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IBM Media and Entertainment Global

UFC

Real-time Analytics

UFC needed a faster way to turn large volumes of performance data, historical matchups and fighter statistics into live, broadcast-ready storytelling because manual analytics workflows could not keep pace with real-time events or rising fan expectations.

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210+ countries airing UFC content
3x increase in insight volume
40+ live events every year
660+ of the world's best fighters

Reported impact

Business outcome

UFC increased insight output, reduced manual analytics effort and created a more scalable fan-engagement platform that turns data into a competitive storytelling advantage during live events.

  • Customer Experience
  • Productivity Improvement
  • Scalability

Solution

UFC partnered with IBM to build the UFC Insights Engine, an AI-powered analytics platform designed to turn raw fight data into live insight for broadcast and digital channels. The platform combines current event data, historical matchups and fighter statistics into a natural-language-accessible analysis environment so editors can query a large fight-data library without manually wrangling datasets. Instead of relying on labor-intensive preparation before and during events, analysts can request advanced analysis and unique storylines on demand, which shortens the path from raw information to fan-facing content. The same architecture also expands output capacity because the system can surface insights quickly enough to support both live event storytelling and broader digital distribution. In effect, UFC uses the engine as a serving layer between its underlying fight-data estate and the analysts, editors and fan experiences that depend on real-time narrative context.

Data flow

Performance data, historical matchups and fighter statistics are aggregated into the UFC Insights Engine, where editors and analysts use natural-language interaction to generate broadcast and digital insights that can be delivered to fans in real time.

Solution architecture

1 components · 1 layer
  1. Serving
    • UFC Insights Engine Generates AI-powered fight insights on demand and lets editors query historical UFC data in natural language.

Architecture clues

  • Editors mine a large library of fight data using natural language.
  • The platform is intended to support both live broadcasts and digital content distribution.
  • The system was designed specifically to replace manual insight-generation workflows.

Evidence from the source

"3x increase in insight volume"
"700M fans following the action"
"The organization partnered with IBM to build the UFC Insights Engine-an AI powered platform"
"accelerates the path from data to insight"
"lets UFC editors mine a massive library of fight data using natural language"
Transparency Evidence & methodology 90/100 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 value90/100
  • 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 specificity20/20
    Measures whether the reported benefit is concrete rather than a generic claim.
  • Quantified impact15/25
    1 metric 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
    5 direct source quotes retained.
  • Date provenance10/10
    The publication date comes from the source page or publisher.
  • Source transparency8/10
    1 source reference 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. IBM

    UFC customer story

    First-party
    https://www.ibm.com/case-studies/ufc-insights-engine
    Source type
    Vendor-published customer story
    Published
    Sep 14, 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

Date evidence

Not separately sourced Industry, Region, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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