Starcraft_2_Data_Analysis
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Data analysis of Starcraft II replays . Visualization and classification models
Starcraft II Data Analysis
In this repository you might find
The goal of this data exploration is to understand more about Starcraft II Gameplay Thourgh data in order to extract metrics that could identify good players from bad Ones, correlation and hierarchy of features in Starcraft II gameplay and visualizations That could add value to current personal #pysc2 research regarding fairness , games and agent design
Data visualization, including
- Dendogram and heat maps (visual clustering)
- Correlation Matrix
- Correlogram
- Radar chart
- Density
Data exploration, including models
- PCA
- KMeans Clustering
- Feedforward Network
Resources for analytics
MSC
https://github.com/wuhuikai/MSC
GGtracker
http://ggtracker.com/landing_tour
Starcraft2 Replay Analysis
https://github.com/IBM/starcraft2-replay-analysis
sc2reader
https://github.com/GraylinKim/sc2reader
Papers
## Predicting Win/Loss Records using Starcraft 2 Replay Data http://snap.stanford.edu/class/cs224w-2010/proj2010/31_final_project.pdf
An Analysis on the Rush Strategies of the Real-Time Strategy Game StarCraft-II
https://kaigi.org/jsai/webprogram/2017/pdf/446.pdf
Using Logistic Regression to Analyze the Balance of a Game: The case of StarCraft-II TM
https://arxiv.org/abs/1105.0755
Master Maker : Understanding Gaming Skill through Practice and Habit from Gameplay Behavior
http://thomas-zimmermann.com/publications/files/huang-topics-2017.pdf
DataSets
https://www.kaggle.com/alimbekovkz/starcraft-ii-matches-history/data
kudos : Michael Park