Sports Performance Insights

A comprehensive AI platform for optimizing athletic performance through data-driven insights and predictive analytics. This application leverages advanced machine learning techniques to enhance decision-making in training and strategy, leading to improved outcomes and competitive advantage.

The Problem

You have the data, but coaches still make high-stakes decisions on gut feel

Organizations face these key challenges:

1

Performance and injury signals are scattered across wearables, video, EHR/physio notes, and spreadsheets with no unified view

2

Training load decisions vary by coach/analyst; protocols aren’t consistent across teams or seasons

3

Insights arrive too late (post-game/post-week), so staff can’t adjust sessions or lineups in time

4

Analysts spend hours building reports instead of answering higher-value questions (readiness, matchup edges, fatigue)

Impact When Solved

Faster readiness and workload decisionsFewer preventable injuries / higher player availabilityScale insights across teams without adding analysts

The Shift

Before AI~85% Manual

Human Does

  • Manually merge GPS/wearable exports, wellness surveys, and training plans into spreadsheets
  • Review dashboards and highlight anomalies based on personal thresholds and experience
  • Create weekly reports and present recommendations to coaches/medical staff
  • Perform qualitative video review and scouting notes with limited quantification

Automation

  • Basic automation: scheduled exports, BI dashboards, static rules/threshold alerts (e.g., HR zones, distance, sprint counts)
  • Simple aggregations (rolling averages, ACWR) and visualization
With AI~75% Automated

Human Does

  • Define performance and health objectives (KPIs), constraints, and intervention policies (e.g., return-to-play rules)
  • Validate and contextualize AI recommendations (e.g., travel fatigue, minor knocks, coach priorities)
  • Make final calls on session plans, minutes restrictions, and tactical adjustments

AI Handles

  • Ingest and normalize multi-source athlete/game data; resolve identities and session alignment automatically
  • Predict readiness/fatigue and injury risk with individualized baselines; flag early-warning trends
  • Generate workload and recovery recommendations (session intensity, volume, rest) with confidence levels and rationale features
  • Run scenario simulations (e.g., expected performance under different lineups/minute allocations) and surface tactical tendencies from video/event data

Solution Spectrum

Four implementation paths from quick automation wins to enterprise-grade platforms. Choose based on your timeline, budget, and team capacity.

1

Quick Win

Daily Workload & Readiness Alertboard with Personalized Baselines

Typical Timeline:Days

Stand up a lightweight daily alertboard that merges GPS/workload and wellness scores, flags abnormal spikes vs individualized baselines, and pushes alerts to staff before training. This level prioritizes speed: minimal modeling, mostly configuration, and relies on existing vendor exports/APIs.

Architecture

Rendering architecture...

Key Challenges

  • Inconsistent athlete identifiers across vendors
  • Alert fatigue from poorly tuned thresholds
  • Missing context (travel, illness, coach intent) causing misinterpretation

Vendors at This Level

Catapult SportsSTATSports

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