Real-time Play Valuation Using Net Expected Scoring
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Solution Overview
Problem
Conventional fantasy sports scoring systems fail to account for the situational context of athletic performances, leading to inaccurate valuation of plays and athletes, as they solely rely on cumulative statistics without considering the game situation or impact on the outcome.
Innovation Solution
A valuation system that calculates the net expected scoring (NES) for each game state based on historical data and regression analysis, allowing real-time valuation of plays by determining the difference in expected scoring before and after a play, and distributing this value among athletes involved, taking into account the specific circumstances of each play.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fantasy sports scoring systems assign points based solely on cumulative statistics, then the scoring system is simple and easy to implement, but the valuation of plays and athletes becomes inaccurate because it does not account for situational context
Solution Approach 1:
The patent segments the valuation process into distinct components: (1) defining game states based on situational context, (2) calculating net expected scoring (NES) for each game state using historical data, (3) determining play value as the difference between post-play and pre-play NES, and (4) distributing value to individual athletes. This segmentation allows accurate situational valuation while maintaining a structured, manageable system framework.
Solution Approach 2:
The patent applies preliminary action by pre-calculating NES values for all possible game states using historical data and regression analysis before actual games occur. This creates a lookup table of expected scoring values for various situations, enabling real-time play valuation without complex calculations during live gameplay, thus balancing accuracy with computational efficiency.
2Measurement precision
If points are assigned based purely on cumulated statistics at the end of competition, then the scoring method is straightforward and requires minimal processing, but it fails to distinguish between plays of different situational value
Solution Approach 1:
The system performs preliminary calculations by pre-computing NES values for all possible game states using historical data before competitions begin. This creates a ready-reference database of expected scoring values, allowing real-time play valuation to simply look up pre-calculated values and compute differences, minimizing processing time during actual games while maintaining high measurement precision.
Solution Approach 2:
The patent creates a simplified computational model (NES calculation system) that replicates the complex relationship between game situations and scoring outcomes based on historical patterns. This model copy allows the system to quickly estimate play value without needing to analyze every historical game scenario in real-time, thus reducing processing time while maintaining accurate discrimination of play value.
3Measurement precision
If conventional systems count all yards gained without regard to game situation or defense quality, then the statistics are easy to collect and compute, but they do not reflect the true difficulty or value of the performance
Solution Approach 1:
The patent segments performance assessment into game-state-dependent components by defining specific game states that capture relevant contextual factors (score differential, time remaining, down and distance, defensive strength). This segmentation allows the system to assess performance accuracy without requiring collection of every possible detail, as only state-defining parameters need to be tracked.
Solution Approach 2:
The system changes the parameters used for performance assessment from simple cumulative statistics to situational context parameters (game state descriptors). By transforming the valuation basis from raw statistics to context-aware game states, the system achieves more accurate performance assessment while the parameter set remains manageable and collectible through standard game data feeds.
Data Source
AI summary
A valuation system determines in real-time values of plays occurring during games by identifying a play that occurred during a game. The system determines an expectation of scoring prior to the play occurring, and an expectation of scoring that results from the play occurring. The system then calculates a value of the play as the difference between the expectation of scoring that results from the play occurring and the expectation of scoring that existed prior to the play occurring, and any scoring generated by the play.