PLAYBOOK ATLASPlaybook Atlas

Sports

AI in sports: explore 30 applications.

Connect video, performance records and workload observations to clearly defined sporting decisions.

Explore match analysis, training review, scouting and performance reporting for coaches, analysts and support teams.

Plan your first AI move See the 30 applications

Where the 30 applications sit

Explore the domains
  1. 24Performance Management
  2. 7Fan Engagement and Experience
  3. 4Research and Development
  4. 2Strategic Planning and Operations

01Why AI now

Why sports is moving on AI, in three figures.

Each figure links to its source.

  1. Sports analytics market: $23.1B by 2033

    Grand View Research projects the global sports analytics market will grow from $5.7 billion in 2025 to $23.1 billion in 2033.

    Source: Grand View Research

  2. Sports fans using AI: 69%, up from 52%

    IBM's June 2026 survey of 20,589 sports fans across 12 countries found that AI use increased from 52% to 69% year over year.

    Source: IBM Newsroom

  3. Fans wanting AI sports insights: 56%

    In a 2025 survey of 20,864 sports fans across 12 countries, 56% wanted AI-powered insights and commentary for past, current and future sporting events.

    Source: IBM Newsroom

How to evaluate a first project

Define the sport, athlete group and measurement before drawing conclusions. Check event labels, sensor synchronization and uncertainty against a suitable reference. Evaluate coaching or scouting outputs separately from injury and return-to-play decisions, which require the relevant clinical assessment and authority.

02Capability map

Where sports puts AI to work, domain by domain.

Pick a domain to see its applications. Each one opens a full report.

Inside Performance Management

Applications in Performance Management

What the use cases ask AI to do

Share of the sports use cases, by the kind of work the AI does.

  1. Reasoning

    Analyzes, predicts and decides: scoring, forecasting, classifying.

    62%

  2. Generation

    Creates: text, images, code and other content.

    31%

  3. Perception

    Sees, hears and reads: documents, images, audio and video.

    6%

Under 1% each: optimization and agentic.

03Workflow ideas

Ways AI could change the work, in sports.

Atlas groups these applications by the changes they propose to a workflow. These preliminary classifications help you explore ideas; each application still needs a review of its sources and operating requirements.

Workflow categories in this catalog

Share of the 25 applications assigned a category.

How to evaluate an application

  1. Start with a bounded task

    Identify the inputs, the person responsible, and the decision or output the workflow must produce.

  2. Check the support for each method

    Look for source-backed details about the specific implementation, including its limits and human review.

  3. Measure the pilot

    Record the current baseline, agree on acceptance criteria, and test on representative cases before expanding.

Explore applications

04What gets built

The approaches sports uses most, and when to skip them.

Knowing when not to use one matters as much as knowing when to.

  1. 01 · 7 applications

    Generative AI

    Models that learn data distributions to generate new text, images, code, and media.

    Use it when

    • When you need to generate natural language, code, or media that would be expensive or slow for humans to produce manually.
    • When tasks involve ambiguity, open-ended questions, or creative exploration rather than strict right-or-wrong answers.
    • When you can ground the model on reliable internal or external data sources to improve factuality.

    Skip it when

    • When the task requires strict determinism, formal guarantees, or regulatory-grade traceability (e.g., certain financial calculations, safety-critical control systems) without a robust verification layer.
    • When you lack access to high-quality, authoritative data or subject-matter expertise to validate outputs in a high-risk domain.
    • When a simple rules engine, search, or template-based system can solve the problem more reliably and cheaply.
    Generative AI, in depth

  2. 02 · 5 applications

    Time-Series

    Model and forecast time-ordered data to capture trends, seasonality, and temporal dependencies.

    Use it when

    • You need to forecast future values of a metric that is naturally ordered in time (e.g., demand, load, traffic, sensor readings).
    • The target variable exhibits temporal dependencies such as trend, seasonality, or autocorrelation that can be exploited.
    • Decisions depend on how a process evolves over time rather than on static snapshots (e.g., capacity planning, staffing, pricing).

    Skip it when

    • The data has no meaningful temporal order or the order is arbitrary (e.g., shuffled survey responses without timestamps).
    • You only need to predict static attributes or cross-sectional outcomes at a single point in time (e.g., churn at signup) without temporal context.
    • Historical data is extremely sparse, short, or irregular, making it impossible to learn reliable temporal patterns.
    Time-Series, in depth

  3. 03 · 4 applications

    Workflow Automation

    Use AI inside orchestrated workflows to automate multi-step business processes.

    Use it when

    • When you have repetitive, rule-heavy workflows that still require human judgment or document understanding.
    • When the process spans multiple systems (ERP, CRM, ticketing, email) and manual coordination is slow or error-prone.
    • When large volumes of semi-structured or unstructured data (emails, PDFs, forms) must be processed consistently.

    Skip it when

    • When the process is highly creative, exploratory, or non-repeatable, with no stable sequence of steps.
    • When decisions are extremely high-stakes (e.g., life-critical medical decisions, major legal judgments) and regulations require full human control.
    • When you lack reliable access to the necessary systems or data sources to complete the workflow end-to-end.
    Workflow Automation, in depth

05The applications

30 sports applications, each with a full report.

