Editorial · Updated 2026
Insights.
Field notes on AI in tennis operations. Match intelligence, coaching analytics, talent identification, club and tournament operations, and the regulatory frame around biometric data. Written for the people who decide.
Match Intelligence
3 articles
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Match Intelligence
Shot Pattern Recognition: Beyond Heatmaps
The heatmap is 2014 output. Sequence learning is what 2026 actually does. The shift changes the coaching question from where to what — at a price in data volume most operations do not yet pay.
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Match Intelligence
Opponent Scouting Reports: From Manual to Machine
The four-hour scouting PDF is still standard on Tour. A defensible pipeline can compress it to twenty minutes without losing tactical density — if the human stays in the right place.
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Match Intelligence
Computer Vision in Tennis: What It Actually Reads
Computer vision is sold as a tactical oracle. It is a measurement tool. This is a clear-eyed primer on what CV extracts from match video — and what it does not.
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Coaching Analytics
3 articles
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Coaching Analytics
Periodisation Planning When the Model Disagrees
The model says rest. The senior coach says push. The disagreement is the interesting part. This is how operations document, decide and audit when AI and human point opposite ways.
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Coaching Analytics
Biomechanics Flags From Match Video, Without Sensors
Pose estimation reads enough biomechanical signal from match video to flag asymmetries, fatigue and toss variance. The limits are real. Knowing where the wearable becomes necessary matters most.
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Coaching Analytics
Training Load Modelling for Junior Tennis Cohorts
Junior academies under-invest in load modelling. The assumption is that young bodies recover. The data argues otherwise. This is what credible junior load modelling actually requires.
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Talent Identification
2 articles
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Talent Identification
Junior Cohort Comparison Across Years: Why It's Hard
Comparing under-fourteens cohorts in 2024 against 2026 looks like a database query. It is a normalisation problem that has defeated most federations for two decades. This is the credible path.
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Talent Identification
Federation Talent Pipelines: The Data Layer Gap
National federations run scouting through regional coordinators. The reports exist. The comparable data layer does not. This is what the gap looks like, and how to close it.
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Operations
3 articles
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Operations
Sponsorship Audience Modelling for Tennis Properties
A tennis property with court bookings, a content channel and a CRM has a defensible audience hidden inside it. Most price sponsorship from rate-cards. Buyers pay for what you can prove.
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Operations
Tournament Operations: AI in Scheduling and Court Allocation
Constraint solving applied to tournament scheduling produces better order-of-play documents in less time. Where it works, where it does not, and what the operations director should ask the vendor.
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Operations
The Member Churn Signal Most Tennis Clubs Miss
The data needed to predict member churn is already in your court booking and billing systems. The signal is two simple ratios. Most clubs do not look because nobody has told them where.
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Want to apply one of these to your operation? Talk to us.
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