Sports Personalization, within Player Value Insights, is Sportradar's AI recommendation engine and the player-facing surfaces it powers – tailoring the sports, events, markets, and bets each player sees, from their first visit through live in-play. A book with thousands of matches and deep prop trees is hard to move through, and players who can't find their bet fall back on a low-margin single or leave; personalization puts the selections each player is most likely to want in front of them, lifting discovery, engagement, and ticket value. It runs on your ticket data through Insight Tech, Sportradar's AI models hub – the family of models that run on your ticket data and power capabilities across trading, player value, and player protection.
77bn+ recommendations and predictions delivered in 2025
163M+ players served in 2025
59M+ sports events covered in 2025
The cornerstone: "bets you may like," surfaced from deep-learning models rather than fixed rules or segmentation. It recommends each player's most relevant next selection – pre-match, live, and even pre-login – across sports, leagues, events, and markets, through surfaces like the Highlights Carousel.
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A live read on what's gaining momentum, tailored to the player: the bets being backed right now, with the option to show how many others have backed each, prioritized to the markets and bet types that player follows.
Discover more Discovery by interest rather than static menus: related sports, leagues, teams, and athletes based on what a player follows, their favorites across the whole offering, and a personalized calendar of the day's key events – all adapting to seasonality.
Discover more Search that forgives typos and ranks on the player's own profile from the first character: "bay" returns Bayern Munich for a European soccer bettor, Green Bay for an NFL one. Players can also search an athlete and get their upcoming games with the most relevant markets ready to bet.
Discover more Surfaces the player props each bettor is most likely to want – on the homepage and match pages – from the athletes and markets they usually back, lifting a high-hold market into view without cluttering the layout across hundreds of micro-markets.
Discover more Ready-to-play combination bets – personalized, popular, or trending – so players don't assemble multi-leg slips by hand on mobile. Includes same-player Bet Builders and a single area housing player props and same-game and multi-game parlays.
Discover more A gamified, swipe-based interface for building accumulators, giving casual players a familiar and fast way to compile a slip and find selections tailored to them.
Discover more Triggered by what's happening on the pitch: when a goal, red card, or other key event lands, the models surface the most relevant live market to each player and deliver it into the live UI, app push, or SMS – cutting the time between the moment and the bet.
Discover more It integrates through a REST API, front-end widgets, and your existing CRM and messaging tools, across site, app, and messaging; handles the cold-start problem with relevant results from a player’s first visit; and ships with analytics and tuning to boost or filter specific sports and bets.
Does it work before a player has any betting history?
Yes. It handles the cold-start problem, giving relevant recommendations from a player’s first visit – falling back to trending and most-popular models for new or unauthenticated traffic – then sharpening as the player bets.
Across the journey: homepage and navigation, search, the betslip, player-prop areas, and live betting – and into app push, SMS, and email through your existing CRM and messaging tools. It integrates via REST API and front-end widgets.
Yes. In-play suggestions are triggered by live match events – a goal, a red card – surfacing the most relevant live market to each player in the moment and delivering it into your live UI, push, or SMS.
Yes. The models can be tuned – boosting, filtering, or grouping specific sports and bets – so recommendations reflect your commercial strategy, and built-in analytics show how they’re performing.
