Sports Analytics Playbook via Multi-Template Alignment
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Solution Overview
Problem
Existing sports tracking systems struggle to efficiently store, catalog, and retrieve individual game sequences, and provide effective interactive analysis tools for sports data, limiting their usefulness in visualizing and predicting player movements and game outcomes.
Innovation Solution
A system that processes sports game sequences using multiple-template alignment and a hash-table-based approach to create a 'playbook' of plays, allowing for interactive statistical analysis and prediction of game events by querying a database with graphical representations of player and ball trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional sports tracking systems store and retrieve individual game sequences, then complete game data is preserved, but retrieval efficiency and query speed deteriorate
Solution Approach 1:
The patent segments game sequences into discrete 'plays' using multiple-template alignment, where each play represents a meaningful action unit (e.g., offensive possession, defensive stop). This segmentation enables the system to retrieve specific plays independently rather than processing entire games, dramatically reducing query time while maintaining data completeness through systematic cataloging of all plays in a hash table structure.
Solution Approach 2:
The system performs preliminary alignment and cataloging of all game sequences into a structured playbook during data processing. By pre-aligning trajectories using multiple templates and organizing plays into a hash table with decision-tree framework before queries are made, the system eliminates the need for complex real-time processing during retrieval, achieving both complete data preservation and fast query response.
2Measurement precision
If multiple-template alignment is used to improve play discovery accuracy, then alignment precision increases, but computational complexity increases
Solution Approach 1:
The patent implements a dynamic multiple-template alignment system where templates are adaptively selected and refined based on the specific play being analyzed. Rather than using a fixed complex algorithm for all cases, the system dynamically adjusts the alignment process by selecting relevant templates from the playbook and using decision-tree frameworks to guide the alignment procedure, reducing unnecessary computational overhead while maintaining high precision.
Solution Approach 2:
The system introduces intermediate structures (hash table playbook, decision-tree frameworks) that mediate between raw trajectory data and final alignment results. These intermediaries organize the complex alignment process into manageable stages, where the hash table provides quick lookup of candidate plays and decision trees systematically evaluate alignment quality, thereby managing computational complexity while achieving high measurement precision.
3Measurement precision
If neural networks are trained on aligned sports data, then predictive accuracy improves, but training time increases
Solution Approach 1:
The system performs preliminary alignment of all training data using multiple templates before neural network training begins. By pre-processing the trajectory data into aligned plays and organizing it into the playbook structure, the system provides the neural network with clean, standardized input data that requires minimal additional processing during training, significantly reducing training time while maintaining high predictive accuracy through the quality of pre-aligned data.
Data Source
AI summary
A system is described for interactively analyzing plays of a sporting event based on real-world positional tracking data. Using positional information regarding the players and/or ball and/or other objects obtained from a tracking system, along with identified event data and contextual information, the system processes a library of plays (e.g., one or more seasons' worth of a league's contests) into a searchable database of plays using multiple alignment templates and discriminative clustering techniques. A user interface is described for interacting with the database in a graphical manner, whereby users can query a graphical depiction of a play and receive the most similar plays from the library, along with statistical information relating to the plays. The user interface further permits the user to modify the query graphically (e.g., moving or exchanging players, ball trajectories, etc.) and obtain updated statistical information for comparison.