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February 20, 2020

Tournament Analysis

Tournament Analysis

This post goes over the web page I made for filtering and generating statistics from games played in selected StarCraft II tournaments. Only included tournaments are those that released replay packs, and were played since 2019 (currently 4735 games). If there is a replay pack that I missed, or someone has a replay pack that isn't freely available and would want to add it here, let me know.

As always, data is the main limiting factor. I'm not claiming this will provide some deep insight into the game. With StarCraft II, you either have data that are relevant, but the dataset is too small, or the dataset is of good size but gathered across too wide skill level and different metagames.


Imgur albums of unfiltered stats:

App link (free hosting, sorry about it being slow):

Filtering

There are several ways to filter, and you can combine these filters:

  • Tournament
  • Map
  • Matchup
  • Minimum and maximum game length
  • Date interval in which games were played
  • Minimum number of certain unit types created during each game

Stats

I added what I though could be interesting. Let me know if there are other interesting stats/charts.

  • Non-mirror matchup winrates
  • Map winrates
  • Hero unit based on total resources killed

Charts

  • Unit cost-effectivness – compares different unit types based on the resource value of killed units divided by resources lost
  • Wins per country
  • Number of wins over game time
  • Winrate over player rating
  • Winrate over game time
  • Game length distribution for different matchups
  • Active workers over game time
  • Mining rate over game time
  • Army value over game time
  • Supply used over game time
  • Proxy locations for Barracks, Starports and Photon Cannons for each map – built in the first 5 minutes and in at least 40 distance from owner's starting location
  • Various pie charts for each race for units killed, lost, created in total numbers or equivalent resource value


GOING FORWARD

If there are good ideas for additional statistics, I will add them. I will add more tournaments as I get hands on more replay packs.

Overall, this was a good project to learn a bit more Python. Main used packages are flask, matplotlib, pandas and sc2reader.

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