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🇳🇬 Nigeria /Technology

AI Supercomputer Launched to Predict the 2026/27 NPFL Season

From Premium Times · () English

Translated from English and summarized by DistantNews. Read the original for the full story.

At a glance

News Named sources New plan
  • Made In Africa Sport launched a model that uses more than 8,000 historical NPFL matches to predict the outcomes and standings for the 2026/27 season.
  • The system runs 100,000 Monte Carlo simulations for each fixture, producing 38 million simulations across the 380-match season.
  • It factors in recent form, head-to-head records, venue strength, goalscoring and transfer activity, while presenting probabilities rather than guaranteed results.

Made In Africa Sport has turned the Nigeria Premier Football League into a season-long data experiment, launching an artificial intelligence-powered supercomputer to predict all 380 matches of the 2026/27 campaign.

The model draws on a database of more than 8,000 historical NPFL matches. For every fixture, it runs 100,000 Monte Carlo simulations, producing 38 million simulations across the season. The competition began on August 28 with 20 clubs scheduled to play across 38 matchdays.

The system does more than select a likely winner. It calculates each club’s probability of finishing in every position, including its chances of winning the league, qualifying for continental competitions or being relegated. Predictions will be updated after each matchday as new results change the teams’ performance profiles.

What we are trying to do is put a proper data layer behind those conversations

· Enitan ObadinaThe MIAS executive director explained the goal of using historical data to analyse the NPFL.

The model combines historical and recent results with head-to-head records, home and away strength, goals scored and conceded, and transfer activity. Transfers are included to reflect changes in squad quality that may not yet appear in previous results. The platform provides the highest-probability outcome, expected goals, team ratings and a projected final table.

MIAS Executive Director Enitan Obadina said the project aims to bring more evidence into discussions about the league. “What we are trying to do is put a proper data layer behind those conversations,” he said. He added that the system does not replace football knowledge or judgment. “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, and that gives you a much better starting point than simply saying a team will win because it looks”

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, and that gives you a much better starting point than simply saying a team will win because it looks

· Enitan ObadinaObadina stressed that the model shows probabilities rather than certain results; the source sentence ends mid-quote.
About this summary

Originally published by Premium Times in English. Translated, summarized, and contextualized automatically by DistantNews, with a note on how the source frames the story. Not individually reviewed before publishing. How this works.

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