Visualisations

In Part 4 of our match report series we will show performance over recent matches to help visualise how the team is trending.

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.

In Part 3 of our match report series we add some stats to show the performance of the team in the given match.

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.

In Part 2 of our match report series we add a set-up page to filter our report page. This page will help to filter our reports to a given match for a team.

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, In this video I am going to show you an easy way of ranking players within a given context. For this I will create a measure that defines the percentile of players within the positional and season context of your choosing. For this, I will also be using one of the external tools recently added to Power Bi called Tabular Editor. Tabular Editor allows you to add new measures and monitor the performance of your queries.

Hi all, In my next video, I build upon the shot plot we created a couple of videos ago using R. This plot was built using ggplot2 and ggsoccer, which allows us to more accurately plot our data. In this video, I add segments to the points allowing you to see the direction of the shots and where they end up. I hope you enjoy! As always, subscribe here for more videos and to Power Performance Through Data.

Hi all, I thought I would follow on from my calculated column a few days ago and present a method for creating this as a measure as well. This measure uses the same DAX with a few minor differences due to how measures work and what they require in Power Bi. As always, subscribe here for more videos and to Power Performance Through Data. Import Notes for Measures There are a few important things to keep in mind when working with measures.

Hi all, Today I am going to focus more on a calculation rather than the visual. For this video, I will focus on a rolling average across matches, rather than days. This requires an extra step to calculate an index value for the match date. In a future video I will show a different method for doing this as well for different types of data. As always, subscribe here for more videos and to Power Performance Through Data.