There’s a reason our current historical era is known as “the information age”. Every day, 1.145 trillion megabytes of data are created and captured by digital systems around the world, a figure set to climb exponentially.
In fact, according to Forbes, 90% of the world’s data was generated over the last 2 years. We experience the impact of this in all areas of our lives, from education to transport, engineering to culture. No part of our daily experience remains untouched by the implications of “big data”.
One prescient example of how this information impacts the organizational structures of a sector can be found in the sports industry. Tons of data is generated each day by sports organizations, ranging from athletic performance data to computational predictions of match-day outcomes.
This information then goes on to inform everything about the odds posted by sites like sportsbooks and all the way through to the coding of artificial intelligence behaviors in sports video games. Below we’re going to take a look at some of the chief ways that ready access to high quality data has changed the sports industry, from participation to spectatorship.
Training & Performance
The central reason behind the proliferation of sports data capture is that it enables teams, athletes and franchises to win and succeed in their field. This is because it helps them to identify the relative strengths and deficiencies in their performance, and thus work to counteract or amend them. Increased access to reliable sports data can also let organizations make predictions in the run up to an event, and make informed decisions based upon them.
This knowledge influences everything from deciding which combination of players to field, to what sort of strategy or play will yield the best results. Performance coaches can also analyze an individual’s performance data to such a fine degree that they can identify the increased risk potential of an injury developing, and take steps to prevent this ahead of time.
All of this makes the predictive power of sports analytics seem indispensable. Using pure data to run your overarching strategy can yield impressive results, such as when the Oakland A’s benefitted from an unprecedented streak of wins in the MLB by building their team upon performance data and statistics.
However, the most effective organizations have come to realize that no amount of data can deliver certain outcomes, and that the impact that leaders with intuition, imagination and experience can have on the fortunes of a team cannot be so easily displaced.
Another key area where sports data has proven important is in refereeing and rule-setting. The subjective perspective and opinions of a referee can sometimes lead to contentious decisions. By increasing the amount of data an umpire or steward has at their disposal, sports have become fairer.
From accelerometers inside soccer balls, to lasers on the touchdown line, a multitude of data capture sensors have enabled objective and accurate decisions to be made in real time to the benefit of all.
Spectatorship
Data capture is also revolutionizing sports spectatorship. Over the past decade, the type of information once closely guarded by athletes and performance coaches has begun to steadily find its way into on-demand entertainment platforms. This trajectory has taken two approximate forms, the first of which is that this information has been made more readily available to sports broadcasters and commentators.
This adds value and insight for viewers at home watching a game or match of their chosen sport on dedicated channels such as ESPN. This is because spectators get to benefit from sports pundits having access to additional information upon which to form their opinions, perspectives and predictions.
By giving commentators and pundits more access to sporting data they are empowered to pass on to viewers a deeper level of analysis in real time.
The second major vector by which sports data has begun to reach the viewer at home is by way of modern sports streaming services and apps, such as the NFL’s Redzone subscription service, or Formula 1’s F1 TV. These platforms go a step further by giving spectators direct access to live data.
Viewers watching a race via F1 TV are able to track the real time GPS telemetry of a car’s position, as well as access read-outs on progressive tire wear, lap time sectors and gear changes. This type of granular access to information means spectators no longer have to rely on an intermediary in order to arrive at their own understanding and perspectives as to how a sporting event is unfolding in real time.
This kind of data capture also has a big impact on those who enjoy sports betting, as sports books are able to offer increasingly accurate odds on sporting events as a result of having access to abundant and high quality data upon which to base their predictions.
Gaming
Sports data also impact the wider sports industry by way of the benefit it confers to developers producing sports video games. When EA set out to create the very first John Madden Football game in 1988, they ran up against hardware and programming limitations that prevented them from being able to realistically depict the complexity and nuance of football plays.
In fact, John Madden warned EA he would withhold his endorsement of the product if they failed to depict full 11-a-side matches, something that pushed the limits of early platforms such as the Commodore 64.
Fast forward to today and you’ll find modern titles such as FIFA, NBA 2K and the Madden series going above and beyond to deliver increasingly immersive and realistic gameplay experiences with each new release.
Modern sports sims make extensive use of real world data in order to arrive at gameplay that mirrors reality as closely as possible, from the way surface temperature and humidity affect a ball’s motion, to the use of motion capture technology to accurately replicate an athlete’s stride.
In fact, these titles are now so sophisticated that they are often employed by performance coaches as a pedagogical device for trainee athletes.