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This project was an assignment in my 3rd year at university, conducting an analysis into a set of telemetry data of 1000 matches from league of legends season 9, to research what can be learnt about how players are playing League of legends? Additionally, I conducted a user experience (UX) study, to analyse league of legends usability, with both experienced and novice users. My study itself was a brief 1 on 1 interview and play session with a handful of participants. 

The telemetry data analysis was conducted within Spyder 4.0, using Python to calculate and find the averages of most used items and champions, weather the first tower kill gave a team a higher success rate and conducting a Chi2 test to see if higher rank players commonly have higher success rates than lower rank players. 

All results and research for this project can be found below in the linked paper PDF.
Here are some screenshots of the python script I wrote for my research. 
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Here is the research paper PDF
 
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