Graph based method of next pitch prediction

A system for predicting a next pitch, comprising:

• a processor;
• and
• a memory having programming instructions stored thereon, which, when executed by the processor, performs one or more operations, comprising:
• retrieving pitch-by-pitch information for a plurality of events and game context information associated with each pitch in the pitch-by-pitch information;
• converting the pitch-by-pitch information and the game context information into a plurality of graph-based representations comprising nodes and edges;
• providing the plurality of graph-based representations to a graph neural network;
• training the graph neural network to generate a pitch type prediction for each pitch based on the provided plurality of graph-based representations comprising the nodes and the edges, wherein the graph neural network includes a first multilayer perceptron layer, a second multilayer perceptron layer, and a third multilayer perceptron layer, and wherein the training comprises:
• identifying a leading node and a trailing node for each of the edges;
• outputting, from the first multilayer perceptron layer, embedded values of the edges based on (i) features corresponding to the leading node and the trailing node for each of the edges and (ii) edge information that connects each of the nodes in time;
• outputting, from the second multilayer perceptron layer, embedded values of the nodes based on (i) the embedded values of the edges and (ii) each of the nodes corresponding to a respective pitch delivered by a respective pitcher in a game;
• and
• outputting, from the third multilayer perceptron layer, the pitch type prediction based on (i) the embedded values of the edges, (ii) the embedded values of the nodes, and (iii) global variable information incorporating the game context information;
• providing a current graph-based representation of current pitch-by-pitch information for a current pitcher and current game context information, to the trained graph neural network;
• and
• predicting via the trained graph neural network, a pitch type for the next pitch to be delivered from the current pitcher, based on the provided current graph- based representation of the current pitch-by-pitch information for the current pitcher and the current game context information.

A non-transitory computer readable medium including one or more sequences of instructions that, when executed by one or more processors, causes:

• retrieving, by a computing system, pitch-by-pitch information for a plurality of events and game context information associated with each pitch in the pitch-by-pitch information;
• converting, by the computing system, the pitch-by-pitch information and the game context information into a plurality of graph-based representations comprising nodes and edges;
• providing, by the computing system, the plurality of graph-based representations to a graph neural network of the computing system;
• training, by the computing system, the graph neural network to generate a pitch type prediction for each pitch based on the provided plurality of graph-based representations comprising the nodes and the edges, wherein the graph neural network includes a first multilayer perceptron layer, a second multilayer perceptron layer, and a third multilayer perceptron layer, and wherein the training comprises:
• identifying a leading node and a trailing node for each of the edges;
• outputting, from the first multilayer perceptron layer, embedded values of the edges based on (i) features corresponding to the leading node and the trailing node for each of the edges and (ii) edge information that connects each of the nodes in time;
• outputting, from the second multilayer perceptron layer, embedded values of the nodes based on (i) the embedded values of the edges and (ii) each of the nodes corresponding to a respective pitch delivered by a respective pitcher in a game;
• and
• outputting, from the third multilayer perceptron layer, the pitch type prediction based on (i) the embedded values of the edges, (ii) the embedded values of the nodes, and (iii) global variable information incorporating the game context information;
• providing, by the computing system, a current graph-based representation of current pitch-by-pitch information for a current pitcher and current game context information, to the trained graph neural network;
• and
• predicting, via the trained graph neural network, a pitch type for a next pitch to be delivered from the current pitcher, based on the provided current graph-based representation of the current pitch-by-pitch information for the current pitcher and the current game context information.