A method of predicting the likelihood of a post tee off golf swing or consecutive swings resulting in a ball being sunk in a hole; the method utilizing communication equipped cameras or communication equipped laser rangefinders at known locations to determine accurate ball lie information. Transmission of this location information in real time to a processing facility linked to a database of historical play information incorporating at least ball position information and golf course in order to calculate odds of success of the upcoming swing and/or subsequent swings.

A method for ball game training, the method comprising steps executed by at least one computer, the steps comprising: receiving image data of a player and a ball, the image data being captured using at least two cameras, using the received image data, tracking motion of the player and motion of the ball in three dimensions, based on the tracked motions, predicting a position of the player and a trajectory of the ball, and based on the predicted position and trajectory, generating a control command for at least one ball throwing machine.

A system that can avoid training overemphasized by a taste of a user and prevent an injury or a trouble from being caused by an unnatural body motion by comparing, between the user and other users, evaluation values of parameters based on exercise data and analyzing training. A training management system includes data detecting means for detecting exercise data related to exercise of a user, parameter calculating means for calculating, on the basis of the detected exercise data, exercise information representing information concerning the exercise carried out by the user, evaluation-value calculating means for calculating an evaluation value of the user on the basis of the exercise information, comparison-target acquiring means for acquiring evaluation values of other users, and comparing means for comparing the evaluation value of the user and the evaluation values of the other users.

Training at the proper level of effort is important for athletes whose objective is to achieve the best results in the least time. In running, for example, pace is often monitored. However, pace alone does not reveal specific issues with regard to running form, efficiency, or technique, much less inform how training should be modified to improve performance or fitness. A sensing system and wearable sensor platform described herein provide real-time feedback to a user/wearer of his power expenditure during an activity. In one example, the system includes an inertial measurement unit (IMU) for acquiring multi-axis motion data at a first sampling rate, and an orientation sensor to acquire orientation data at a second sampling rate that is varied based on the multi-axis motion data.

During a first time period and for a first user, a second user is automatically selected based on competitive data of the first user and competitive data of the second user, and a workout selection is sent to cause a video of a workout to be displayed during a second time period on a smart mirror of the first user and a smart mirror of the second user. During the second time period, a live stream of the first user exercising is displayed at the smart mirror of the second user, and a live stream of the second user exercising is received and displayed at the smart mirror of the first user. During the second time period, a performance score of the first user and a performance score of the second user is displayed at the smart mirrors of the first user and the second user.

A training system operates to provide an online training system that includes an instructional portion, a performance portion and a results report. A trainer can create training modules and/or training programs and then launch a training program in which one or more users, utilizing a user system, can participate. A training program consists of one or more training modules. Each training module is configured to first run in a demonstration mode, in which the operator streams a demonstration of the physical activity required by the training module to one or more user systems. Users can thus view the demonstration of the physical activity on the user systems. The training module then enters a trial or trial mode in which each of the participants then engage in performing the physical activity. The user systems present a video/graphical display to show various performance criteria of the training module. The user systems also include a camera that is configured to monitor the activity of the user weighed against the performance criteria. Once the trial mode is completed, the data gathered by the user system cameras is then analyzed and evaluated and presented back to the participants.

The present embodiments provide systems and methods for aggregating measurements captured by different technologies during a golf swing. By capturing measurements using different technologies, more accurate measurements may be provided to a user by selecting from the measurements, offsetting measurements based on the technologies used, and aligning measurements between devices. Further, by aggregating measurements received from different devices, additional features and functionality may be provided to the user that is absent from any one device used alone. Additionally, by storing the aggregated measurements, users, club fitters and instructors may access and leverage larger databases of measurements to better understand the user's golf swing and to provide better recommendations and instruction to the user.

A system and method for generating a play prediction for a team is disclosed herein. A computing system retrieves trajectory data for a plurality of plays from a data store. The computing system generates a predictive model using a variational autoencoder and a neural network by generating one or more input data sets, learning, by the variational autoencoder, to generate a plurality of variants for each play of the plurality of plays, and learning, by the neural network, a team style corresponding to each play of the plurality of plays. The computing system receives trajectory data corresponding to a target play. The predictive model generates a likelihood of a target team executing the target play by determining a number of target variants that correspond to a target team identity of the target team.

A system configured to be coupled with a participant of an activity. The system comprises: a participant activity monitoring unit configured for monitoring a performance of the activity by the participant; an activity information module configured for storing performance information corresponding to the activity; and a participant performance correlator configured for delivering comparative performance data based on the monitored performance of the activity by the participant and the stored performance information.

An athletic training system (200) has a data recording system (202) and a data engine (204). The data recording system (202) is configured to record an athletic competition event. The event may have a first team of players competing against a second team of players. The data engine (204) is configured to receive data associated with the recorded athletic competition event. The data engine (204) processes the data and displays the data as a replay of the event in animated form.