an essential aspect of business success across industries. However, it’s the sports industry that has been pioneering performance analytics.<\/p>\n\n\n\n
Analytics in professional sport has been around since the 1970s, but in 2003 it received worldwide attention thanks to Michael Lewis\u2019s best-selling book Moneyball<\/em>, where the statistical analysis of baseball records, also known as sabermetrics,1<\/sup> was used to make decisions about player performance and to discover the secret to success in baseball player evaluation.2<\/sup> Today, sports analytics has gone beyond just tracking data on paper: the market is expected to reach almost $4 billion by 2022, and most major professional sports teams have analytics experts on staff to interpret every aspect affecting player performance.3<\/sup><\/p>\n\n\n\n The National Football League (NFL) understands the importance of being able to track individual player performance through sports analytics and data, and has done so successfully for the last few seasons. The NFL do so by placing small sensors in each player\u2019s shoulder pads, which track their game performances throughout the season. They\u2019ve even taken it a step further, and shared their players\u2019 tracking information with all the clubs.4<\/sup> The goal? To provide clubs with the data to understand and analyse their competitors\u2019 (as well as their own) strengths and weaknesses, and to adapt strategies accordingly.<\/p>\n\n\n\n Wimbledon has similarly been tracking individual tennis player performances for years. The player reports \u2013 consisting of text as well as video footage \u2013 helps tennis players identify their strengths and weaknesses, and can be used as a coaching aid after the game.5<\/sup> \u201cWe have over 150 staff on the premises and we capture over 3.2 million data points throughout the course of the Championships,\u201d says IBM Wimbledon client executive Sam Seddon. \u201cThe data entry team is made up of around 48 people \u2013 all of them tennis players \u2013 and most of them are courtside. They capture the speed, serve location, and rally count. On bigger courts, one person calls the match like a radio commentary and the other person is inputting the data into the systems.\u201d6<\/sup> This information is not only stored for the benefit of the players, but is also shared online and on spectator screens.<\/p>\n\n\n\n In basketball, some teams use 3D trackers to track and analyse every shot, and gain insight into shooting accuracy and patterns.7<\/sup> This way, coaches get a full understanding of player position, performance, and accuracy on the court.<\/p>\n\n\n\n Sports data analytics is not solely used in ball sports. Ducati uses data gathered from sensors on their motorbikes, which informs what changes should be made to the configuration of the bike.8<\/sup> By running various racing scenarios, including track and weather conditions, machine learning techniques are used to inform the bike engineers on modifications needed to achieve faster lap times.<\/p>\n\n\n\n Few sports use data analytics like Formula 1 (F1). The modern F1 car is an intelligent and connected data system, monitored by hundreds of sensors that measure lap times, G-force, tyre and brake temperatures, air flow, engine performance, and driver biometrics, just to name a few.9<\/sup> In Formula 1, perhaps more than anywhere else, big data drives big decisions.<\/p>\n\n\n\n When it comes to winning, the entire race is not left up to the driver. F1 racers have a well-trained crew trackside, as well as a host of engineers, mechanics, and analysts offsite, making decisions based on the incoming data. Events such as pitstops can impact a driver winning or losing a race. In 2016, the Willams team connected four pit crew workers with biometric sensors to measure heart-rate variability, recovery times, breathing rate, and estimated core temperature. This data allowed the team to analyse and optimise the crew\u2019s fitness training, with the aim of improving performance in a role where every second counts.10<\/sup><\/p>\n\n\n\n The vast amount of data collected during a race is also used afterwards in simulations to improve the car\u2019s systems for the next event. According to Chris Dyer, head of vehicle performance for the Renault Sport F1 team, simulators provide an ideal opportunity to check for engineering faults, and to test alternative engineering scenarios. \u201cThere\u2019s a lot of stuff we can do here, better than we can do at the track, faster. Is it an aerodynamic problem, is it a tire modelling problem, is it a suspension modelling problem? That will focus us, and we\u2019ll review it through the year.\u201d11<\/sup><\/p>\n\n\n\n As the application of data analytics continues to be adopted in many sectors of industry around the world, F1 is likely to take further advantage of the benefits of the tech industry for the world of sport, using cloud computing, predictive analytics, predictive intelligence, machine learning, and prescriptive intelligence.12<\/sup><\/p>\n\n\n\n Innovation in a business should be seen as a team sport. Having the right team of talent working on a project will have a higher likelihood of success.13<\/sup> However, the ability to identify and combine those specific individual talents of your team members can be a challenge.<\/p>\n\n\n\n Tracking and measuring the individual\u2019s performance over time may help strategise for the team\u2019s ongoing and future success.14<\/sup> Those who embrace data analysis early on could enjoy a competitive advantage, and can adapt their tactics accordingly. “The real thing that will happen is that, while there will be an impact in year one, the teams who start adapting early will have like 10 times more value in year three and four than other people who are slower,” explains Rajiv Maheswaran, CEO of machine-learning company Second Spectrum, an ESPN partner that processes individual performance tracking data.15<\/sup><\/p>\n\n\n\n Here\u2019s what businesses can learn from sports data analysis for team performance:<\/p>\n To gain the benefits of individual performance tracking, you\u2019ll need:<\/p>\n When it comes to understanding sports fans, and what they want, the sports industry aggressively uses data analytics to do so. Sports organisations gain insight into what fans are watching, and what time they are watching it, thanks to digital engagement data and data patterns from online sports viewing, app logins, and online video views.26<\/sup><\/p>\n\n\n\n Data-driven campaigns are proving highly successful when it comes to marketing ticket sales to millennials over social media channels.27<\/sup> Data analytics can also be applied to social media streams to understand fan sentiment, and to positively engage those fans via social channels. “Our content team puts a lot of resources into providing fans with unique experiences on game day through live social content,” says Eric Long, director of production with the Philadelphia Eagles. “Showcasing that work to more than 65,000 people in the stadium is a great opportunity to continue to grow our audience and provide value.”28<\/sup><\/p>\n\n\n\n Data from customer engagement can even be used within the stadium to understand fan movements through electronic tickets and fingerprint or retinal scans. In 2016, the New England Patriots started using data to track fan movement, tracking what fans buy at the pro shop to when exactly they buy tickets.29<\/sup> By analysing this data, organisations can predict everything from ticket pricing to adequate staffing on game day.<\/p>\n\n\n\n Sports organisations use software providers to analyse data that can potentially help them sell more hotdogs and beer, ensure cleaner bathrooms in stadiums, and improve congestion in the parking lot \u2013 all in a bid to improve the overall experience of local sports fans and drive better revenue.30<\/sup><\/p>\n\n\n\n Tactics to apply in your business:<\/p>\n Just as the volume of data increases, so will the use of data analytics in the sports industry. As data sources on and off the field continue to provide insights to key decision-makers on how to best manage their teams or individual talent, it also gives organisations insight into the hearts and minds of their fan base. Considering how deeply and effectively data is being mined in the world of sports, the potential applications, impact and scope a similar approach could have within the business world could be game-changing.<\/p>\n\n\n\nHow data analytics is used in sport<\/h2>\n\n\n\n
How sports analytics can be applied to business<\/h2>\n\n\n\n
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What businesses can learn from fan engagement and sports data analytics<\/h2>\n\n\n\n
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