Tech-Stack: Python with the DEAP EA library. An evolutionary algorithm selects the optimal football team from a selection of 523 players.
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Updated
Nov 21, 2020 - Jupyter Notebook
Tech-Stack: Python with the DEAP EA library. An evolutionary algorithm selects the optimal football team from a selection of 523 players.
Sistema de automação da seleção de perfis para times
Interactive football tactics platform for building, comparing, and analyzing World Cup XIs, formations, player roles, and tactical setups.
Developing a framework to select cricket teams by analyzing sports commentary
A modern web app for fair and effortless team organization through smart randomization tools.
This project predicts the optimal playing XI for IPL matches using statistical models and player performance data. It assists in fantasy cricket team selection and match outcome forecasting.
A modern and responsive cricket team selection web application built with React, TypeScript, Tailwind CSS, and DaisyUI. Users can claim free credits, browse available players, select players within their budget, and manage their selected team.
Constrained optimization engine for cricket team selection using MILP — budget, role, and form constraints.
A Spring Boot-based backend application for intelligent cricket team selection. ICTSS uses machine learning and real-time analytics to optimize team selection based on player statistics, match conditions, and more.
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