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Football today is no longer just about instincts and passion; it has become a game driven by data. Across the world, clubs are using analytics to optimise performance, influence decisions, and shape transfer strategies. The question now is whether Kenya’s SportPesa Premier League can follow suit and use data not only to analyse opponents but to transform how clubs are managed and how players are developed.
A close look and a point in reference has been Brighton’s operation over the last few years. The club has used data to scout players and sell them at profitable prices. They bought Moises Caicedo for around €4.5 million and sold him for about €115 million, Marc Cucurella was bought for €15 million and sold for €65 million, while Mitoma recently had a €65 million offer from Saudi Arabia rejected. How do they do it? The answer lies in Jamestown Analytics. Brighton’s success is attributed to having access to information from almost every league in the world, something that could not be achieved through traditional, eye-based scouting. Brighton’s technical director, who previously worked for Jamestown Analytics, has been central to this success, leading to impressive results in scouting and selling players like Mac Allister, Trossard, Minteh, and O’Riley at significant profits. Their success also ties back to owner Tony Bloom, who himself has a background with Jamestown Analytics. It all narrows down to data.
This raises the question of whether Kenyan Premier League teams, now under the SportPesa Premier League, implement data analytics not only in analysing opponents’ tactics and style of play but also within their own teams to track performance indicators such as player movements, passing patterns, opponent set-piece strategies, throw-ins, heart rates, and other physical metrics. Heat maps and expected goals (XG) allow coaches to create models that optimise game plans. The use of catapult analysers and, recently in CHAN, the use of player tracking kits shows how player data can answer simple but important questions such as “what does the data show?” or “why are short corners better than long ones?” The answers all lie in data.
In the Kenyan football scene, most coaches can be described as people who rely on emotions and feelings rather than data. Yet, data is revolutionising football in ways that go far beyond the pitch. For instance, in contract negotiations, Kevin De Bruyne worked with Analytics FC when negotiating his contract. He used data to formulate a report on his on-field contribution and financial value by analysing every touch, movement, goal, and assist in comparison with other players across Europe. This helped him save on agent fees and gave him strong ground in his negotiations.
Other clubs that have gone hard on implementing data-driven operations and have seen great results include CD Castellón, owned by data scientist Haralabos Voulgaris, and Como 1907, both customers of Jamestown Analytics. Their promotion and success have partly been attributed to the use of data-driven decision-making. The biggest question now is whether Kenyan top-flight clubs need to start adopting and implementing data-driven solutions, decision-making, and performance analysis to improve both the quality and competitiveness of the league.
