Data Visualisations

Match Report Part 6 - Shooting Analysis

In part 6 of our match report series, find out how to dig a little deeper in to your data with a simple shooting analysis of the match.

Match Report Part 5 - Season Ranking

In Part 5 of our match report series, we look back at what we have done so far and also add performance of our team throughout the season. Check it out today!

#WOW2021 #PowerBi - First 4 Weeks

Hey guys, This week I started to make my way through the Workout Wednesday for Power Bi challenges. This is an awesome extension of the Tableau community to Power Bi, providing challenges weekly to help extend your capabilities in the given software.

Match Report Part 4 - Recent Performance

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

Plotting Event Data in Matplotlib

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.

Match Report Part 3 - Today's Performance

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

Tutorial - Team Shot Dashboard

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.

Match Report Part 2 - Set-Up Page

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.

Match Report Part 1 - Data Load

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.

Tutorial - Ranking Player Performance

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.