Pitch Call Intent Tracking for Real-Time Baseball Analytics
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Solution Overview
Problem
Current data analytics in sporting activities, particularly in baseball, are inadequate in accounting for rapidly changing circumstances and fail to distribute real-time intelligence to players effectively, limiting the value and application of data analytics.
Innovation Solution
A system that tracks pitch call intent before a pitch is thrown, derives pitch outcome data based on the call intent, and distributes this data to wearable devices in real-time, allowing coaches and players to make informed adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If data analytics are applied to sporting activities, then intelligence can be extracted from gathered data, but the analytics become static and inadequate for rapidly changing game circumstances
Solution Approach 1:
The system transitions from static data analytics to dynamic real-time analytics by continuously tracking pitch call intent before pitches are thrown and comparing it with actual pitch outcomes. This dynamic approach allows the system to adapt to rapidly changing game circumstances by processing data in real-time and providing timely insights to coaches and players.
Solution Approach 2:
The system captures pitch call intent data before the pitch is thrown, performing preliminary data collection and analysis. This allows the system to have the intended pitch information ready in advance, enabling faster comparison with actual outcomes and quicker distribution of insights to players during the game.
2Loss of information
If data analytics are distributed to players, then real-time intelligence can be provided, but the distribution is not timely enough for rapidly changing game circumstances
Solution Approach 1:
The system maintains continuous operation by tracking pitch call intent before each pitch and continuously comparing it with actual pitch outcomes. This continuous data collection, analysis, and distribution cycle ensures that insights are provided to players without interruption or significant delay, maintaining timeliness throughout the game.
Solution Approach 2:
The system implements feedback by comparing intended pitch calls with actual pitch outcomes and using this information to provide real-time insights to coaches and players. This feedback loop enables continuous improvement and adjustment of strategies based on actual game performance, delivering timely intelligence that reflects current game circumstances.
3Loss of information
If pitch outcome data is derived relative to pitch call intent, then relevant insights can be provided, but the system complexity increases
Solution Approach 1:
The system segments the data analytics process into distinct components: capturing pitch call intent before pitches, tracking actual pitch outcomes, comparing intent with outcomes, and distributing insights to players. This segmentation allows each component to be optimized independently and simplifies the overall system architecture while maintaining the ability to derive comprehensive pitch outcome insights.
Data Source
AI summary
A method includes receiving, from a coach device, a first pitch call for a first pitch to be thrown prior to the first pitch being thrown; creating a pitch call intent data file corresponding to the received first pitch call; receiving post first pitch game circumstance data corresponding to one or more results of the first pitch having been thrown; and comparing the pitch call intent data file to the received post first pitch game circumstance data to generate first pitch outcome data, wherein the first pitch outcome data is generated relative to the pitch call intent data file and prior to a second pitch that is subsequent to the first pitch having been thrown.