Achraff ADJILEYE
Achraff Adjileye is a research engineer passionate about football analytics and artificial intelligence. He is the founder of the BALLER project, which aims to build a foundational model for football analytics—powering the next generation of context-aware football analysis, much like GPT revolutionized text understanding.
His vision: Football is the ultimate team sport, yet most analytics treat players as isolated individuals. Players are often represented by radar charts of individual statistics, ignoring the rich collective context that shapes their identity. While this approach transformed data-driven scouting, it is inherently prone to misinterpretation, leading to costly mistakes in transfers and strategic decisions. Achraff works every day to create a football analytics world that respects the collective DNA of the beautiful game.
Session
FootballBERT introduces a new way of representing football players — not as static IDs or statistical aggregates that fluctuate wildly over short periods, but as contextual embeddings learned directly from match data.
Built on a Transformer architecture and trained through a Masked Player Prediction (MPP) objective, FootballBERT captures how a player’s identity emerges from teammates, opponents, and coaches tactical demands — much like BERT learns word meaning from sentences.
Openly released on Hugging Face, FootballBERT is a plug-and-play foundation model whose embeddings can be integrated into any downstream system, paving the way for player-aware analytics across performance modeling, recruitment and prediction.