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PokéAnalytics

A much-awaited follow-up to the idea proposed here, this project combines Pokemon Showdown usage data with canonical inequality/diversity metrics from social sciences to calculate quantitative metrics for the otherwise hand-wavey concept of metagame balance.

How To

  • From the project directory, run bash ./scripts/scraper.sh to scrape usage data from smogon. Change the list of files as desired in the script file. The script will place all json files in a data directory.
  • Once you have your data, you can compute the balance metric for a given file like so:
python analysis/balance_metrics.py --month 2016-11 --format ru-1760 --metric gini

This will print the value of the metric.

  • More importantly, you can plot (courtesy matplotlib) the value of a given metric for a given format over time by simply not providing the month:
python analysis/balance_metrics.py --format ru-1760 --metric gini
  • And you can plot multiple formats on the same figure by providing multiple arguments to the format flag:
python analysis/balance_metrics.py --format ru-0 ru-1500 ru-1630 ru-1760 --metric gini

The plot given by the last command:

example

Metrics

The metrics implemented, and there corresponding format flag argument:

  • Gini coefficient gini
  • True diversity diversity
  • Richness richness
  • Shannon index shannon
  • Rényi entropy renyi
  • Simpson index simpson
  • Gini-Simpson gini_simpson
  • Berger-Parker index berger_parker

The diversity indices and their calculations are from wikipedia.