Sports Content Management

Part of the worlds-biggest-software-project initiative.

A modular, AI-assisted platform that unifies live sports data, editorial content production, and fan engagement for mid-market sports organisations.

Sports organisations -- leagues, federations, clubs, and media rights holders -- juggle live data feeds, editorial workflows, and fan-facing digital experiences across disconnected systems. Sports Content Management bridges these three workstreams into a single platform with a shared data model, giving smaller organisations access to capabilities previously locked behind enterprise-tier pricing.

Why Sports Content Management?

Enterprise tools price out the mid-market. Stats Perform and Genius Sports target tier-1 rights holders and major broadcasters. Second- and third-tier clubs, national federations, and niche sports leagues lack affordable alternatives that combine data, content, and engagement in one platform.
No purpose-built open-source option exists. Drupal with the Sports League module is the closest open-source contender, but it requires extensive custom development, has no live data ingestion, and lacks mobile optimisation out of the box.
Editorial and statistics remain siloed. Most solutions force teams to maintain separate systems for live data and content creation, causing duplicated data entry, inconsistent statistics across channels, and delayed publication.
Fan engagement is bolted on, not integrated. Gamification tools like LiveLike and STATSCORE PointsInPlay operate as standalone overlays with no editorial awareness or shared data backbone, limiting contextual personalisation.
Broadcast rights enforcement is an afterthought. No examined solution offers configurable, per-asset geo-embargo rules with geo-IP detection as a core feature -- a critical gap for organisations operating across multiple broadcast territories.

Key Features

Live Data Backbone

Real-time ingestion of scores, play-by-play, lineups, and statistics from configurable data providers (Opta, SportsRadar, SportsDataIO)
Normalisation to a common internal schema that accommodates structural differences across sports
WebSocket / SSE delivery for sub-second latency to editorial tools and fan-facing apps
Historical statistics database queryable at player, team, and competition levels

Editorial CMS

Sports-aware content editor with automatic tagging by player, team, tournament, and match
Live data widgets that auto-populate within articles and match reports
Publication scheduling with multi-channel distribution (web, mobile app, social, partner embeds)
Role-based access control for editors, data admins, and publishers

Fan Engagement

Prediction games, polls, quizzes, and leaderboards driven by live match context
Personalisation engine surfacing content based on supported team and past behaviour
Event-triggered push and in-app notifications (goals, red cards, kick-off, full-time) with fan-controlled subscription preferences

Rights and Distribution

Per-asset broadcast rights and embargo rules with geo-IP enforcement at the content delivery layer
Multi-channel publishing from a single content entry to web, mobile, social, and partner embeds
Multi-language support for auto-generated content

Analytics

Audience engagement metrics (page views, session duration, notification open rates, game participation) correlated with match events
Editorial performance tracking across content types and distribution channels

AI-Native Advantage

AI capabilities address the core cost barrier that keeps mid-market organisations dependent on manual workflows. The platform uses language models to generate match summaries, previews, and post-match recaps from structured statistics data -- delivering editorial automation that Stats Perform charges enterprise rates for. Beyond content generation, AI powers semantic content tagging (detecting narrative themes like injury drama, record-breaking moments, and rivalries), notification timing optimisation based on historical engagement patterns, and personalised content recommendations through collaborative filtering. These capabilities allow a three-person editorial team to produce output that previously required dedicated data analysts and a larger writing staff.

Tech Stack & Deployment

Architecture: Headless, composable design with RESTful and GraphQL APIs, allowing organisations to use their own front-end frameworks (React, Vue, static sites)
Real-time delivery: WebSocket and server-sent events for live data; edge caching and auto-scaling infrastructure to handle match-day traffic spikes
Mobile-first: The 2026 Stats Perform survey projects owned apps and social video will overtake websites as primary fan channels by 2030; the platform prioritises mobile-native experiences
Deployment: Self-hosted, cloud, or hybrid; designed for organisations without dedicated DevOps teams
Data providers: Configurable adapters for major sports data APIs (not vendor-locked to a single provider)

Market Context

The global sports media rights market exceeds USD 50 billion annually, with digital fan engagement platforms growing as rights holders invest in owned-channel audience development to reduce dependence on social media algorithms. Enterprise vendors (Stats Perform, Genius Sports) serve the top tier effectively, but clubs and federations below the largest leagues are underserved and often lack even a consistent statistics database. A modular platform at an accessible price point addresses this gap directly (Stats Perform 2026 Survey, ClickUp Fan Engagement Report).

Project Status

This project is in the research and specification phase.
Contributions, feedback, and domain expertise are welcome.

Contributing

We welcome contributions from developers, domain experts, and potential users. See CONTRIBUTING.md for guidelines.

Important: All contributions must be your own original work or clearly attributed open-source material with a compatible licence. Copyright infringement and licence violations will not be tolerated and will result in immediate removal of the offending contribution. If you are unsure whether a piece of code, text, or other material is safe to contribute, open an issue and ask before submitting.

Licence

Licence to be determined. See discussion for context.