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Athlete Performance Data Integration Workbench

Unifies GPS load, video, tactical event, wellness, readiness, roster, and specialized training data to support rehab planning, drill design, goalkeeper analytics, draft operations, and custom performance modeling.

The Problem

“Athlete performance data integration and analysis across telemetry, video, tactical, roster, and wellness systems”

Organizations face these key challenges:

1

GPS, video, tactical, wellness, readiness, and roster data live in disconnected systems with inconsistent schemas

2

Player identity matching across providers is error-prone, especially during draft and roster changes

3

Physical load metrics lack immediate on-field context without synchronized video and event data

4

Tactical and physical performance are reviewed separately, limiting understanding of sustainable role demands

Impact When Solved

Reduce manual data reconciliation and video lookup time for analysts and performance staffImprove rehab planning by linking high-load or anomalous movement events directly to contextual videoEnable drill design based on verified tactical and physical stress patterns rather than isolated metricsPrevent draft-period roster errors through automated record reconciliation and master data synchronization

The Shift

Before AI~85% Manual

Human Does

  • •Export GPS, video, wellness, readiness, roster, and event data from separate platforms
  • •Match player identities, draft records, and timestamps manually across sources
  • •Review load spikes, rehab sessions, and drills by searching video and comparing spreadsheets
  • •Build one-off reports for coaches, medical staff, analysts, and front-office users

Automation

    With AI~75% Automated

    Human Does

    • •Approve roster changes, player identity exceptions, and master record updates
    • •Interpret integrated performance findings for rehab plans, drill design, and role decisions
    • •Review flagged anomalies or uncertain movement classifications before action

    AI Handles

    • •Unify incoming GPS, video, tactical, wellness, readiness, roster, and training data into athlete profiles
    • •Reconcile player identities and synchronize drafted-player records across changing feeds
    • •Link load events, tactical moments, and movement patterns to relevant video and session context
    • •Classify goalkeeper and role-specific movement events, detect anomalies, and surface cross-domain performance insights

    Operating Intelligence

    How Athlete Performance Data Integration Workbench runs once it is live

    AI surfaces what is hidden in the data.

    Humans do the substantive investigation.

    Closed cases sharpen future detection.

    Confidence84%
    ArchetypeDetect & Investigate
    Shape6-step funnel
    Human gates1
    Autonomy
    67%AI controls 4 of 6 steps

    Who is in control at each step

    Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.

    Loop shapefunnel

    Step 1

    Scan

    Step 2

    Detect

    Step 3

    Assemble Evidence

    Step 4

    Investigate

    Step 5

    Act

    Step 6

    Feedback

    AI lead

    Autonomous execution

    1AI
    2AI
    3AI
    5AI
    gate

    Human lead

    Approval, override, feedback

    4Human
    6↺ Loop
    AI-led step
    Human-controlled step
    Feedback loop
    TL;DR

    AI scans and assembles evidence autonomously. Humans do the substantive investigation. Closed cases improve future scanning.

    The Loop

    6 steps

    1 operating angles mapped

    Operational Depth

    Real-World Use Cases

    League scheduling and competition data integration into external operational systems

    Leagues and teams can move schedules, fixtures, and competition data from the platform into their own systems so operations data is available where staff already work.

    Operational data synchronization and workflow enablementavailable operational integration use case
    10.0

    Linking GPS load events to video for rehab and drill design

    Fulham connects player movement data to video clips, so staff can see the exact actions behind hard runs or accelerations and build rehab drills that match real match demands.

    Multimodal event linking across telemetry and videoactive integrated workflow using existing hudl products in elite football.
    10.0

    Goalkeeper-specific performance monitoring with dive analytics

    Special algorithms track goalkeeper actions like dives and recovery to standing, giving coaches numbers for a position that is usually hard to measure.

    Activity classification from wearable movement dataspecialized but deployed
    10.0

    Hudl event data integration for tactical + physical performance review in iP

    The platform combines what a player did in the game, like pressing or tackling, with how hard their body worked, like sprinting and fatigue, so coaches can plan smarter training.

    Multimodal performance intelligence and cross-domain correlation analysisdeployed integration workflow within kitman labs ip using hudl sportscode event data.
    10.0

    Automated drafted-player roster synchronization

    When a player gets drafted, the system quickly adds that player to the right NBA team roster and fills in missing player records if needed.

    record reconciliation and master data synchronizationoperational workflow clearly defined in the documentation.
    9.5

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