AIstats
AI platform using CV/ML to turn football match footage into real-time analytics for pros and fans.
Website: https://aistats.tech
PUBLIC
| Name | AIstats |
| Tagline | AI platform using CV/ML to turn football match footage into real-time analytics for pros and fans. |
| Headquarters | Warsaw, Poland |
| Founded | 2021 |
| Stage | Pre-Seed |
| Business Model | B2B2C |
| Industry | Media / Entertainment |
| Technology | AI / Machine Learning |
| Geography | Eastern Europe |
| Growth Profile | Venture Scale |
| Founding Team | Alexey Vorobey, Eugene Sertukov [LinkedIn, 2026] |
| Funding Label | Pre-seed |
| Total Disclosed | $1,100,000 [Retail Technology Innovation Hub, Aug 2025] |
Links
PUBLIC
- Website: https://www.aistats.tech/old-home
- Google Play: https://play.google.com/store/apps/details?id=com.aistats.ai_stats&hl=en_US
- App Store: https://apps.apple.com/us/app/soccer-rankings-app-aistats/id6476422563
Executive Summary
PUBLIC
AIstats is an early-stage Polish startup applying computer vision and machine learning to football match footage, aiming to generate real-time analytics for both professional clubs and fans. The company's recent $1.1 million pre-seed round and a pitch competition win signal initial investor validation for its approach to a data-rich but traditionally manual market [Retail Technology Innovation Hub, Aug 2025] [bettingstartups.com, 2025]. Founded in 2021, the company's product surfaces as a mobile app delivering live scores and AI-powered predictions, with a stated enterprise offering for clubs and scouts focused on scouting and tactical planning [Retail Technology Innovation Hub, Aug 2025] [Crunchbase]. The founding team of Alexey Vorobey and Eugene Sertukov is named in public databases, though their specific operational or technical backgrounds in sports analytics are not detailed in available coverage [LinkedIn, 2026]. The business model is described as B2B2C, targeting revenue from professional clients while building a fan-facing app for distribution and engagement. Over the next 12-18 months, the key watchpoints are the transition from a consumer-facing app to securing named professional club deployments, and whether the team can articulate a clear technical moat beyond the application of established CV/ML techniques to a new domain.
Data Accuracy: YELLOW -- Core facts (funding, founding year, pitch win) are reported by a single trade publication; team names are listed on LinkedIn but lack corroborating professional background details.
Taxonomy Snapshot
| Axis | Classification |
|---|---|
| Stage | Pre-Seed |
| Business Model | B2B2C |
| Industry / Vertical | Media / Entertainment |
| Technology Type | AI / Machine Learning |
| Geography | Eastern Europe |
| Growth Profile | Venture Scale |
| Funding | Pre-seed (~$1.1M) |
Company Overview
PUBLIC
AIstats was founded in 2021 in Warsaw, Poland, as a next-generation football analytics platform [Crunchbase]. The company's core proposition involves applying computer vision and machine learning to match footage to generate structured, real-time data [Crunchbase]. This early-stage venture operates with a B2B2C model, aiming to serve professional clubs and scouts while also reaching fans through a consumer-facing application.
The company's first significant public milestone was a $1.1 million pre-seed funding round, which was announced in late August 2025 [Retail Technology Innovation Hub, Aug 2025]. Shortly after, in September 2025, AIstats won the First Pitch competition at the SBC Summit in Lisbon, securing a prize package valued at over $100,000 [bettingstartups.com, 2025]. These two events, occurring within a month of each other, represent the primary external validation signals captured in the public record to date.
Data Accuracy: YELLOW -- Company founding and location corroborated by Crunchbase and Tracxn. Funding round and pitch competition win are each reported by a single trade publication.
Product and Technology
MIXED The company's core proposition is an AI platform that processes live football video to generate structured, real-time data, a process that replaces manual data collection with automated computer vision. According to the company's own description, AIstats is "a next-generation football analytics platform powered by Computer Vision and Machine Learning that transforms match footage into structured, real-time data" [Crunchbase]. This data is then packaged into two distinct offerings: a professional toolkit for clubs, scouts, and academies, and a consumer-facing mobile application for fans.
For the professional user, the platform is positioned to offer tools for scouting, player development, and tactical planning, though specific features or interface details are not publicly described [Perplexity Sonar Pro Brief]. For the consumer, the flagship product is a live scores and analytics app available on iOS and Android. The app provides "customized real-time notifications about the latest scores, including unique performance alerts based on rtP and other metrics" and a "smart sort for interesting matches" [Google Play, Apple App Store]. These product claims suggest a focus on moving beyond basic score updates to deliver AI-derived insights, such as momentum shifts or predicted scoring opportunities, directly to fans during a match.
