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World Rugby

Real-time Analytics

World Rugby wanted to make the Women’s Rugby World Cup 2025 more engaging by unlocking and activating complex match data in real time so broadcasters, commentators, and digital channels could give fans richer insights and better storytelling during matches.

1,521 insights that were used across 147 million viewing hours
32 were used on Instagram posts
36 appeared on BBC match broadcasts
439 were promoted via World Rugby Match Center

Reported impact

Business outcome

The platform helped World Rugby deliver a more engaging broadcast and digital fan experience with real-time AI-generated commentary insights during the Women’s Rugby World Cup 2025, and it was later extended to other rugby competitions and additional languages.

  • Customer Experience

Solution

World Rugby, Capgemini, Stats Perform, and AWS built TryZone IQ as a generative AI platform for live rugby insight generation. The implementation ingests historical and live Opta match data delivered in real time by Stats Perform, then routes that data into generative AI models hosted on Amazon Bedrock to produce short, match-ready narratives about player impact, team trends, and standout performances. TryZone IQ acts as the orchestration and delivery layer, packaging those model outputs for editorial use. Before distribution, analysts review and approve the generated insights to maintain quality and relevance. Approved insights are then pushed into the live broadcast production workflow for commentators and on-screen graphics, and also published to World Rugby’s online and in-app Match Center plus social channels. The source does not name a separate storage service, so storage is not attributed beyond the historical and live data inputs.

Data flow

Historical and live Opta match data is delivered in real time by Stats Perform into TryZone IQ, where generative AI models hosted on Amazon Bedrock create summaries of player impact, team trends, and standout performances. Analysts review and approve the outputs, which are then fed into live broadcast production, World Rugby’s Match Center, in-app digital experiences, and social media clips.

Solution architecture

3 components · 3 layers
  1. Ingest
    • Opta match data Historical and live rugby data source used to generate in-game insights.
  2. Compute
    • Amazon Bedrock Hosts the generative AI models that turn match data into bite-sized insights for commentators and fans.
  3. Orchestration
    • TryZone IQ Custom-built platform that orchestrates real-time insight generation and distributes approved outputs to broadcast, digital, and social channels.

Architecture clues

  • Deployed for the first time at the Women’s Rugby World Cup 2025
  • First use of generative AI in rugby
  • Generative AI models were hosted on Amazon Bedrock
  • Human review and approval step by analysts before publication
  • Later expanded to provide insights in French, Italian, Welsh, and English
  • Three-month development process

Evidence from the source

"Capgemini worked with Stats Perform, Amazon Web Services (AWS), and World Rugby to develop TryZone IQ, an award-winning Generative AI-driven platform that creates insights in real time for use in broadcasts and commentary"
"Of the 1,521 total insights generated, 439 were promoted via World Rugby Match Center, 36 appeared on BBC match broadcasts, and another 32 were used on Instagram posts."
"The outputs are reviewed and approved by analysts to ensure quality and relevance."
"The platform processes historical and live Opta match data delivered in real time by Stats Perform and leverages generative AI models hosted on Amazon Bedrock to create insights"
"Then, the insights are delivered through the live broadcast production workflow for use by commentators and appearing as on-screen broadcast graphics, as well live insight streams on digital platforms and clips on social media."
"TryZone IQ played a key role in what was the most successful and watched Women’s Rugby World Cup in history; generating 1,521 insights that were used across 147 million viewing hours"
Transparency Evidence & methodology 96/100 reference value · 97% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

01

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value96/100
  • Problem clarity20/20
    Measures whether the customer's operational problem is specific enough to compare.
  • Implementation depth25/25
    Rewards named components, data flow, integrations, and architecture detail.
  • Outcome specificity16/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact25/25
    3 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence97%
  • Source authority25/25
    The deployment is described by the adopting organization or a government source.
  • Claim traceability23/25
    11 of 12 key fields link to a named source.
  • Direct evidence20/20
    6 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency9/10
    2 source references document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity10/10
    Rewards source-backed components, data flow, quantified impact, and a specific outcome.
02

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

  1. World Rugby

    World Rugby customer story

    First-party
    https://www.capgemini.com/news/client-stories/with-ai-world-rugby-leaves-nothing-on-the-field/
    Source type
    Customer-published story
    Published
    Jul 6, 2026
    Supports
    • Customer
    • Business problem
    • Solution
    • Products
    • Solution components
    • Data flow
    • Integrations
    • technical area
    • use case category
    • Business outcome
    • outcome category
    • Metrics
    • Architecture
    • evidence quotes
    • Publication date
  2. LinkedIn

    World Rugby | LinkedIn

    Independent secondary
    https://www.linkedin.com/company/world-rugby/

    LinkedIn's Organization JSON-LD lists numberOfEmployees value 846 and sameAs "http://www.worldrugby.org".

    Source type
    Structured company profile
    Supports
    • Company size

Date evidence

  • Published on source page Jul 6, 2026 · Capgemini · First-party
    Open date source
Not separately sourced Industry, Region. Treat these normalized attributes as lower-confidence until a dedicated source is added.