All articles
If we can accurately capture the movements of football or volleyball players, how can algorithms process this data to give us important information?
The best-selling book Moneyball by Michael Lewis changed the way people thought about sport, particularly for those with the biggest stakes. Lewis’s book helped bring about a revolution in which player performance was measured and assessed using an evidence-based approach rather than a tradition dominated by experience and intuition.
Since then, sports scientists have attempted to replicate the success of this approach in sports such as basketball, soccer, American football, and so on. This science is driven by the relatively new ability to gather vast amounts of data about the players and the play while the game is in progress.
Revolutionizing Player Recruitment, Training, and Performance
Sports organizations are adopting a data-driven decision-making strategy at all levels, from player recruitment to fan engagement, which has led to more investment in data services and analytical solutions. Given the exponential growth in the sports industry and related businesses, it has become clear that technology and sports are becoming further intertwined in a multitude of ways that will benefit teams, fans, and the industry at large.
Baseball was one of the first sports to adopt big data in player scouting and recruitment and teams now have dedicated staff focused only on analytics. They use performance data to optimize their lineups and improve team competitiveness. Teams draw up a complete profile of the players from a continuous flow of data, which help them decide what they should do. Even players have begun to adopt data into their daily and offseason preparation routines, to monitor caloric intake, set training levels and even interact with fans.
Data aggregation and monitoring technologies are becoming increasingly sophisticated. Player performance is recorded and analyzed by technologically advanced cameras, sensors and wearables that account for every aspect of the game. These technologies provide the tiniest details about player performance and even notify staff when a potential injury could occur (and even how to avoid one). In contact sports like American football or rugby, wearable sensors have proved to reduce injury levels by monitoring and analyzing the intensity of activity and impact of collisions, and by reviewing historical data.
Changing the Dynamics between Rights Holders, Sponsors, and Fans
Modern fans don't merely watch sports — they connect in real time, socializing, critiquing, and engaging deeply with each event. Due to their loyalty, advertisers are increasingly valuing their relationship with fans, leading to higher sponsorship budgets.
The North American sports market alone is projected to grow at annual rate of 3.1%, from $69.3 billion in 2017 to $78.5 billion in 2021. Sports media rights are expected to grow at the fastest pace ever, from $19.1 billion this year to $22.7 billion in 2021. Rights holders and brands, that collect and apply their consumer data, have many opportunities, but they have to deal with shortening consumer attention spans and increasing competition. A successful strategy is a more flexible approach to adapt to unexpected events to take advantage of opportunities using insights from fan/customer data.
Not surprisingly, social media play an important role in the sports industry. New revenue streams are being generated because of increased fan engagement on social media. Athletes and influencers have become incredibly important for connecting with digital audiences and 'accidental' endorsements (when a celebrity athlete uses a product or service 'by chance') have proven to boost a brand’s popularity instantly.
Taking Advantage of the Emerging Sports Gambling Market
Nowadays teams use huge databases containing their players’ performances to their advantage, but these same sets of data can be also used in sports gambling. Big data can revolutionize the way we gamble.
There are many companies, like Wyscout and Optasports, which collect sports data. They can analyze every single element of a sports event: every single touch made by each player; the angle and the strength; every single bounce the ball makes etc… Thanks to this data and the use of advanced statistical models, sports betting professionals can predict the outcome of an event and analyze the individual contribution of each player, creating advanced betting strategies.
This data are analyzed by powerful machines and the more the data we "feed" them, the more they learn and thus generate increasingly accurate forecasts.
Now you can build machines that analyze all the individual events of each game in the world, quantify how each of them is related to the outcome, check the market and the prices and create the best betting strategy.
