Intelligence for Better Football Decisions

Be-Healthy.AI turns football data into actionable intelligence, helping organisations prevent injuries, identify the right players and make better decisions earlier.

From injury-risk early warnings to AI-powered scouting intelligence.

Explore Our Solutions Talk to Be-Healthy

Professional players: 20,000+Professional players
European leagues monitored: 6European leagues monitored
Historical data points: MillionsHistorical data points

Two of Football's Hardest Decisions

Who needs attention now? And who should we recruit next?

Prevent

Live

See Injury Risk Early

Identify elevated injury risk, monitor how it changes and help your team prioritise preventive action.

Explore Injury Prevention →

Recruit

In development

Find the Right Player

When a position becomes vacant, identify and rank potential replacements based on projected fit for the role.

Explore Scouting →

Football Decisions Happen Before the Outcome Is Known

Many non-contact injuries develop before they become visible. Recruitment decisions are made before a player joins the team.

Be-Healthy.AI uses football data and AI to give decision-makers an earlier, broader view of the factors that matter.

Data
Signal
Decision
Outcome

Injury Risk Prevention

See Injury Risk Early. Act Sooner.

Be-Healthy.AI analyses player and football-context data every day to identify elevated injury-risk patterns and help performance and medical teams decide where attention is most needed.

Professional players: 20K+Professional players
European leagues monitored: 6European leagues monitored
Historical data points: MillionsHistorical data points
Observed injury frequency in the Critical class: 5.6×observed injury frequency2025/26 Premier League live-monitoring sample

Recurring risk escalation before multiple injury events. Illustrative of the pattern reported in our 2025/26 Premier League monitoring; not a real player's data.

The value is not certainty. It is earlier attention.

We Analyse the Football Context You Don't See

Player profile

Age
Height
Nationality
Position
Dominant foot

Career & club

Matches
Career trajectory
Transfers
Tenure
Exposure

Injury history

Injury type
Severity
Recurrence
Contact / non-contact
Recovery patterns

Player Workload

Match load
Selection & Utilisation
Fatigue proxies
Rest days
Dynamics

We Bring the External Context.
You Add What Only You Can Measure.

Be-Healthy.AI works with publicly available football data, giving organisations an independent external layer of intelligence. Clubs can enrich that picture with their own training, wellness, medical and performance information when available.

Be-Healthy

Public football data

Your organisation

Internal data

Result

Better decisions

Not Every Injury Can Be Seen Coming

Soft-tissue injuries often develop through accumulated damage, creating precursor signals we can model. Collision injuries result from sudden external events with no reliable precursor for the system to detect, so we do not attempt to forecast them. Being clear about that boundary is part of what makes our predictions credible.

Anticipated

Patterns the system is built to surface early.

Muscle injuries
Tendon injuries
Non-contact ligament injuries

Not anticipated

Events with no meaningful precursor.

Contact ligament injuries
Traumatic fractures
Trauma from collisions

Noise

Excluded rather than modelled.

Non-injuries
Unknown injuries
Other

New · Scouting & Recruitment

In development

From Vacancy to Shortlist.

A player leaves. A position opens. The scouting team needs answers. Be-Healthy.AI can analyse the available player universe and identify potential replacements, ranked by projected fit for the role.

How the Shortlist Is Built

Step	What happens
01	A player leaves, a position opens
02	You define the role
03	Be-Healthy analyses the candidate universe
04	Candidates are ranked by projected fit
05	You receive a shortlist of ten

Illustrative process. This capability is in development.

Replacement Shortlist

Rank	Player	Fit score
01	Example Player A	94
02	Example Player B	91
03	Example Player C	89
04	Example Player D	87
05	Example Player E	85

Illustrative example. Player scores shown are not live recommendations.

Who Should Replace Your Next Player?

Talk to us about how Be-Healthy.AI can support your scouting workflow.

Explore Scouting

Intelligence Without the Friction

Public data

Start without requiring proprietary club datasets.

No hardware

No wearables required to begin.

No integrations

Deploy without disrupting existing systems.

Independent layer

Add another perspective to existing decision-making.

Continuous intelligence

Monitor changing risk and player profiles.

Competitive context

Benchmark players and squads against the wider football ecosystem.

What We've Built. What We've Proven.

Case study

A Risk Signal Before the Injury

Availability is not the same as stability. How continuous monitoring surfaced an unstable return-to-play trajectory before a second injury followed.

Access the full case study →

Case study

Reprioritising a Ligue 1 Squad in Eleven Days

A completed proof of value with Olympique Lyonnais, run on public data alone, showing a squad ranking that reordered itself over eleven days.

Read the case study →

Live evidence

Live Premier League Monitoring Shows Meaningful Separation of Injury Exposure

Out-of-sample monitoring across the 2025/26 Premier League season shows recurring pre-injury escalation and clear separation between risk bands.

Read the research →

Live evidence

Out-of-Sample Performance of the Premier League Muscular Injury Risk Model

An out-of-sample performance report on the Premier League muscular injury risk model, evaluated on a fully blind 2025/26 test season using public data only.

Read the research →

Live evidence

Integrating Injury Early Signals into Daily Workflows

How a club puts daily injury early signals to work inside its existing medical and performance meetings, without integrations and without ceding judgement.

Read the research →