Made In Africa Sport has unveiled an AI-powered NPFL Supercomputer that will predict all 380 league matches using 38 million simulations and one of the largest historical databases in Nigerian football.
As the 2026/27 Nigeria Premier Football League (NPFL) season kicks off, Nigerian football is stepping into a new era of data-driven analysis.
Made In Africa Sport (MIAS), a sports technology and media company, has launched an artificial intelligence-powered supercomputer designed to predict every match of the new NPFL season. The platform, available at npfl.madeinafricasport.com, combines historical data, machine learning and probability modelling to forecast match results, expected goals and the eventual league table.
The project represents one of the most ambitious uses of analytics in Nigerian domestic football, with MIAS aiming to transform how clubs, journalists and fans understand the league.
Unlike generic football prediction models, the MIAS Supercomputer has been built specifically around the realities of Nigerian football.
The system draws on a database of more than 8,000 historical NPFL matches, making it one of the most extensive collections of league data available.
To generate its predictions, the model runs 100,000 Monte Carlo simulations for each of the 380 fixtures, producing a staggering 38 million simulations across the entire season.
Rather than simply predicting winners, the platform calculates the probability of every possible outcome, from title races and continental qualification to relegation battles.
Beyond predictions: Building a football data ecosystem
Speaking at the launch, MIAS Executive Director Enitan Obadina said the platform was created to address the lack of data-driven conversations surrounding Nigerian football.
“For a league with as much history as the NPFL, we still do not use enough of the data we have,” Obadina said.
He explained that football discussions are often driven by opinion rather than evidence, and the company wants to provide supporters and analysts with a stronger statistical foundation.
He added, “What we are trying to do is put a proper data layer behind those conversations. We are not saying the computer knows what will happen. Football does not work like that. What it can do is show the probability based on the evidence available to it.”
