Sports Analytics Market Size and Share

Sports Analytics Market Analysis by Mordor Intelligence
The sports analytics market size stood at USD 5.28 billion in 2026 and is forecast to reach USD 17.88 billion by 2031, corresponding to a 27.63% CAGR over the period. Momentum is coming from three structural shifts: leagues now treat live performance data as a monetizable media asset, betting operators pay premiums for official feeds that settle wagers in milliseconds, and cloud platforms have replaced proprietary servers for 72.33% of deployments in 2025. Services are expanding faster than software because clubs need integration, data governance, and model-tuning expertise to stitch sensor, video, and fan data into coherent pipelines. North America’s early adoption of Internet-of-Things (IoT) sensors and legalized sports wagering supplies scale, yet Asia Pacific’s cricket-led franchise model is advancing even faster. Vendor competition is intensifying as hardware firms acquire software specialists to offer end-to-end stacks, as illustrated by Sony’s 2024 acquisition of KinaTrax and 2025 acquisition of STATSports.
Key Report Takeaways
- By component, software platforms captured 64.89% revenue in 2025, while services are expanding at a 28.11% CAGR through 2031.
- By sport, football led with 39.78% revenue share in 2025, whereas rugby is projected to post the quickest 29.23% CAGR through 2031.
- By deployment, cloud models accounted for 72.33% of the sports analytics market share in 2025 and are increasing at a 28.06% CAGR toward 2031.
- By end user, sports teams and clubs accounted for 43.83% of revenue in 2025, while sports betting operators are expected to grow at a 28.61% CAGR between 2026 and 2031.
- By geography, North America accounted for 42.76% of the revenue share in 2025, yet Asia Pacific is anticipated to register the fastest 28.69% CAGR over the forecast period.
Note: Market size and forecast figures in this report are generated using Mordor Intelligence’s proprietary estimation framework, updated with the latest available data and insights as of January 2026.
Global Sports Analytics Market Trends and Insights
Drivers Impact Analysis
| Driver | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Real-time tracking enabled by IoT sensors in North American professional leagues | +5.2% | North America with spillover to Europe and Asia Pacific | Medium term (2-4 years) |
| Centralised data-warehousing mandates from European football clubs for transfer valuation | +4.8% | Europe, South America, Middle East | Long term (≥4 years) |
| Sports betting data partnerships post-legalization in the United States | +6.1% | North America, expanding to Asia Pacific and Europe | Short term (≤2 years) |
| Franchise-driven analytics adoption in Indian and Australian cricket leagues | +3.9% | Asia Pacific, Middle East and Africa | Medium term (2-4 years) |
| AI-powered injury prediction models reducing player downtime | +4.3% | Global | Medium term (2-4 years) |
| Integration of esports performance data with traditional sports analytics | +2.9% | Global, concentrated in Asia Pacific and North America | Long term (≥4 years) |
| Source: Mordor Intelligence | |||
Real-Time Tracking Enabled by IoT Sensors in North American Professional Leagues
Zebra RFID chips in NFL shoulder pads and optical cameras in NBA arenas generate millions of coordinates each game, compressing the analysis loop from hours to seconds. Microsoft’s Copilot-enabled sideline application, rolled out league-wide in August 2025, converts those streams into fourth-down probabilities and fatigue alerts that coaches can act on instantly.[1]Microsoft, “NFL expands partnership to bring AI to the sideline,” microsoft.com Edge gateways and low-latency cloud zones are therefore replacing fixed data centers because teams cannot tolerate 5-10 second round-trip delays. The model is already diffusing to the English Premier League, which signed its own five-year AI partnership with Microsoft in July 2025.
Centralised Data-Warehousing Mandates from European Football Clubs for Transfer Valuation
Premier League and continental clubs increasingly treat multi-season performance archives as capital assets that justify eight-figure transfer fees. Oracle’s Match Insights platform, first launched in 2021, collates video, positional, and biometric records so recruitment teams can benchmark prospects against historical comparables. Academy programs follow suit: Kitman Labs now underpins longitudinal tracking across every Premier League youth setup, giving sellers data-backed leverage in negotiations. As a result, buyers must counter with equally rich datasets or risk overpaying.
