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:

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.