CASE STUDY

AI Dynamic Player Ranking
Generator

Our AI-driven solution automates the complex player ranking process for the Squash Federation of India, efficiently handling real-time data and generating accurate monthly rankings for 1500 players across multiple categories.

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SPORTS

OVERVIEW

Handling a Complicated Ranking Algorithm

The Squash Federation of India faced the daunting task of generating monthly player rankings for 1500 players. The ranking algorithm had to consider either two tournaments from the previous month or the top three tournaments of the current year. Additionally, it required separate rankings for different age categories and gender. Initially handled by Celery (Python), the process was time-consuming and complicated. Our AI solution streamlined and automated this process, ensuring quick and accurate rankings based on real-time match results.

HIGHLIGHTS

50% reduction in processing time
Automation of complex ranking calculations with AI
Generation of monthly rankings for 1500 players for different age categories and both genders

TOOLS

Tools we Used

Python

Pandas

NumPy

SQLAlchemy

Flask

React.js

PostgreSQL

PROBLEM STATEMENT

The Countless Challenges

The ranking algorithm required consideration of either two tournaments from the previous month or the top three tournaments of the current year, adding significant complexity.
Processing real-time match results and updating the rankings on both their website and mobile app promptly without any errors was critical as the system had to consider historical match data for accurate ranking calculations.
The solution needed to scale to accommodate growing numbers of players and tournaments.
Ensuring the ranking process adheres to the Squash Federation's guidelines and policies and that the ranking algorithm is transparent and understandable for stakeholders and users.
Standardizing diverse data formats received from different tournament organizers and managing incomplete or missing data entries that could impact the accuracy of the rankings.

POSSIBLE SOLUTION

Our Flawless Solutions

Developed a flexible AI algorithm capable of dynamically adjusting ranking criteria based on specified input parameters, accommodating both the previous month's tournaments and the current year's top tournaments.
Implemented efficient data ingestion and processing pipelines to handle real-time match data, ensuring timely updates to rankings.
Designed the AI system to categorize and process data based on specified age groups and gender criteria, ensuring accurate and separate rankings.
Utilized scalable cloud infrastructure and parallel processing techniques to manage high data volumes, ensuring efficient ranking generation for 1500 players.
Implemented rigorous validation and testing procedures to ensure the accuracy of AI-generated rankings, including cross-checks against historical data.
Developed robust APIs and middleware to integrate the AI solution with existing systems, ensuring smooth data flow and synchronization.
Regularly reviewed and updated the ranking algorithm and process to ensure compliance with the Squash Federation's guidelines and policies.