AI built for football
ScoutsCapital runs machine learning across the whole platform, from the moment media is uploaded to the moment a coach sees a better option drawn onto a match clip. Six AI systems are in production today, spanning computer vision, sequence modelling, and football-specific prediction.
Not AI as a feature. AI as the infrastructure.
ScoutsCapital Agent
Digital chatbot interface
Trust and safety
A safe community, protected by AI
Every piece of user-generated media is screened before it reaches the community. Dedicated models analyse the audio track and the video frames independently, detecting violent content and policy violations. Anything flagged is held back or escalated for human review.
Families, academies, and clubs get a platform that is monitored around the clock, at a scale human moderation alone could not reach.
- Cleared
matchday-warmup.mp4
Audio + frames analysed
- Cleared
u15-highlights.mov
Audio + frames analysed
- Held
training-clip-044.mp4
Escalated to human review
Personalisation
The right content finds you
Posts and their metadata are classified into categories. From there the system builds an interest profile for each user based on genuine engagement, then routes new content to the people most likely to value it.
Scouts see the players and positions they follow. Players see content relevant to their own development. The feed sharpens with use.
Interest profile
Built from genuine engagement
Match highlight
U-17 striker
Training drill
Finishing
Scout report
Left wing
Advertising that understands intent
Ad targeting runs on sequence models RNNs, LSTMs, and Transformers trained on purchasing behaviour over time. Because these models learn from sequences rather than isolated events, they capture how a user's interests actually evolve instead of over-fitting to a single click.
For advertisers: higher conversion, because ads reach people whose behaviour signals real intent. For users: relevant offers instead of noise.
Behaviour over time, not a single click
Football intelligence
AI that reads the game like a referee
Our card prediction model assesses an incident and predicts whether it results in a yellow card or a red. It's football-native intelligence, the kind of judgement that generic AI platforms have no way to make, and it feeds match analysis, discipline insight, and richer player profiles.
Incident classification
Yellow card
Reckless challenge
Red card
Serious foul play
Feeds match analysis, discipline insight, and player profiles.
See the better play
Tactical analysis takes raw match footage and surfaces stronger options directly on the video. Players and coaches don't just review what happened; they see what a better decision looked like, drawn onto the play itself.
Coaching-level insight, generated from footage a player already has.
Safety first, by design
Content moderation was the first AI system we built, not the last. Screening media for violence and policy violations before it reaches a young audience is a precondition for everything else on the platform and it shapes how we approach every model that follows.
We publish claims we can stand behind. Where a system is in production, we say so. Where it isn't, we don't.