Sports Betting Data Partnerships Post-Legalization in the United States
Tri-exclusive NBA agreements with Sportradar and Genius Sports, MLB’s equity-linked 2032 renewal with Sportradar, and the NCAA’s January 2025 data deal formalize a closed-loop market in which leagues profit from every in-game wager.[2]Sportradar, “MLB and Sportradar extend partnership through 2032,” sportradar.com Operators receive authenticated feeds that update sub-second odds on mobile apps, while broadcasters gain predictive graphics that boost engagement. The short-term revenue jolt is U.S.-centric, but regulators in Europe and the Asia Pacific are now drafting copycat rules that prize “official” data.
Franchise-Driven Analytics Adoption in Indian and Australian Cricket Leagues
Hawk-Eye ball-tracking, Catapult GPS vests, and proprietary auction databases have turned Indian Premier League franchises into data laboratories. Player-level fatigue curves and pitch-condition models help owners maximize returns within tight roster budgets. The template is travelling: Big Bash League clubs apply the same stack, and Saudi Arabia’s Vision 2030 program is funding analytics pilots in domestic leagues. This pull from Asia Pacific explains why regional growth is set to eclipse North America by the early 2030s.
Restraints Impact Analysis
| Restraint | (~) % Impact on CAGR Forecast | Geographic Relevance | Impact Timeline |
|---|---|---|---|
| Limited technology budgets of tier-2 clubs in South America and Africa | -3.7% | South America and Africa with pockets in Asia Pacific | Long term (≥4 years) |
| GDPR and CCPA constraints on biometric data collection | -4.2% | Europe and North America with global compliance spillover | Medium term (2-4 years) |
| Data ownership disputes between leagues and betting operators | -2.8% | North America and Europe | Short term (≤2 years) |
| Lack of standardised performance metrics across women’s sports | -1.9% | Global | Long term (≥4 years) |
| Source: Mordor Intelligence | |||
Limited Technology Budgets of Tier-2 Clubs in South America and Africa
Many second-division football organizations operate on annual budgets under USD 10 million and must choose salaries over data pipelines. Patchy fiber backhaul further hampers live uploads, forcing coaches to rely on manual tagging rather than automated sensor feeds. The gap risks locking in a two-tier global talent market where data-rich clubs monetize undervalued prospects, while cash-strapped peers fall behind.
GDPR and CCPA Constraints on Biometric Data Collection
Wearable outputs are Article 9 “special-category” data in the European Union, demanding explicit athlete consent and strict purpose limitation.[3]European Commission, “General Data Protection Regulation (GDPR) text,” europa.eu California’s CCPA offers similar opt-out rights, and recent NOYB complaints have already triggered league policy reviews. Vendors now incorporate on-device encryption and federated learning architectures so algorithms can train without exporting raw biometrics, but compliance overhead slows rollouts and inflates the cost of ownership.
Segment Analysis
By Sport: Rugby’s Smart Ball Accelerates Adoption
Football generated 39.78% revenue in 2025, yet rugby is expanding fastest at a 29.23% CAGR through 2031 as Sportable’s sensor-embedded Gilbert ball delivers 20 positional updates per second for officiating and broadcast overlays. This data-rich object verifies lineouts and forward passes in real time, satisfying both referees and broadcasters. Cricket retains the second-largest slice, propelled by Hawk-Eye dominance in India and Australia, while basketball’s spatial-tracking partnerships fortify its analytics baseline.
Rugby’s momentum demonstrates that sports confronting officiating ambiguity adopt embedded sensors sooner than those with established replay systems. Successful trials at the 2023 Under-20 World Championship convinced Six Nations organizers to roll out smart balls through 2029, guaranteeing a steady uptick in hardware and software demand. The sports analytics market, therefore, benefits when technology solves officiating pain points and enriches fan storytelling.

