output_png

In this folder you will find all the plots generated by the scraper.

Both directories gameProgressions and progress_plots, as well as their subdirectories (corresponding to teams & their seasons specified in options.py) are automatically generated when running the scraper.

Below you can find further information about the content in these folders and crucial information for interpreting the plots within them.

gameProgressions

This folder's subdirectory hierarchy looks as follows:

team / season / individual games & all games plotted together

In here you will find analysis of individual game's progressions. Data for this is scraped from "Spielverlauf" (game progression), which is recorded live while a game goes on. Let's look at an example:

Here you can see a game from the U15 league. The graphs in this folder show a game's goal differential over time, representing a team's performance (drops/increases) over the course of a game. For each season there is also a plot representing analysis of a team's performance over the course of a whole season.

These graphs look like the one above. The median performance of a team is calculated by taking the median of all moving average values at each minute of a game. This is supposed to be an indicator for a team's consistency:

Please Note For any interpretation of these graphs the follwing is important to consider:

• Wether the progression of a game is rated as positive or negative (your team is leading or trailing on the scoreboard) depends on a hardcoded list of keywords:

us = ['lakeside', 'wacker', 'steffisburg']
if any(us in home.lower() for us in us):
    homeAway = 0
else:
    homeAway = 1

• The game progression plotter looks for any of these values in the title of the .csv file which is read in. The naming convention for these files follows this scheme:

  yy_mm_dd_{home team} _ {away team}.csv

  This, of course is biased towards what interests myself: how well my local teams performed.

progress_plots

This folder's subdirectory hierarchy looks as follows:

team / season / individual players (& all players plotted against each other) / individual stats for individual players

The above graph shows statistics of an expert penalty taker (Ivan Wyttenbach) over the course of his season 2019/2020. For each datapoint you can see how many goals out of how many attempts he scored.