Portfolio

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Midterm Project: League of Legends Diamond Ranked Trend

Midterm School Project that analyzes trends of diamond ranked players in League of Legends. It explores statistical analysis with confidence intervals and data visualizations. Data was downloaded from Kaggle.

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League of Legends Champion Match Outcome Prediction

Taking a step further with League of Legends, I first generate a SQLite Database file using Riot Game’s API which involves generating various lists of python code.

Then, another database is created by scraping the website of Counterstats.net to score each champion’s best counter and worst counter based on lane matchups.

Finally, all the data is cleaned and a model is made to attempt to predict the outcome of a match based off of a match’s champion selection using various machine learning tools. Ultimately the model was unable to be improved past 50% prediction accuracy. However, this could be a sign into how balanced the game could be at the moment; if a match could be predicted reliably based on champions picked alone, it may not be a sign of a balanced game!

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