Player Preferences-Based Recommendations

Key Features

Preferred Sports Feed: Utilise the FA_similarityFilter to analyse players’ historical preferences for specific sports and leagues through the BRE API. This filter dynamically prioritises and showcases the most relevant sports within the user interface based on past betting behaviour, making it easy for players to quickly locate their preferred sports options.
Preferred Tournaments Feed: The FA_similarityFilter enhances tournament engagement by drawing on players’ betting history to suggest high-interest competitions. This personalised tournament feed, accessible via the BRE API, allows players to view competitions they are most likely to bet on, helping to create a more targeted and engaging experience.
Preferred Teams and Athletes Feed: With team and player recommendations optimised by the FA_similarityFilter, the API fetches and ranks preferred teams and athletes based on historical betting data. By surfacing team or player IDs and recommendation rankings, players can easily follow their favourite teams and athletes, encouraging continued engagement.
Preferred Markets Feed: The FA_similarityFilter also powers market prioritisation by identifying key betting markets aligned with each player’s historical activity. Through the BRE API, a curated list of betting markets for each sport and competition is displayed, ensuring that players are presented with market options that closely match their previous preferences and maximise their likelihood to engage.

Practical Use Cases

Enhanced Navigation and Front-End Optimisation

Dynamic Front-End Components
Use insights from the Preferred Sports Feed to dynamically organise and prioritise sports categories on the front end. For example, for a player consistently betting on football, football-related content can be prioritised on the homepage, side menus, and event pages. This tailored experience increases the likelihood of interaction by ensuring preferred sports are easily accessible.
Team-Centric Navigation
The Preferred Teams and Athletes Feed enables team-centric navigation options. For a player with a strong preference for a specific basketball team, the front end can be optimised to feature team-specific content, such as upcoming games, team statistics, and exclusive promotions. This targeted approach enhances engagement by streamlining access to relevant team-based content.
Market-Focused Presentation
Utilise the Preferred Markets Feed to present market-focused sections within front-end components. If a player frequently engages with "Asian Handicap" markets, this market type can be prominently displayed on the homepage and prioritised in event pages. Such front-end optimisation simplifies navigation, ensuring players quickly locate their preferred markets.
Tailored Browsing Menus
Draw on insights from all feeds to dynamically structure side menus for personalised browsing. For players with varied interests, the side menu can be customised to offer quick access to their most engaged sports, tournaments, and teams. This tailored menu structure streamlines navigation, creating a more intuitive and efficient user experience.
Prominent Recommendations Section
Showcase curated recommendations from all feeds in a dedicated section on the homepage. This section can highlight upcoming matches, favoured teams, and recommended markets based on historical preferences, ensuring that players are immediately exposed to content that resonates with their interests, enhancing overall interaction.

Targeted Marketing Campaigns

Sport-Specific Promotions
Use insights from the Preferred Sports Feed to develop marketing campaigns focused on specific sports. For players with a strong preference for soccer, promotions offering exclusive bonuses, free bets, or loyalty rewards tied to upcoming soccer events can be launched. This targeted approach encourages engagement by aligning promotions with players’ sports interests.
Tournament-Centric Campaigns
Leverage the Preferred Tournaments Feed to design campaigns focused on key tournaments. For example, players who consistently engage with major tennis tournaments can be offered bonuses, odds boosts, or challenges centred around these events. This strategy boosts engagement by capturing attention with relevant, tournament-focused promotions.
Team-Driven Incentives
The Preferred Teams and Athletes Feed can help create marketing incentives based on players’ favourite teams. For players with a strong preference for a specific basketball team, campaigns offering bonuses, cashback, or exclusive promotions tied to that team’s upcoming games enhance engagement by aligning incentives with individual team interests.
Market-Specific Offers
Draw on insights from the Preferred Markets Feed to craft campaigns around players’ preferred betting markets. For example, players who regularly engage with "Over/Under" markets can receive targeted promotions featuring enhanced odds or cashback offers for these markets, ensuring that promotions align closely with their betting habits.
Personalised Email Campaigns
Combine insights from all feeds to deliver personalised email campaigns that highlight individual player preferences. These targeted emails can feature a mix of sport-specific promotions, tournament offers, team incentives, and market-specific bonuses, ensuring each player receives highly relevant content that resonates with their betting history.

