A method, comprising: receiving, by a computing system , game control data and sensor data from a client machine , wherein the game control data and the sensor data are associated with a user account that is logged into a video game service , wherein the game control data is to be processed by a video game for controlling an aspect of the video game, and wherein at least one of the game control data or the sensor data is received as encrypted data; determining, by the computing system, private key data associated with a private key that was used to encrypt the encrypted data, the private key data comprising at least one of: a length of time that the private key has been associated with the user account; a number of times the private key has been used with, or used to login to, the user account; or a number of times the private key has been switched between different user accounts; determining, by a computing system, a score associated with the user account by: providing the sensor data and the private key data as input to a trained machine learning model ; and generating the score as output from the trained machine learning model, the score indicative of a probability of the game control data having been generated by a handheld device associated with the client machine; assigning, based at least in part on the score, the user account to an assigned match of multiple matches, the assigned match comprising at least one of a first match or a second match; and causing, by the computing system, execution of the video game for the user account in the assigned match, wherein the sensor data comprises raw sensor data generated by one or more physical sensors of the handheld device. receiving, by a computing system , game control data and sensor data from a client machine , wherein the game control data and the sensor data are associated with a user account that is logged into a video game service , wherein the game control data is to be processed by a video game for controlling an aspect of the video game, and wherein at least one of the game control data or the sensor data is received as encrypted data; determining, by the computing system, private key data associated with a private key that was used to encrypt the encrypted data, the private key data comprising at least one of: a length of time that the private key has been associated with the user account; a number of times the private key has been used with, or used to login to, the user account; or a number of times the private key has been switched between different user accounts; a length of time that the private key has been associated with the user account; a number of times the private key has been used with, or used to login to, the user account; or a number of times the private key has been switched between different user accounts; determining, by a computing system, a score associated with the user account by: providing the sensor data and the private key data as input to a trained machine learning model ; and generating the score as output from the trained machine learning model, the score indicative of a probability of the game control data having been generated by a handheld device associated with the client machine; providing the sensor data and the private key data as input to a trained machine learning model ; and generating the score as output from the trained machine learning model, the score indicative of a probability of the game control data having been generated by a handheld device associated with the client machine; assigning, based at least in part on the score, the user account to an assigned match of multiple matches, the assigned match comprising at least one of a first match or a second match; and causing, by the computing system, execution of the video game for the user account in the assigned match, wherein the sensor data comprises raw sensor data generated by one or more physical sensors of the handheld device. <EOS>