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Scraping statistics, predicting NBA player performance with neural networks and boosting algorithms, and optimising lineups for Draft Kings with genetic algorithm
This is the code for constructing a portfolio of lineups for DraftKings baseball contests with a top heavy payoff structure. This code is based on the paper Picking Winners Using Integer Programming by David Hunter, Juan Pablo Vielma, and Tauhid Zaman (https://arxiv.org/abs/1604.01455).
We have used our skill of machine learning along with our passion for cricket to predict the performance of players in the upcoming matches using ML Algorithms like random-forest and XG Boost
Python API client that can be used to make calls to the Yahoo! Fantasy Sports API. Developed specifically for NHL, but should support the NFL, MLB, and NBA as well.
A flutter application for a simplified version of Fantasy Cricket like Dream11. Users can create private pools and share joining link with others. The winners is declared at the end of the match and prizes are distributed.