SYSTEMS AND METHODS FOR IDENTIFYING REAL-TIME NETWORK DATA STRUCTURE ASSOCIATIONS USING LANGUAGE MODELS

1 . A system, comprising:

one or more processors coupled to non-transitory memory, the one or more processors configured to:

maintain a plurality of wager opportunities corresponding to a plurality of live events, each of the plurality of wager opportunities identifying at least one of a plurality of teams or a plurality of participants of one or more live events;

maintain a dataset identifying one or more participant attributes of the plurality of participants and one or more team attributes of the plurality of teams;

receive, from a client device, a prompt comprising a request for a wager recommendation, the request identifying a requested attribute of a participant of the plurality of participants or a team of the plurality of teams;

generate, using a language model, the prompt, and at least a portion of the dataset, an output message identifying at least one wager opportunity of the plurality of wager opportunities selected based on the requested attribute; and

provide the output message to the client device in response to the request.

2 . The system of claim 1 , wherein the one or more team attributes comprise one or more of a ranking of each of the plurality of teams, a performance of a corresponding team of the plurality of teams in one or more live events, or a type of sport in which each of the plurality of teams participate.

3 . The system of claim 1 , wherein the one or more participant attributes comprise one or more of a ranking of each of the plurality of participants or subsets thereof, one or more performance metrics of each of the plurality of participants in one or more live events, or one or more associations with the plurality of teams.

4 . The system of claim 1 , wherein the one or more processors are further configured to:

determine that the request comprises an attribute request for wager opportunities corresponding to one or more top ranking players; and

select a subset of the plurality of wager opportunities that identify one or more participants of the plurality of participants that satisfy the attribute request.

5 . The system of claim 4 , wherein the one or more processors are further configured to:

generate an input context for the language model to include data of the subset of wager opportunities; and

generate the output message by providing the input context to the language model.

6 . The system of claim 1 , wherein the one or more processors are further configured to:

generate the output message to include a plurality of candidate wager opportunities selected from the plurality of wager opportunities, each candidate wager opportunity selected based on a similarity between the candidate wager opportunity and the at least one requested attribute.

7 . The system of claim 6 , wherein the one or more processors are further configured to:

receive, from the client device, a second prompt identifying a second requested attribute; and

generate, using the language model and the second prompt, a second output message comprising a first wager opportunity of the plurality of candidate wager opportunities, the first wager opportunity selected based on the second requested attribute.

8 . The system of claim 1 , wherein the dataset further comprises one or more historical participant attributes of one or more historical participants or one or more historical team attributes of one or more historical teams.

9 . The system of claim 8 , wherein the one or more processors are further configured to:

receive, from a client device, a second prompt comprising a second request for a wager recommendation, the second request identifying a historical attribute of the plurality of historical participants that relates to one or more of the plurality of participants; and

generate, using the language model, the second prompt, and data of the plurality of wager opportunities, an output message identifying at least one second wager opportunity of the plurality of wager opportunities selected based on the historical attribute.

10 . The system of claim 1 , wherein the client device is associated with a player profile, and wherein the one or more processors are further configured to:

generate the output message further based on the player profile.

11 . A method, comprising:

maintaining, by one or more processors coupled to non-transitory memory, a plurality of wager opportunities corresponding to a plurality of live events, each of the plurality of wager opportunities identifying at least one of a plurality of teams or a plurality of participants of one or more live events;

maintaining, by the one or more processors, a dataset identifying one or more participant attributes of the plurality of participants and one or more team attributes of the plurality of teams;

receiving, by the one or more processors, from a client device, a prompt comprising a request for a wager recommendation, the request identifying a requested attribute of a participant of the plurality of participants or a team of the plurality of teams;

generating, by the one or more processors, using a language model, the prompt, and at least a portion of the dataset, an output message identifying at least one wager opportunity of the plurality of wager opportunities selected based on the requested attribute; and

providing, by the one or more processors, the output message to the client device in response to the request.

12 . The method of claim 11 , wherein the one or more team attributes comprise one or more of a ranking of each of the plurality of teams, a performance of a corresponding team of the plurality of teams in one or more live events, or a type of sport in which each of the plurality of teams participate.

13 . The method of claim 11 , wherein the one or more participant attributes comprise one or more of a ranking of each of the plurality of participants or subsets thereof, one or more performance metrics of each of the plurality of participants in one or more live events, or one or more associations with the plurality of teams.

14 . The method of claim 11 , further comprising:

determining, by the one or more processors, that the request comprises an attribute request for wager opportunities corresponding to one or more top ranking players; and

selecting, by the one or more processors, a subset of the plurality of wager opportunities that identify one or more participants of the plurality of participants that satisfy the attribute request.

15 . The method of claim 14 , further comprising:

generating, by the one or more processors, an input context for the language model to include data of the subset of wager opportunities; and

generating, by the one or more processors, the output message by providing the input context to the language model.

16 . The method of claim 11 , further comprising:

generating, by the one or more processors, the output message to include a plurality of candidate wager opportunities selected from the plurality of wager opportunities, each candidate wager opportunity selected based on a similarity between the candidate wager opportunity and the at least one requested attribute.

17 . The method of claim 16 , wherein the one or more processors are further configured to:

receiving, by the one or more processor, from the client device, a second prompt identifying a second requested attribute; and

generating, by the one or more processors, using the language model and the second prompt, a second output message comprising a first wager opportunity of the plurality of candidate wager opportunities, the first wager opportunity selected based on the second requested attribute.

18 . The method of claim 11 , wherein the dataset further comprises one or more historical participant attributes of one or more historical participants or one or more historical team attributes of one or more historical teams.

19 . The method of claim 8 , further comprising:

receiving, by the one or more processor, from a client device, a second prompt comprising a second request for a wager recommendation, the second request identifying a historical attribute of the plurality of historical participants that relates to one or more of the plurality of participants; and

generating, by the one or more processors, using the language model, the second prompt, and data of the plurality of wager opportunities, an output message identifying at least one second wager opportunity of the plurality of wager opportunities selected based on the historical attribute.

20 . The method of claim 11 , wherein the client device is associated with a player profile, and further comprising:

generating, by the one or more processors, the output message further based on the player profile.