Over the last few years, and following the global digitalization of society, analytical data has become integral to the future successes of many industries. Such information is being used far more frequently within the sporting sector with the National Football League developing vastly since its introduction back in 2016. The revolutionary implementation of analytics has been widely embraced by leading football teams and has since become essential to various elements including player performance and tracking.
Following the importance which is being placed on analytics, we’re going to look at how the NFL has changed since it began hiring data specialists back in 2016, while also discussing the purpose of the Big Data Bowl and how statistical analysis is being used within other games such as online poker.
What happened when the NFL started to hire analytics specialists in 2016?
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Across the sporting world, in-depth analytical data is being linked to performance improvements and increased short-term and long-term success. Analytics were beginning to find a home in sports during the early 2000s with the Moneyball concept, which was centered around using statistical data to drive decision-making processes, being considered by several football teams following its early triumphs in baseball. However, upon hiring data specialists in 2016, it became clear that statistical analysis had developed far beyond the previously limited approaches and teams were becoming far less reluctant to adopt the strategy for signing players. Throughout the last few seasons, and when assessing possible signings, the NFL’s advanced tracking service has allowed general managers access to raw data across attributes such as expected yardage, routes of coverage and speed.
Upon embracing analytics, and despite some resistance remaining, its introduction has had a significant impact on the NFL. Back in 2016, the Cleveland Browns hired data expert Paul DePodesta with the hope that his expertise would add a critical dimension to preparations. Although on-the-field performance didn’t immediately improve, the unconventional approach grew as many teams now believe that analytics result in greater staff efficiency. Before the rise of analytics, coaches had limited time in which to assess their opponents, however, preparation can now be carried out against much wider sample sizes due to the increased data pool. As we’ll see further down the page, that’s the same kind of analytical approach being adopted in fields such as poker, another area in which less onus is being placed on the decision-maker and more faith placed in technology-sourced calculations. With data now so easily accessible, a heightened focus is on communications within the NFL to ensure higher levels of efficiency are being achieved.
Aside from coaching efficiency, the rise of the computer has driven the sports industry into a new data-focused era. As already touched upon, along with analytics being used to track player performance, its implementation has become integral to preventing injuries. Injuries have a devastating impact on both clubs and players throughout most sports, with the cost of injuries in Major League Baseball totaling approximately $1.4 billion. While technology and data can’t guarantee that fitness problems never occur, their introduction has seen an injury reduction rate of between 20 and 30 percent according to a report carried out by Catapult and Kitman Labs. Such results have seen a consensus emerge throughout the football league that injury-related analytics will continue improving. Moreover, injury-related data is extremely beneficial for player recruitment as it outlines any potential future medical issues that players may face.
The Big Data Bowl
After analytics began to take flight, the NFL sought to continue embracing and incorporating data through the creation of the Big Data Bowl. While the work conducted by analysts is done behind closed doors, the tournament desires to identify members of the community for their talents and role within the sport. Although the competition has been developed to recognize the continued commitment to further advancing analytics within the NFL, the organization’s Senior Vice President of Football Strategy and Business Development, Damani Leech, believes the tournament also enables a focus on modern and innovative methods of approaching and using football data.
Furthermore, the competition encourages the wider analytics community to be a part of football’s future evolution. Despite fans already having access to some data through platforms such as Next Gen Stats, the NFL uses the Big Data Bowl to allow raw information and statistics to be handled in return for contestants picking between several areas of analysis including receiver route combinations and rule changes. Ultimately, the concept is designed with the ambition of altering trends in player performance and coaching.
The Big Data Bowl demonstrates how vital the analytical side of football is becoming among the industry’s leading figures. Although the competition is aimed at NFL development, the wider importance of the tournament cannot be understated. For many years, the sports industry has been considered rather simplistic, but the Big Data Bowl is one of many recent changes that have altered its outlook. In fact, big data goes so much further than just the NFL: just as baseball players no longer simply step up to the plate and swing, poker isn’t defined merely by 52 cards: information has changed the foundations of all kinds of popular games.
How is data being used in other industries?
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While there can be no doubts that analytical data in football has revolutionized the sport, there are some suggestions that players are now being viewed as statistics and not part of a wider sporting family. Outside of the NFL, however, big data has become central to individual games like poker, where an effective strategy can be the difference between high-stakes success and failure. Although the format of both games is very dissimilar, the influence of statistical data on each can be monumental.
Contrary to common belief, poker is slowing becoming less about luck and more about pre-planning and game management. Phil Simon, an experienced poker analyst, details that professional players enjoy more success than the average participant due to maximizing varied hand strategies and, rather crucially, possessing an ability to process valuable information while at the table. With that being said, although data itself holds incredible value to the player, it doesn’t guarantee a favorable result. Moreover, Simon explains that combining big data predictions with consistently playing high-level hands stand you in good stead for continued progression.
In 2008, ‘November Nine’, a four-month break in play, was introduced by the World Series of Poker. This decision was taken for several reasons, with one being that each player could use the time to evolve their poker game in their efforts to win the $8 million first-place prize. Along with hiring coaches and using statistical data such as VPIP% (average time of voluntarily using chips) and WTSD% (willingness for a showdown after a flop), online training and live poker games such as Texas Holdem allowed for the intertwining of big data predictions and consistent practice. Additionally, online poker calculators analyze ongoing games before providing analytical feedback on either how far ahead or behind your opponents you are.
The influence of big data in sport is only heading in one direction
Ultimately, statistical analysis has been pivotal in the NFL’s recent growth. From deciding who to sign to assessing the risk of reoccurring long-term injuries, big data is increasing efficiency while also saving teams millions of pounds. Moreover, the Big Data Bowl demonstrates how the industry isn’t content to stand still as it seeks to encourage the analytics community to shape the future of the sport. Whether players are possibly being viewed as mere numbers or not, the influence of big data in sport is only heading in one direction.
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