Pre-Built Bet Recommendation

The Pre-Built endpoint delivers AI-powered, personalised pre-built combos to provide a fast and frictionless user experience. This enables users to quickly place bets, thereby increasing the overall bet volume for operators. Recommendations can be requested for general popular combos or for a specific user by providing a user ID.

Best Practice

• Highlight pre-built bet combos on key touchpoints: Home page, Sport page, League page & Event Page.

• Offer personalized or popular recommendations:

  • Logged-in users: Pass the user_id in the request to receive personalized pre-built bet recommendations.

  • Guest users: Pass user_id=0 in the request to receive the most popular pre-built bet recommendations.

• Types of pre-built recommendations

  • Currently, recommendations are available per event.

  • Future releases will support more flexible requests (by sport, tournament, or specific market).

Try out now on our Demo Page

Supported Sports & Markets

We support all Sports for both Pre-match and Live events.

Check out this document to find the markets we support for Pre-Built Recommendation: Supported Markets List

Product Access & Data Availability

• To access this feature, you need to activate the Pre-Built package per sport. Please get in touch with your sales representative for more information.

• After the package is activated, we will set up your database, which usually takes 3–5 days. Once complete, you will receive personalized recommendations based on your users’ preferences. During this setup period, you can still access the endpoint and continue integration, but the data returned will not yet reflect your exact ticket data.

• The prebuilt recommendation would be available when the match is available in Custom Bet.

API Endpoint

Get Pre-Built Bet Recommendations

get

Returns pre-built bet recommendations for a specific event.

Authorizations

key

x-access-tokenstringRequired

Query parameters

event_urnstringRequired

Unique event identifier.

Example: sr:match:12345

countinteger · min: 1 · max: 20Optional

Number of recommendations to return (1–20).

Default: 1Example: 5

lengthinteger · min: 2 · max: 10Optional

Number of selections in each bet builder (2–10).

Default: 2Example: 2

userstringOptional

The user to get recommended bet builder for. If 0, defaults to most popular combos.

Example: 23456

Header parameters

sub_bookmaker_idstringRequired

Sub bookmaker ID found in the MTS console.

Example: 12345

Responses

200

Successful response with pre-built bet recommendations.

application/json

requested_recommendationsintegerOptionalExample: 4

generated_atstring · date-timeOptionalExample: 2025-08-28T03:46:23+00:00

400

Invalid request

application/json

401

Unauthorized. Token is missing or invalid.

403

Forbidden. Access to Custom Bet not allowed.

404

No data for the event (match id). Invalid event.

409

Custom Bet API currently unavailable or betting not allowed.

429

Too many requests. Rate limit reached.

500

Internal Server Error - VAIX. Retry or contact support.

get

/v2custombet/prebuilt

HTTPcURLJavaScriptPython

GET /v2custombet/prebuilt?event_urn=sr%3Amatch%3A12345 HTTP/1.1
Host: api.betradar.com
x-access-token: YOUR_API_KEY
sub_bookmaker_id: 12345
Accept: */*

{
  "event": [
    {
      "id": "sr:match:62602726",
      "provided_recommendation": 3,
      "source": "text",
      "recommendations": [
        {
          "odds": 1.6908642659096753,
          "probability": 0.5419945158026643,
          "selection": [
            {
              "market_id": "63",
              "outcome_id": "9",
              "specifiers": null
            }
          ]
        }
      ]
    }
  ],
  "requested_recommendations": 4,
  "generated_at": "2025-08-28T03:46:23+00:00"
}

Response Explanation

Parameter	Type	Description	Sample
pre_built_bets	Object	Root element containing all pre-built bet recommendations.	—
requested_recommendations	Integer	Number of recommendations requested in the API call. If not set, we will return 0.	5
event	Object	Event object containing recommended combos for a specific events.	—
event.id	String	Unique event identifier for the recommendations.	sr:match:56328351
event.provided_recommendation	Integer	Number of recommendations returned for the event.	5
recommendations	Object	A recommended pre-built combo with odds, probability, and selections.	—
recommendations.odds	Number	Odds value for the recommended pre-built combo.	4.927841099580573
recommendations.probability	Number	Fair probability of the recommended pre-built combo.	0.16083858971602788
selection	Object	A selection within the recommended combo.	—
selection.market_id	Integer	Market identifier.	219
selection.outcome_id	String	Outcome identifier	4 or pre:playerprops:56328351:1153254:9
selection.specifiers	String	Additional specifiers for player props or special markets.	variant=pre:playerprops:56328351:1153254

PAPI Rate limits:

We have a base rate limit of 20 requests per second, as the PAPI should only be used on cashout edge cases. If you require a higher limit, please get in touch with our implementations team

FAQs

Questions	Answers
Can I personalize recommendations by user?	Yes. Pass a user value to generate combos based on historical behavior. Use user=0 for most popular bets, which is not personalized for a specific user.
What happens if the event has no available markets?	You’ll receive a 400 response with a message explaining that the event lacks sufficient markets for a valid recommendation.
Can I request for recommendations without providing an event_urn?	No, you need to select an event for recommendation. In the future, we will enable you to request recommendation without an event id, meaning that the API will pick the most relevant event based on user or global data.
Is this endpoint available for all sports?	Yes, it supports all sports available in Custom Bet, both Pre-match and Live events. Check this page for the most up-to-date coverage.
Will odds always be returned?	Yes — each recommendation includes odds and fair probability in the same response. Note: the odds provided via the endpoint is using the Custom Bet Ladder you selected in CTRL. To get the harmonization odds, you would need to call the Custom Bet calculation API with the same selections.
What factor does the AI model uses to generate recommendation?	Our AI model generates recommendations primarily based on the ticket data you share with us, ensuring that suggestions are aligned with your users’ actual betting behavior.