Note: Segment shares of all individual segments available upon report purchase
By Component: Services Growth Outpaces Software
Software licenses still accounted for 64.89% of value in 2025, but integration, data quality, and model-training services are expanding at a 28.11% CAGR. Deloitte’s Converge for Sports bundles a fan data lake, loyalty functions, and real-time dashboards into a single managed service, underscoring why clubs prefer outcome-based contracts over toolkits. Consulting arms also mediate between proprietary wearables and public-cloud APIs, ensuring privacy controls and single-sign-on function across the stack.
The premium on services reflects rising architectural complexity. Modern deployments connect optical cameras, RFID chips, ticketing logs, and betting feeds inside a cloud warehouse. Without integration partners, clubs struggle to harmonize schemas or deploy machine-learning models safely. Vendors that pair product licenses with advisory programs have a cross-sell edge, and private equity investors reward those with steady services annuities.
By Deployment: Cloud Architecture Gains Momentum
Cloud deployments accounted for 72.33% of expenditure in 2025 and are advancing at a 28.06% CAGR, driven by compute-heavy workloads such as win-probability simulations that refresh every second. Oracle Cloud’s ability to run 100,000 match simulations per Premier League fixture validates its scale advantage over on-premises GPU clusters. Amazon Web Services provides a similar backbone for Six Nations Rugby match graphics, underscoring the broadcast dependency on elastic resources.
Pure on-premise remains viable for federations with data-sovereignty rules, but hybrid topologies now dominate new tenders. Sensitive biometrics stay behind the firewall, while aggregate metrics and fan-facing content move to the cloud. The switch is also encouraged by the rise of generative AI engines, which teams can tap on demand rather than funding their own GPU inventories.

By End User: Betting Operators Accelerate Adoption
Sports teams and clubs spent the most in 2025, yet betting operators are scaling fastest at a 28.61% CAGR as they embed scouting tools directly into league infrastructure. Sportradar’s equity-linked renewal with Major League Baseball exemplifies vertical integration: the vendor now supplies analytics to both clubs and sportsbooks, guaranteeing exclusive feed rights. Genius Sports applies the same logic to English football under its Football DataCo extension.
This shift toward multi-sided data platforms means the same telemetry underpins roster decisions, fan engagement, and micro-bets. As operators finance technology build-outs in exchange for rights exclusivity, they indirectly subsidize clubs and leagues, accelerating overall analytics penetration. Individual-athlete subscriptions, although niche, indicate a future in which players monetize their own biometrics in parallel.
Geography Analysis
North America controlled 42.76% of revenue in 2025, aided by the NFL’s league-wide IoT stack and widespread legal wagering that values sub-second data feeds. Major League Baseball’s 2032 renewal with Sportradar, including an equity component, illustrates how long-term data contracts anchor cash flows for both rights holders and vendors. Mature broadband infrastructure, large media rights, and a culture of quantitative decision-making sustain spending momentum.
Europe ranked second, propelled by unified football data strategies and Oracle-powered broadcast overlays. Growth remains healthy but sits beneath global averages because GDPR introduces consent hurdles for biometric capture. Nevertheless, the July 2025 Premier League–Microsoft pact shows clubs will invest heavily once compliance workflows are standardized. The Middle East acts as an extension market: Saudi Arabia channels Vision 2030 capital into analytics pilots across cricket and football, while the United Arab Emirates recruits startups to its free zones.
Asia Pacific is advancing fastest at a 28.69% CAGR through 2031, led by cricket’s franchise economics and a booming esports sector that shares data infrastructure. The Indian Premier League forces every club to maintain Hawk-Eye and Catapult systems, locking in recurrent software upgrades each season. China, South Korea, and Japan fuse traditional sports data with esports telemetry to build hybrid dashboards that coaches and shout-casters both rely on. By the early 2030s, cumulative spend is on track to match, then surpass, North America.
South America and Africa remain double-digit growth regions despite smaller bases. Budget limitations among tier-2 clubs slow adoption, but elite sides in São Paulo, Buenos Aires, and Johannesburg are already deploying wearables and cloud analytics on par with European counterparts. Infrastructure investments tied to 2030 World Cup bids and regional broadcasting deals are expected to gradually narrow the gap.

