LLM Fantasy Sports Recap Generation with Tone Constraints

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Solution Overview

Problem

Generating custom, entertaining, and offensive-free recaps for fantasy sports leagues is challenging, especially with large user bases, as existing methods struggle to personalize content effectively.

Innovation Solution

Utilizing large language models (LLMs) to generate customized recaps for fantasy athletic teams by obtaining relevant statistics, creating prompts with constraints, and processing outputs to ensure conformance to predetermined guidelines, including tone and format.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If existing methods are used to generate recaps for fantasy sports leagues, then the system can handle large user bases, but the recaps lack personalization and entertainment value

Engineering Contradiction:

Improvepersonalization capabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent uses large language models to generate recaps by copying and adapting from a vast training dataset of sports content, allowing the system to produce personalized recaps without requiring complex custom writing logic for each user scenario

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system adjusts parameters such as tone, style, and content focus based on user preferences and team characteristics, enabling personalized recaps while using the same underlying LLM infrastructure

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If existing methods are used to generate recaps, then the system can process data efficiently, but the content quality and entertainment value are insufficient

Engineering Contradiction:

Improvecontent qualityVSAvoidrecap generation speed

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The patent replaces traditional mechanical data processing and template-based recap generation with large language models that use statistical patterns and contextual understanding to generate high-quality, entertaining content at scale

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Object-affected harmful factors

If existing methods are used to generate recaps, then the system can maintain simplicity, but offensive or inappropriate content may appear

Engineering Contradiction:

Improveoffensive contentVSAvoidsystem simplicity

Core Design Contradiction:

Object-affected harmful factorsVSEase of operation

Solution Approach 1:

The system incorporates feedback mechanisms including user reports and automated content moderation that continuously refine the recap generation to eliminate offensive content while maintaining ease of use through automated filtering rather than complex user control systems

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20250200291A1Systems and methods for generating customized recaps for fantasy athletic leagues

Publication Date: 2025.06.19 YAHOO ASSETS LLC

AI summary

In some implementations, the techniques described herein relate to a method including: (i) obtaining, by a processor, at least one statistic related to a recent history of a fantasy athletic team managed by a user within a fantasy athletic league, (ii) creating, by the processor, a prompt for a large language model (LLM), the prompt comprising, the at least one statistic and a set of constraints configured to produce as output from the LLM a fantasy team recap that conforms to at least one predetermined guideline, (iii) providing, by the processor, the prompt to the LLM as input, and (iv) causing display, by the processor, of the fantasy team recap output by the LLM in response to the prompt.