The widest first, by the number of use cases each covers. Every report shows what changed, how it works, who has done it and what can go wrong.

  1. Athlete Performance Modeling EngineThis AI solution covers AI systems that capture and analyze athlete, team, and game data to model performance, optimize training loads, and support tactical and operational decisions. By combining video, spatio-temporal tracking, biomechanics, and contract/operations data, these tools give coaches, analysts, and sports executives actionable insights. The result is improved on-field performance, smarter roster and contract decisions, and more efficient use of coaching and training resources.Silo → Int52 use cases
  2. Joint Load Biomechanics MonitorAI Sports Joint Load Intelligence uses wearables, vision-based pose estimation, and biomechanical models to estimate joint loads and fatigue in real time across training and competition. By predicting injury risk, quantifying movement quality, and personalizing workload, it helps teams extend athlete availability, optimize performance, and reduce the medical and salary costs associated with preventable injuries.React → Pred20 use cases
  3. Sports Strategy Simulation EngineAI Sports Strategy Engine ingests live and historical performance, tracking, and video data to recommend optimal tactics, lineups, and in‑game decisions for teams and coaches. By transforming complex multimodal sports data into real-time, actionable insights, it sharpens competitive strategy, improves player utilization, and increases win probability while maximizing the return on talent and analytics investments.Batch → RT19 use cases
  4. Athlete Fatigue Risk MonitorAI Athlete Fatigue Intelligence continuously analyzes multimodal data—from wearables, video, and match stats—to detect fatigue, quantify load on specific joints or muscle groups, and predict injury and overtraining risk in real time. By turning raw performance signals into explainable fatigue and exertion insights, it helps coaches optimize training loads, refine recruitment decisions, and extend athletes’ peak performance windows while reducing costly injuries.React → Pred10 use cases
  5. Sports Performance Operations Analytics HubThis application area focuses on turning the vast volumes of data generated across sports—on‑field performance, training, medical, scouting, fan behavior, ticketing, and venue operations—into actionable insights for both athletic and business decision‑making. It spans player evaluation, tactics, and injury risk management on the performance side, as well as fan engagement, pricing, sponsorship, and operational optimization on the commercial side. The core objective is to replace subjective, slow, and fragmented judgment with evidence‑based decisions that update in near real time. AI is used to ingest and unify heterogeneous data (video, tracking, wearables, biometrics, CRM, sales), detect patterns and anomalies, forecast outcomes, and recommend optimal actions. This enables coaches to refine tactics and training loads, performance staff to manage health and longevity, front offices to improve roster and contract decisions, and business teams to personalize fan experiences and maximize revenue per fan. As data volumes and competitive pressure rise, this integrated performance-and-operations analytics layer is becoming a strategic capability for sports organizations and their technology partners.Time-Series Anomaly Detection9 use cases
  6. Player Availability Insights PlatformA 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.Expert → Platform8 use cases
All 30 applications, A to Z

Work with us

The catalog shows what is possible. A sprint decides what you should fund.

Reading every report still leaves the hardest question open: which move is worth funding first, here, given your constraints. That is the sprint: two weeks, fixed scope, and a candid answer either way.

Book a 30-minute callHow the sprint works

Two weeks Fixed scope A candid fit-or-no-fit answer

  1. 01

    Three ranked opportunities

    A decision-ready shortlist scored against value, feasibility, evidence, risk, and time to proof.

  2. 02

    One pilot-ready workflow

    A bounded operating design with actors, handoffs, data needs, controls, and success measures.

  3. 03

    A defensible 90-day plan

    Build-versus-buy guidance, ROI assumptions, risk treatment, sequencing, and executive decisions.

06Rules & standards

Rules and standards to check, with their scope and sources.

Selected US and EU references for these workflows. Applicability depends on jurisdiction, organization, data and intended use. The planning notes are Atlas editorial guidance; they are not official implementation-time estimates or an exhaustive list of obligations.

  1. GDPR · personal data and automated decisions

    Law or regulation

    European Union / EEA · processing within GDPR scope

    Personal-data processing needs an applicable lawful basis and safeguards. Article 9 adds conditions for special-category data; Article 22 addresses certain solely automated decisions with legal or similarly significant effects. Consent is not the only lawful basis.

    EUR-Lex: GDPR, Articles 3, 6, 9, 22 and 35

    Source checked

    Project planning note

    For in-scope athlete health or biometric data, establish the relevant Article 9 condition as well as the general lawful basis.

  2. FTC Rule on Unfair or Deceptive Fees

    Law or regulation

    United States · live-event tickets and short-term lodging

    The rule requires covered sellers to disclose the total price including mandatory fees upfront and prohibits misleading fee representations. It is not a general ban on dynamic pricing.

    FTC: fees rule frequently asked questions

    Source checked

    Project planning note

    For live-event ticketing, test the displayed total and mandatory fees across the complete purchase flow.

Your next step

Find your first move in sports.

Ask the workspace which move fits your company. Add your size, systems and constraints, and it works from these 30 applications to a plan your team can act on.

Plan your first AI move

Rather talk it through? Book a 30-minute call