AdrenalineIP

Embodiments include utilizing artificial intelligence and/or machine learning to produce sports analytics based on historical score data for specific teams, players, events, or other relevant data. Machine learning can be applied to the historical data in order to improve the betting odds. Correlations between event outcomes and available parameters can be analyzed in advance and in real time by an odds module to give accurate and up-to-date odds.

A method, system, and apparatus for collecting, manipulating, transmitting, and interpreting data. In one embodiment, a plurality of sensors configured to capture real-time sensor data from a live event including a plurality of actions; one or more sport gaming platforms, and a user device, where the one or more sports gaming platforms are configured to: receive and store the captured sensor data, filter a historical sensor database on similar event data matching an ID for an upcoming action, wherein the ID identifies odds on upcoming plays, determine, based on artificial intelligence and/or machine learning and before occurrence of the upcoming action, that there is a high correlation between the captured sensor data and the similar event data, determine a probability of occurrence of the upcoming play associated with the wager ID, and update odds offered by the exchange system.

A method of sharing a wager on a live sporting event with another individual on a play by play wagering platform. Users can additionally invite other users to place the same wager or another wager on a different play. Upon accepting a wager invitation, the users additionally joining a chat conversation so as to communicate while placing wagers on the live sporting event.

A method of identifying wagers trends from a user's wagering history in order to alert the user of similar wagers that are available. The user interacts with a betting platform which displays all of the live plays available to be wagered upon, and the odds of those wagers. The user's interaction with the application may be recorded, along with their wagering data and a plurality of play characteristics. As the betting platform receives a new live play available to be wagered on, it may compare the characteristics of the new play to the user's history and may notify the user of the new play if it is highly correlated with their past wagering interactions with the platform.

A system for wagering on outcomes of a live sporting event. The system includes an artificial intelligence-based process which will notify users when wagers that would be of interest to them are available. These notifications could be used to drive users to wagers where there is an imbalance wagers in order to reduce risk for the offeror of the wager.

A method of informing a user of a sports betting application of his or her performance compared to the user's friends or other users, e.g., this user just fell behind his friend, or this user is doing the best out of his group of friends.

Methods and systems for determining and providing automatic flags for what is classified as a “significant” bet. When the user makes a significant bet, a software application automatically records the play and may also record the user's reaction. The user does not have to provide an indication to record these clips.

A system that allows a user to set threshold preferences for wager limits and the amount of time a wager is placed to allow the user to authenticate or identify themselves when the thresholds are exceeded to reconfirm that the user wishes to place a wager. The system compares the wagers placed by the user to thresholds inputted by the user. If the wager parameters exceed the inputted thresholds, the wagering network reconfirms the wager with the user by requesting a means of authentication to ensure that it is the user placing the wager and determining if the user wants to place the wager and that it was not placed in error.

The present disclosure provides a method of determining a user's long-term value to a wagering network and identifying new users similar to the users that provide long-term value to the wagering network. This method determines a user's long-term value and the user's engagement with a wagering network and places the users into cohorts. The method also provides finding correlations with the users' data and then correlating the data of new users and comparing the correlation coefficients of the new users with the older users to group the new users into the cohorts similar to the older users to predict their long-term value to the wagering network.

The present disclosure provides a system and method of using telemetry data to determine wager odds by receiving time-stamped position information captured by sensors, such as telemetry data, of one or more participants of one or both is the first set of participant(s) and/or the at least second set of participant(s) in the competition, and then using the time-stamped position information to determine a first action situation of the competition, and determining the probability and wager odds of a first future event occurring at the competition based on at least the first action situation and playing data associated with at least a subset of one or both of the first set of one or more participants and the at least second set of one or more participants and historical playing data.