How Player Preferences Work

Integration and Data Ingestion
The Bet Recommendation Engine integrates seamlessly with sportsbook operators, establishing a robust data ingestion system. This process collects and processes player behaviour, historical betting patterns, and transaction data, creating a rich dataset that powers personalised recommendations.

Data Analysis and Machine Learning
Once integrated, the engine applies advanced machine learning algorithms to analyse this extensive dataset. By evaluating each player’s historical preferences—such as sports, tournaments, teams, athletes, and markets—the engine transforms raw data into actionable insights, offering a nuanced view of each player's betting tendencies.

Timely and Relevant Recommendations
Focusing on active pre-match bets, the engine aligns recommendations with each player’s recent betting behaviour to ensure relevance and accuracy. Additionally, a 4-day horizon provides insights into upcoming events, allowing players to explore future betting opportunities and engage proactively with sports, teams, and markets over the next week.

API-Driven Operation
The Bet Recommendation Engine operates through robust API endpoints for smooth integration with operator systems. This API-centric approach simplifies the incorporation of player preference data, allowing operators to retrieve comprehensive historical data on preferred sports, tournaments, teams, athletes, and markets. The API integration enables efficient data flow, equipping operators with insights that drive personalised recommendations and enhance the player experience.

Dynamic Front-End Optimisation
Operators can dynamically optimise front-end components using insights from the Bet Recommendation Engine. By highlighting the most relevant and frequently chosen options—such as specific sports, tournaments, teams, and markets—the platform can adapt to each player's preferences, delivering a more tailored and engaging experience.

API Request and Response Structure

Request Structure

Endpoints:

Endpoint	Description	URL Pattern
Preferred Sports	Retrieves sport preferences	/api/preferred-sports
Preferred Tournaments	Retrieves tournament preferences	/api/preferred-tournaments
Preferred Teams/Athletes	Retrieves team/athlete preferences	/api/preferred-teams-athletes
Preferred Markets	Retrieves market preferences	/api/preferred-markets

HTTP Method: POST

Content-Type: application/json

Request Parameters

Parameter	Type	Required	Description
id_clients	string[] or string	Yes	Target client ID(s) for recommendations
top_n	integer	Yes	Number of recommendations to return per client

Request Example

{  
   "id_clients": [1011377, 1023029], 
    "top_n": 3 
}

Example Responses

Refer to the provided examples for each feed (Sports, Tournaments, Teams/Athletes, Markets) to understand the expected structure of the API response.

Preferred-Sports:

{ 
   "items": [ 
     { 
       "id_client": "1023029", 
       "sportPreferences": [ 
         {"sport": "Tennis", "rating": 0.28378427}, 
         {"sport": "Basketball", "rating": 0.100532964}, 
         {"sport": "Volleyball", "rating": 0.03186505} 
       ] 
     }, 
     // Additional players entries... 
   ] 
 }

Preferred-Tournaments:

{
"items": [
{
"id_client": "1011377",
"tournamentPreferences": [
{"tournament": "England Premier League", "rating": 55.417243559665984},
{"tournament": "Poland Ekstraklasa", "rating": 41.964815912794066},
{"tournament": "Spain LaLiga", "rating": 37.83963079882878}
]
},
// Additional players entries...
]
}

Preferred-Teams-Athletes:

{ 
   "items": [ 
     { 
       "id_client": "1011377", 
       "playerPreferences": [ 
         {"preference": "Austria", "SportName": "Football", "TournamentName": "International European Championship Qualification", "rating": 0.0033773411114522566}, 
         {"preference": "Greece", "SportName": "Football", "TournamentName": "International European Championship Qualification", "rating": 0.003223825606386245}, 
         {"preference": "Netherlands", "SportName": "Football", "TournamentName": "International European Championship Qualification", "rating": 0.003070310101320233} 
       ] 
     }, 
     // Additional players entries... 
   ] 
 }

Preferred-Markets:

{ 
   "items": [ 
     { 
       "id_client": "1011377", 
       "marketPreferences": [ 
         {"market": "DoubleChance", "tournament": "International European Championship Qualification", "rating": 0.05}, 
         {"market": "DoubleChance", "tournament": "USA NHL", "rating": 0.04870263912774858}, 
         {"market": "EuropeanHandicap-0:1", "tournament": "International European Championship Qualification", "rating": 0.009933774834437087} 
       ] 
     }, 
     // Additional players entries... 
   ] 
 }