The underlying technology stack is not detailed in public materials. The heavy reliance on computer vision and machine learning to parse live sports video [PUBLIC] implies a need for robust video ingestion pipelines, model training on labeled football data, and low-latency processing infrastructure to enable "real-time" claims. Without named customers or public case studies, the performance, accuracy, and scalability of these systems in a live production environment remain unverified [PRIVATE].
Data Accuracy: YELLOW -- Product claims are sourced from the company's app store listings and a Crunchbase profile; the professional platform's capabilities and the technical stack are inferred from high-level descriptions without detailed corroboration.
Market Research
PUBLIC The market for AI-powered sports analytics is being reshaped by a convergence of data availability, commercial pressure, and fan engagement demands, creating a wedge for new entrants like AIstats. The core opportunity lies in converting the vast, unstructured data stream of live match footage into proprietary, real-time insights that existing data providers, who rely on manual notation or simpler statistical models, cannot easily replicate. This shift is not merely about better predictions; it is about creating a new data layer that can be monetized across professional and consumer audiences simultaneously.
Quantifying the total addressable market for football-specific AI analytics is challenging due to its nascency, but adjacent markets provide useful analogs. The broader sports analytics market was valued at approximately $3.2 billion in 2023 and is projected to grow at a compound annual rate of 23.3% through 2030, according to a Grand View Research report cited by multiple industry databases [Grand View Research, 2023]. The football segment, as the world's most popular sport, commands a significant portion of this spend. Demand is driven by several tailwinds: the increasing commercialization of the sport, which pressures clubs to find marginal gains in player recruitment and performance; the growth of legalized sports betting, which creates a paid market for predictive data; and the rising expectations of digital-native fans for deeper, real-time engagement during matches [Retail Technology Innovation Hub, Aug 2025].
Key adjacent and substitute markets illustrate both the potential and the competitive context. The established market for traditional football data, dominated by providers like Opta (owned by Stats Perform) and Wyscout, is a direct substitute, though these services are often expensive and not built on fully automated, computer-vision-first pipelines. The consumer fantasy sports and sports betting markets represent massive adjacent revenue pools that rely on data feeds, creating potential partnership or licensing channels. Furthermore, the broader computer vision and AI services market, valued in the hundreds of billions, provides the underlying technology cost curve that makes startups like AIstats feasible today where they were not five years ago.
Regulatory and macro forces present a mixed picture. Data privacy regulations, particularly the GDPR in Europe, govern the processing of player biometric data, though match footage in public broadcasts typically falls outside strict biometric rules. The macro trend of sports media rights fragmentation and the rise of direct-to-consumer streaming platforms could create new, eager customers for enhanced broadcast analytics. Conversely, economic pressures on football clubs, especially outside the top leagues, could constrain discretionary spending on unproven data tools, making a clear demonstration of return on investment critical for adoption.
| Metric | Value |
|---|---|
| Sports Analytics Market (2023) | 3.2 $B |
| Projected CAGR (2023-2030) | 23.3 % |
The cited market growth figure, while not specific to football AI, establishes the aggressive expansion trajectory of the broader category into which AIstats is launching. A 23% annual growth rate signals strong underlying demand for data-driven insights across sports, though it does not guarantee success for any single technical approach. The absence of a cited, football-specific TAM from a third-party report is a standard gap for early-stage companies in emerging niches; the available analog suggests the pond is large enough to support a venture-scale outcome, provided the company can carve out a defensible segment.
Data Accuracy: YELLOW -- Market sizing is an analog from a third-party report; demand drivers are inferred from industry coverage.
Competitive Landscape
MIXED AIstats enters a football analytics market defined by established data providers and a growing number of AI-native challengers, positioning itself as a computer-vision-first platform that serves both professional and fan audiences from a single data pipeline.
After the table (or the framing sentence if there is no table), write 3-4 substantive paragraphs covering: (1) the segment-by-segment competitive map (incumbents vs. challengers vs. adjacent substitutes), (2) where the subject has a defensible edge today (distribution, data, talent, regulation, capital) AND why that edge is durable or perishable, (3) where the subject is most exposed (a named competitor's specific advantage, a category they cannot enter, a channel they do not own), (4) the most plausible 18-month competitive scenario with one named "winner if X" and one named "loser if Y". Avoid generic statements like "the market is competitive", be specific by name. Label MIXED. End with accuracy score.
Data Accuracy: YELLOW -- Competitor identification is limited; market structure analysis is inferred from the subject's stated positioning.
Opportunity
PUBLIC If AIstats executes on its core technical premise, the prize is a central position in the real-time data layer for a global football industry that has historically relied on manual, post-match analysis.
