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Capgemini Media and Entertainment global

Ryder Cup

Real-time Analytics

Ryder Cup needed a way to turn a huge volume of live and historical golf data into instant, understandable insights that could enrich broadcasts and fan experiences for a global audience.

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almost 170 million ways a single match play score card can be filled out
millions of viewers worldwide
processes up to 360 insights simultaneously
tracked over 4000 shots

Reported impact

Business outcome

Ryder Cup gained an operational AI layer that helps broadcasters and analysts explain a complex tournament in real time while making the event more engaging and understandable for millions of fans.

  • Customer Experience
  • Scalability

Solution

Ryder Cup worked with Capgemini to build Outcome IQ, an AI sports-analytics platform that converts live golf data into instant fan and broadcast insights. The system was first deployed for Ryder Cup 2023 in Rome, where it tracked more than 4,000 shots, and was then enhanced for the 2025 competition with agentic AI and richer real-time insight generation. Outcome IQ evaluates live shot-by-shot match data alongside historical player performance, course characteristics, and team-pairing context to calculate probabilities and "what if" scenarios as play unfolds. Those insights are surfaced simultaneously to broadcasters, analysts, and digital fan experiences, including push-style updates that make an intricate match-play format easier to follow. By packaging deep golf data into near-real-time commentary support and audience-friendly explanations, the platform turned a complex statistics problem into an operational content service for a global sports event.

Data flow

Live shot-by-shot data, historical player records, course characteristics, and pairing context are evaluated by Outcome IQ, which generates probabilities and explanatory insights that are delivered to broadcasters, analysts, and fan experiences in near real time.

Solution architecture

1 components · 1 layer
  1. Serving
    • Outcome IQ Interprets live and historical golf data to generate near-real-time probabilities and fan-facing match insights.

Architecture clues

  • Agentic AI was added for the 2025 competition
  • The platform was first deployed for Ryder Cup 2023 in Rome
  • The solution supports dynamic what-if scenarios for broadcast teams
  • The system evaluates every shot, hole, and match in real time

Evidence from the source

"First deployed for Ryder Cup 2023 in Rome, where the system tracked over 4000 shots"
"In a matter of weeks, our team developed Outcome IQ, an AI-powered sports analytics platform that interprets live shot-by-shot data."
"It now processes up to 360 insights simultaneously"
"With the subsequent addition of agentic AI, it now uses historical player performance and other factors to generate near-instant probabilities and insights."
Transparency Evidence & methodology 71/100 reference value · 89% confidence · 1 source

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 value71/100
  • 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 impact0/25
    0 metrics describe measurable impact.
  • Deployment scale10/10
    Rewards evidence of a live or scaled deployment and meaningful integration scope.
Evidence confidence89%
  • Source authority20/25
    The main evidence is an official vendor-published customer story.
  • Claim traceability21/25
    10 of 12 key fields link to a named source.
  • Direct evidence20/20
    4 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency10/10
    1 source reference document publisher, URL, authority, retrieval, and supported fields.
  • Implementation specificity8/10
    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. Capgemini

    Keeping AI on the ball - Capgemini

    First-party
    https://www.capgemini.com/news/client-stories/keeping-ai-on-the-ball/
    Source type
    Vendor-published customer story
    Published
    Oct 27, 2025
    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

Date evidence

  • Published on source page Oct 27, 2025 · Capgemini · First-party
    Open date source
Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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