Competitive Landscape
The sports analytics market is moderately fragmented. Enterprise software giants such as Microsoft, Oracle, and SAP sell horizontal cloud and database layers, while specialists like Stats Perform, Catapult, Sportradar, and Genius Sports provide sport-specific capture and modeling tools. Startups, including Zone7, Kitman Labs, and Orreco, address niche use cases such as injury prediction and athlete wellness, frequently partnering with cloud hyperscalers for back-end scale.
Consolidation is picking up. Sony purchased KinaTrax in October 2024 and STATSports in October 2025, marrying optical tracking with on-body sensors into a single telemetry pipeline. Hudl took a different tack, buying StatsBomb in 2024 for football event data and Balltime in 2025 for volleyball video, signaling a sport-by-sport roll-up. Teamworks’ September 2024 acquisition of Zelus Analytics integrates roster-optimization algorithms into its operations suite, underscoring cross-functional expansion.
Strategic white space lies in privacy-preserving data architectures and cross-sport standardization. Vendors that can encrypt on-device, federate learning, and still monetize aggregated insights will satisfy regulators while preserving revenue. Equally, platforms that normalise metrics across football, basketball, and rugby enable scouts to evaluate multi-sport prospects, which is an advantage as clubs diversify their talent pipelines. Competitive differentiation is therefore shifting from raw data volume to model accuracy and regulatory compliance.
Sports Analytics Industry Leaders
IBM Corporation
SAP SE
SAS Institute Inc.
Oracle Corporation
Microsoft Corporation
- *Disclaimer: Major Players sorted in no particular order

Recent Industry Developments
- December 2025: Orreco integrated its athlete-optimization platform with Sportradar’s NBA feeds, unlocking personalised injury-risk dashboards tied to live league benchmarks.
- October 2025: Sony acquired STATSports Group, combining GPS wearables with Hawk-Eye optical tracking and KinaTrax biomechanics to offer an end-to-end performance stack.
- August 2025: Microsoft expanded its NFL deal to deploy Copilot-driven sideline analytics, giving coaches real-time call recommendations based on live sensor streams.
- July 2025: Microsoft signed a five-year AI and cloud partnership with the Premier League covering live analytics, fan engagement, and broadcast graphics.
Research Methodology Framework and Report Scope
Market Definitions and Key Coverage
Our study defines the global sports analytics market as all software platforms and associated services that ingest structured or unstructured data from wearable sensors, optical-tracking cameras, ticketing systems, and fan-engagement channels to generate real-time or predictive insights for on-field strategy and off-field commercialization. According to Mordor Intelligence, hardware sold without an embedded analytics layer is not counted within revenue.
Scope exclusion: standalone ticketing or stadium Wi-Fi solutions that provide no analytical output are omitted.
Segmentation Overview
- By Sport
- Football
- Cricket
- Basketball
- Hockey
- American Football
- Baseball
- Rugby
- Other Sports
- By Component
- Software
- Services
- By Deployment
- On-Premise
- Cloud
- By End User
- Sports Teams/Clubs
- Leagues and Federations
- Individual Athletes
- Sports Betting Operators
- Other End Users
- By Geography
- North America
- United States
- Canada
- Mexico
- Europe
- Germany
- United Kingdom
- France
- Russia
- Rest of Europe
- Asia-Pacific
- China
- Japan
- India
- South Korea
- Australia
- Rest of Asia-Pacific
- Middle East and Africa
- Middle East
- Saudi Arabia
- United Arab Emirates
- Rest of Middle East
- Africa
- South Africa
- Egypt
- Rest of Africa
- Middle East
- South America
- Brazil
- Argentina
- Rest of South America
- North America
Detailed Research Methodology and Data Validation
Primary Research
Mordor analysts interviewed performance directors at professional teams, data architects at solution vendors, and betting operator analysts across North America, Europe, and Asia-Pacific. These discussions validated software pricing bands, typical seats per license ratios, and emerging use cases (AI-assisted injury risk flags), filling gaps that desk research alone cannot bridge.