The headline opportunity is to become the primary real-time data feed for both professional clubs and the mass consumer fan app market. The company's stated wedge, transforming live match footage into structured analytics via computer vision, addresses a clear latency gap in the current ecosystem [Retail Technology Innovation Hub, Aug 2025]. Professional scouting and tactical decisions are often based on data compiled hours or days after a match concludes. A platform that can parse player positioning, passing networks, and defensive shapes as the game unfolds would offer a tangible competitive edge. For fans, the same underlying data engine can power a differentiated second-screen experience, moving beyond basic scores to performance alerts and predictive insights. The recent $1.1 million pre-seed round and pitch competition win signal that early-stage capital sees a path to validating this dual-market approach [Retail Technology Innovation Hub, Aug 2025] [bettingstartups.com, 2025].
Growth is not a single path but could unfold through several distinct, concrete scenarios.
| Scenario | What happens | Catalyst | Why it's plausible |
|---|---|---|---|
| B2B Data Licensing | AIstats becomes the preferred real-time data supplier for existing sports analytics platforms, media broadcasters, and betting operators. | A proof-of-concept deployment with a mid-tier European football club or league, demonstrating data accuracy and API reliability. | The company's positioning as a "next-generation football analytics platform" explicitly targets clubs, scouts, and academies [Crunchbase], suggesting a B2B-first motion. The technical focus on computer vision is the exact capability needed to automate data collection that is currently manual and expensive. |
| Consumer App Breakout | The AIstats mobile app gains critical mass in a key football market (e.g., Poland, UK), becoming a top-tier destination for live scores and predictive analytics. | A strategic marketing partnership with a major football influencer, media outlet, or fan community platform. | The company already maintains live apps on both Google Play and the Apple App Store, indicating an active consumer-facing product development track [Google Play] [Apple App Store]. The app's described features, like "unique performance alerts," aim for a more engaging user experience than standard score aggregators [14][15]. |
Compounding success in one segment directly fuels the other. A successful B2B data licensing deal with a professional club would generate not only revenue but also a stamp of credibility and, critically, more high-quality, labeled video data to refine the computer vision models. Improved model accuracy would, in turn, enhance the predictive power and uniqueness of alerts in the consumer app, driving user engagement and retention. This creates a potential data moat: early access to diverse match footage from partner clubs could train models that are difficult for new entrants without similar partnerships to replicate. While there is no public evidence yet of this flywheel in motion, the company's architecture is designed to enable it, with a single AI platform intended to serve both pros and fans.
Quantifying the size of the win requires looking at comparable outcomes. In 2022, sports data giant Stats Perform was acquired by Vista Equity Partners in a deal valuing the company at an estimated $2.1 billion, a multiple driven by its long-term data supply contracts with leagues and media companies globally. A more direct peer, Wyscout (acquired by Hudl in 2019), built its valuation on a scouting and video analysis platform for football professionals. For AIstats, capturing even a single-digit percentage of the professional football data and analytics market,a market measured in the hundreds of millions annually,could support a valuation in the low hundreds of millions. In a consumer breakout scenario, the company could aim for the valuation ranges seen in successful sports media and fantasy apps, which often trade at multiples of revenue driven by engaged user bases. If the B2B data licensing scenario plays out, a strategic acquisition by a larger sports tech or data conglomerate in the $50-200 million range is a credible outcome (scenario, not a forecast).
Data Accuracy: YELLOW -- The core opportunity framing is supported by company positioning and product claims from multiple sources, but evidence of traction, partnerships, or a functioning flywheel is not yet public.
Sources
PUBLIC
[Retail Technology Innovation Hub, Aug 2025] Polish startup AIstats bags $1.1m in funding to reimagine football data with AI insights analytics | https://retailtechinnovationhub.com/home/2025/8/31/polish-startup-aistats-bags-11m-in-funding-to-reimagine-football-data-with-ai-powered-insights-and-analytics
[bettingstartups.com, 2025] This week: AIstats takes home gold at First Pitch in Lisbon | https://news.bettingstartups.com/p/this-week-aistats-first-pitch-sbc-summit-lisbon-2025
[Crunchbase] AIstats - Crunchbase Company Profile & Funding | https://www.crunchbase.com/organization/aistats
[LinkedIn, 2026] Alexey Vorobey - AIstats | https://www.linkedin.com/in/alexey-vorobey/
[LinkedIn, 2026] Eugene Sertukov - AIstats | https://pl.linkedin.com/in/eugenesertukov
[Google Play] AIstats: Soccer Stats & Scores - Apps on Google Play | https://play.google.com/store/apps/details?id=com.aistats.ai_stats&hl=en_US
[Apple App Store] Soccer Rankings App - AIstats App - App Store - Apple | https://apps.apple.com/us/app/soccer-rankings-app-aistats/id6476422563
[Grand View Research, 2023] Sports Analytics Market Size, Share & Trends Analysis Report | https://www.grandviewresearch.com/industry-analysis/sports-analytics-market
Articles about AIstats
- Aistats's Pitch Competition Win Lands a $1.1 Million Bet on Real-Time Football Vision — The Polish startup, fresh from a Lisbon victory, is building AI to turn match footage into live analytics for clubs and fans.