Sportradar Group (SRAD) Fair Value & Analysis
Technology · US · Market cap $4.3B
Analysis
Sportradar Group (SRAD) currently trades at $14.70, while our model-based Fair Value estimate is $11.07 — implying the stock looks roughly 24.7% overvalued today. We read business quality at 95/100 (high quality), in the Technology sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Sportradar Group AG, together with its subsidiaries, provides sports data services for the sports betting and media industries in Switzerland, the United States, North America, Africa, Malta, the Asia Pacific, the Middle East, Europe, Latin America, and the Caribbean. The company offers betting technology and solutions, including betting and gaming content; real-time sports data points; pre-match and live odds services; streaming and betting engagement services; iGaming, which includes virtual soccer, horse and dog racing, basketball, tennis, baseball, and cricket; managed betting and trading services; and sports betting and gaming platform. It also provides sports content, technology, and services that include marketing services; sports media services comprising data, content and solutions for broadcasters, publishers, rights-holders, and technology companies; integrity services, including monitoring, intelligence, education, consultancy, rights protection, and regulatory solutions…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.