Desk Research
We began by collating publicly available datasets from bodies such as FIFA, World Rugby, the National Basketball Association, and the International Cricket Council, which publish match volumes, athlete counts, and broadcast reach. Macroeconomic indicators from the World Bank and IMF helped us normalize team budgets across currencies, while patent filings accessed through Questel signaled upcoming computer vision innovations. Company 10-Ks, investor decks, and Factiva news feeds then revealed average software contract values and cloud migration rates for clubs and leagues. These secondary sources, though illustrative here, form only a fraction of the repositories our analysts routinely mine for baseline evidence.
A second pass drew on trade associations; for example, the Sports & Fitness Industry Association's annual participation census and WSTS sensor shipments; to benchmark addressable device pools feeding analytics platforms. The list above is not exhaustive; dozens of similar channels were reviewed for cross-checks and clarification.
Market-Sizing & Forecasting
A calibrated top-down model starts with the global spend of professional and semi-professional teams, rebuilt through league counts and average analytics spend per squad, which are then adjusted for fan engagement platform outlays and betting data subscriptions. Supplier roll-ups of sampled average selling price multiplied by unit volumes provide a selective bottom-up lens for sanity checks. Key variables include 1) teams adopting optical tracking systems, 2) cloud share of analytics deployments, 3) average software subscription growth, 4) regional sports media rights inflation, and 5) active wearable sensors per athlete. We forecast forward with a multivariate regression where team technology budgets, media rights revenue, and cloud price curves explain over 85% of historical variance. Scenario analysis captures outlier seasons such as pandemic disruptions.
Gap pockets; for instance, missing ASPs in minor leagues; are bridged using validated ratios from adjacent tiers before final triangulation.
Data Validation & Update Cycle
Outputs undergo variance checks against external spend surveys, peer growth signals, and anomaly flags generated by our in-house scripts. Senior reviewers sign off after reconciling divergences. The dataset refreshes annually, and interim events (major collective bargaining deals, regulatory shifts on sports betting) trigger ad hoc revisions.
Why Mordor's Sports Analytics Baseline Scores High on Reliability
Published figures often differ because studies vary in market scope, refresh cadence, and currency treatment. We openly state exclusions and re-benchmark each assumption every year, which reduces hidden inflation or omission.
Key gap drivers include some publishers bundling generic sports technology hardware, others applying five-year-old exchange rates, or projecting using single-variable growth curves that ignore media rights volatility. Mordor's model, by contrast, blends recent contract data with multi-factor forecasting and an annual refresh.
Benchmark comparison
| Market Size | Anonymized source | Primary gap driver |
|---|---|---|
| USD 4.14 B | Mordor Intelligence | - |
| USD 5.79 B | Global Consultancy A | Includes broader sports tech platforms and uses constant 2022 USD |
| USD 5.68 B | Industry Publisher B | Relies mainly on supplier shipments, limited fan engagement revenues captured |
| USD 2.29 B | Regional Consultancy C | Narrow sample of North American leagues and a conservative cloud adoption curve |
In summary, the balanced blend of validated inputs, dual-angle modeling, and timely updates enables Mordor Intelligence to deliver a dependable reference point that decision-makers can replicate, audit, and trust.
Key Questions Answered in the Report
How large is the sports analytics market in 2026?
It reached USD 5.28 billion in 2026 and is projected to grow to USD 17.88 billion by 2031 at a 27.63% CAGR.
Which sport is expanding fastest in analytics adoption?
Rugby leads with a forecast 29.23% CAGR, powered by Sportable’s smart-ball technology and broadcast demand for verified officiating data.
Why are cloud deployments dominating new projects?
Real-time workloads and AI model training demand elastic GPU resources, making cloud architectures more cost-effective than on-premise clusters.
What factors are driving betting operators to invest in analytics?
Exclusive data rights, legalized wagering in 36 U.S. states, and the need for sub-second odds calculations push operators toward integrated analytics stacks.
How do privacy regulations affect biometric data collection?
GDPR and CCPA designate biometrics as sensitive data, requiring explicit athlete consent and forcing vendors to adopt encryption and federated-learning methods.
Which region is expected to overtake North America by the early 2030s?
Asia Pacific, fueled by cricket franchises and esports-analytics convergence, is on track to surpass North America’s spending early in the next decade.



