The Increasing Importance and Reliance on Data Analytics in Sports

The Increasing Importance and Reliance on Data Analytics in Sports

The most popular sports in the world remain somewhat rudimentary in their design and equipment. While protective equipment has evolved in leaps and bounds, soccer is still played on a grass pitch with a spherical ball, cricket requires (preferably) wooden stumps, a couple of bats, and a leather ball, and basketball uses two hoops and a rubber ball.

However, there’s so much money in sports at the highest level, with earnings mostly being predicated on success, that leagues, teams, players, broadcasters, and everyone else involved constantly seek ways to get a competitive edge. This is where all of the breakthroughs and applications of Technology come into play, with sports aligning with businesses to utilize data analytics. As we’ve reported here at TechProData on numerous occasions before, technologies are constantly shifting and it’s worth keeping an ear to the ground and keeping abreast of developments.

If there’s one sport that comes to mind for data analysis, it’s baseball. Brought to the spotlight by the Brad Pitt-starring movie Moneyball, by analyzing every bit of data possible from player performances, gems can be found at every level. Now, the MLB is a data-driven behemoth, and most other top-flight leagues have followed suit.

Collecting data to level the playing field

Sabermetrics was a solid foundation for baseball analytics, but modern data analysis in sports goes far beyond this core concept. Sports analytics is tipped to become a $4 billion market by the end of this year, with advanced technologies joining the game to streamline the effort while also expanding its reach. Not only are teams hiring data analysts, but whole franchises are to home in on ways to refine the spectator experience.

For teams, sports analysts are able to compile and review huge swathes of information and data points, but then boil them down to very clear-cut but insightful visualizations to relay the points to the decision-makers. Many sports teams around the world use SAS, a program that both manages data and helps users to understand the points. It was used by the Orlando Magic, a team that’s among the top earners in the NBA despite being in one of the smaller markets.

For coaching, conditioning, fitness, and scouting, wearable technologies have become essential. In the NFL, players are loaded up with small pieces of tech in their helmets and sometimes in other parts of their protective gear. The devices collect data on movement, impact, and other useful data that coaches can analyze to help improve the player, and physiotherapists can view to monitor potential injuries.

Data-driven predictive modeling based on the performances of players and their histories can also greatly help talent scouts find gems. For smaller teams, this can be an invaluable exercise, with machine-learning algorithms indicating where the clubs can save money on fundamentally strong players. As market prices are often driven by aspects like player popularity, assumed prospects, and the press, data points can help teams avoid costly mistakes as well.

Spectators also get a piece of the sports analysis action when they watch games through leading broadcasters. The massive streaming platform that is Hotstar integrates many key live statistics throughout its broadcasts, giving viewers more insight into the happenings on the field in real-time. Not only does this give them more knowledge and a more immersive experience, but viewers can then utilize that in-depth data elsewhere, such as to call events in the game.

Transforming the sport of cricket with data

Cricket analytics – or “Criclytics,” if you will – has transformed the game in a very similar way to its bat-and-ball cousin. Not only have top domestic teams, particularly those in the IPL, been employing sports analysts for years, but the ICC has also been incorporating it into its competitions as well – even though the ICC doesn’t run a team. The organization collects data throughout the year, tracking over 531,000 players across nearly 12,000 grounds.

For the teams, coaches, and captains, the data collected is just as integral for improving performances as it highlights weaknesses and dangerous players on the opposing team. A grand example of this in action came with the use of the analytics system Pdogg by the South African national team in 2010. Coming up against the indomitable Virender Sehwag, Graeme Smith was informed that putting out a deep third man from the start of the Test – a very uncommon practice – would help to stifle the opening batsman, and it did.

Coaches get a better look at the real-time performances of their players through bat attachments, helmet tech, and the technologies used by broadcasters, such as ball-tracking. One such advanced bit of kit is the Intel-collaborated startup Speculur BatSense, from Bengaluru. With a small sensor atop the handle of a cricket bat, it can store and emit data via Bluetooth, measuring: bat speed at impact, impact angle, follow-through angle, back-lift angle, and more.

While the real-time, in-play data feeds coaches, teams, and players, it’s performance data that feeds the spectator side of cricket, especially when it comes to the viewing and betting experience. To keep the odds as accurate and competitive as possible, the best cricket betting app in India compiles all of the old performance data as well as live event data, such as injuries or form, to create odds that reflect the match or competition. Such a collection of cricket data also allows for accurate odds on deeper markets, like player props.

People can use the data collected and reflected as odds by betting platforms to get a clear view of how statistically likely an outcome is – be it a player to get a century or a team to win by so many wickets. Also helping spectators get a deeper look at their favorite sport are the statistics websites like ESPNCricInfo. The Insights tool, in particular, showcases cricket’s big data analytics in action on a player-to-player basis.

Data analysis and sports management now go hand-in-hand, with the most successful teams and associated parties evidently making the most of the technologies and professionals to get an edge wherever possible.

I am a full-time professional blogger from India. I like reading various tech magazines and several other blogs on the internet.

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