In this Python Tutorial I will plot event data from StatsBomb in a few different scenarios. This will include shots and passes from a single match. This data will be called using the StatsBomb python library and reformatted entirely in Python. I hope you enjoy.
Hi guys,
In this weeks tutorial, we are expanding on the shot plot we created in R by adding some extra information to easily understand the plot and some context around it. This will include cards which total up shots and are coloured based on the if this game was above or below an average for the season. We will also have a matrix at the bottom, highlighting how the shots were created such as from a corner or open play.
Hi all,
Welcome to a new series of videos I am starting this week, creating a match report using StatsBomb event data. This series will run over a few videos, starting with this first video walking through loading data in to Power Bi.
As always, subscribe here for more videos and to help you Power Performance Through Data.
Enjoy the video and if you have any questions, please leave a comment below.
Hi all, last time we created a nice shot plot using the built-in scatter plot for Power Bi. Today we will take things a step further, using the R Custom Visual in Power Bi. This visual allows you to use R code to create a visual however you want, with that visual interacting with the slicers on your page. Use base ggplot2, these visuals will not have any interaction ability, such as tooltips, but they provide a neat way of creating visuals not possible with the built-in set provided by Microsoft.
Hi all, following on from my last tutorial, I have now created something more football specific using the built-in scatter plot in Power Bi. This tutorial will take you through building a basic shot plot with shots coloured by outcome. The video can be found at the bottom of the page, but I will also take you through a step by step process here as well.
As always, (subscribe here)[https://www.
This post is aimed at walking through one method of comparing players upon specific metrics within a league setting. For this example I will use a couple of different metrics from the free StatsBomb FA WSL dataset.
In this tutorial I take you through reformatting a match events file downloaded as "tidy" data frame from the statsbomb library. This will hope to show you some basic needs when reformatting these files for use in visualisations or databases.