Explore complex relationships with network visualisations
Relationships between data points can be an important signal but very difficult to understand and explore. This app shows how it can be done effectively and efficiently.
Relationships between data points can be an important signal but very difficult to understand and explore. This app shows how it can be done effectively and efficiently.
Visualising and exploring big, geographical data can be done quickly with the right tools. This app built with Dash, Dask and Datashader allows users to analyse large quantities of geographical data quickly for deep insights.
Extract macro and micro-scale intelligence from a complex and large text database in an instant.
This app uses AI to analyse video feeds to quantify subjects' movements in real-time allowing for instant feedback and learning.
Breaking down the shot profile data for each player and visualising it to quickly identify and compare players' roles within a team context
How to visualise the shot distance profiles for each team. How do we optimise these visualisations to reveal each team's strategic DNA?
First issue! Also - big sports datasets, visualisations of the week.
Visualising the dramatic changes to the NBA offences over the last 15 years to see how it has changed and where it might be going.
A data-driven look at how ageing affects the modern NBA. How old are the league's best players? Are modern players getting younger? Who's getting playing time? With visuals.
Analyze sports data with hexbin shot charts and bubble charts with Plotly and Plotly Express (source code & my own data for all 30 teams included in my GitLab repo)
Are assists good? In this article, I assess the link between NBA assists and scoring efficiency.
A look at the players whose presence most help their teammates' offence (or... not).
Where shots come from in modern basketball, and why - in visuals.
Catching up with the advanced analytics revolution
Relationships between data points can be an important signal but very difficult to understand and explore. This app shows how it can be done effectively and efficiently.
Visualising and exploring big, geographical data can be done quickly with the right tools. This app built with Dash, Dask and Datashader allows users to analyse large quantities of geographical data quickly for deep insights.
Extract macro and micro-scale intelligence from a complex and large text database in an instant.
This app uses AI to analyse video feeds to quantify subjects' movements in real-time allowing for instant feedback and learning.
How to automate our python scripts to run on a schedule; taking arguments / parameters from a shell input, time zone tricks.
We move onto producing a summary chart capable of telling the story of each game for the teams as well as players involved.