Adam Riley
Software Development
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Gameplay Data Extraction for League of Legends Through
Computer Vision
Game analytics plays an important role esports much easier. This system adds
and electronic sports (esports) by getting like football or basketball.
in guiding teams in both traditional sports
a better understanding of the opponent’s
strategies. Unfortunately, not every esport This thesis brings these two worlds
collect and analyze the data needed for extract, collect, and analyze gameplay
game has a reliable method to extract,
team and player analysis. For instance,
League of Legends, a popular Multiplayer
Online Battle Arena (MOBA) video game,
does not provide the ability to track
together and presents a methodology to
data from League of Legends match
videos via an automated computer vision
system.
gameplay data like players’ position, hit I tracked the positions of players on
having to watch and manually encode the Convolutional Neural Networks (CNNs)
points and mana within the game without
entire match.
On the other hand, machine learning is
taking the world stage by using object
detection to help Artificial Intelligence (AI)
learn the features within images to make
analysis of various traditional games and
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various visuals to games watched at home
SOFTWARE DEVELOPMENT
the minimap using object detection via
and encoded them into a data file that can
accelerate the work of analysts and will
thus lead to more informed and decisive
strategies.