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Michael Kwambo: Sport and data are not mutually exclusive!

NAIROBI, Kenya, Sept 3 – Yep…that’s right!

Sport and data go hand in hand, and in more ways than we can imagine. It is a relationship that manifests itself through reactions from full time scores and results from fixtures and competitions or disciplinary sanctions in the form of red and yellow cards, false starts and many other related events and statistics that make sport worth watching, and following too.

Locally, many a sports team and organization seem not to care about data beyond the list of players, officials, bio data, league results and standings at the close of the competitive season.  The rest, whether by intent, or design, is irrelevant.

Historical records and related vital statistics (such as your most capped player, all time goal, try or points scorer, team colors and jerseys over the years, youngest or oldest player to attain a certain milestone) are either incomplete or impossible to trace and recover.

This is most unfortunate, especially when you realize that, away from collecting data for sentimental and statistical reasons, sports management is increasingly becoming scientific and data is key to driving a lot of decisions on and off the pitch.

Data is now being collected in sporting disciplines globally with the intention of steering teams and athletes to victory and ensuing success in and out of the playing arena.

Sport is part of the basic fabric of contemporary Kenyan culture, and with goodwill and strong governance systems in place, can be a massive contributor to the country’s economy.

A strong, vibrant Kenyan sports industry has the potential to exploit the opportunities that may arise from data, big data for that matter. Other industrial sectors are using data to reach and connect with their audiences, so why should sport be the exception? Especially when you consider that sports teams and organizations can use data to enhance both player, organization and fan experience?

So how do we link data and sports? We can share and utilize data on granular levels to enhance the experience for all parties involved. Everybody in the sporting realm, from journalists, commentators, coaches, players and enthusiasts can interrogate data to extract the real story behind every sporting event ranging from player or team selection to fan engagement.

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You’d have to agree that this works much better than intuition, experience or anecdotes from veterans who may distort data and history as they regale younger audiences with tales, usually at the bar counter of heroics from their playing days.

To give a lot more credence to this conversation, I would like to go across the pond to the United States of America and the city of Oakland in California, the home of Major League Baseball (MLB) side, Oakland Athletics. The famous story of the Oakland Athletics, popularized in Michael Lewis’s book Moneyball, showed the power of big data in sports as it depicted the revitalization story of a struggling team using evidence-based recruitment tactics.

Data helped Oakland Athletics’ general manager Billy Beane pick his talent based on the numbers, not gut feeling – and to great success. His actions from 2002 have set the stage for innovations across the sporting world, leading to smart recruitment decisions, training regimes and tactical approaches across myriad sporting disciplines.

Fast forward to the present and we are living in a moment in time where training has increasingly become a full-time activity as doors continue to open for professional sports in more outposts around the world.

Athletes are working hard to have an extra edge, coaches on the other hand are working to build databases of their athletes as they seek to gain insights into what makes top athletes succeed at major competitions, and which factors play the biggest role. This data is also helping competitors learn more about the challenges they face during training.

On the fan side of things, nowhere is there a bigger source of data than social media. Of course, fans can use these platforms to interact and find more information about their favorite teams – but that’s not even the biggest role of social media in sports. Teams can leverage data from social media to attract and engage fans, encouraging them to buy tickets and attend games.

-Clubs and organisations-

Sports teams and organizations have a lot to gain from social media usage as many users of social platforms tend to be teenagers and young adults. This is a great way to make their various sports disciplines and organizations attractive to newer audiences by way of engagements, particularly with millennials who are extremely active on these social media platforms.

We’ve only scratched the surface with use cases of big data and sports, and that’s the most exciting thing moving forward. Every bit of data that is being collected now could be of use in the future, with many applications still in their early stages.

Wearables, for example, can help monitor players on the field and are becoming increasingly advanced as time goes on, even becoming integrated in players’ uniforms! Coaches can already check on players’ fatigue and hydration levels. As these devices become smarter, player safety and performance will also be tracked, analyzed and improved.

Data from fans will continue to influence marketing efforts and decisions about sporting events, such as when to schedule games and how to cater to fan preferences. Advances in big data can even lead to career opportunities for avid fans with a talent for numbers. The possibilities are endless for coaches, players and fans – and we’ll only continue to see data playing a larger role in sports moving forward. Keep an eye out for big data advancements with your favorite team!

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As I sign off, I would like to remind our sports teams and organizations that data collection and record keeping are important. I would further like to add that Kenya prides itself as Africa’s innovation hub and it would great to see big data innovations in Kenyan sports.

I mean…it only goes to reinforce the point that sport and data are not mutually exclusive!

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