Fastbreak AI Partners with Lega Serie A for Fixture Scheduling

Jun 5, 2026
Fastbreak AI has entered a multi-year partnership with Lega Serie A to use its Pro Schedule platform for managing Italy’s top football league fixtures, optimizing club needs and broadcast requirements.

Fastbreak AI and Lega Serie A have announced a multi-year partnership to manage fixture scheduling for Italy’s top football league, according to a press release. The league will use Fastbreak’s Pro Schedule platform to balance fixture demands, club sporting needs, and competitive fairness.

Developed using mathematical optimization and machine learning, the Pro Schedule system helps generate season calendars that account for venue availability, rest periods, blackout windows, and broadcast requirements. The platform supports leagues in creating balanced schedules that align with team and broadcaster preferences.

Lega Serie A CEO Luigi De Siervo said the tool will help the league handle complex scheduling requirements more efficiently. Fastbreak CEO John Stewart noted that the technology is designed to give sports leagues flexibility and control when managing season-long scheduling challenges.

Fastbreak’s scheduling technology is already used by more than 65 professional sports leagues, including the NBA, NHL, MLB, and NRL. With this partnership, Serie A aims to produce fixture lists that better reflect the needs of clubs and fans while maintaining competitive integrity.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.

Free newsletter

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more
Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.