[SeptembRSE Turing Data Story] Football discipline v aggression - a look at yellow/red cards and results

[billfinnegan]

Story description

Please provide a high level description of the Turing Data Story A clear and concise description of what the data story is going to be about.

Andrew Gait: Inspired somewhat by reading the baseball-based story yesterday I wondered about further stories using various analysis of (open-source) data available for other sports; as a (simple) example, I’ve always wondered whether there’s some kind of correlation between “discipline” and “result” in sport (e.g. in football, is the result inversely proportional to the number of yellow cards received by each team?)

Pulled from: https://hackmd.io/CuYW9hsjSu2OlOHYKVWw6w?both

Which datasets will you be using in this Turing Data Story? Cite the dataset that are going to be used in this story (these of course can change whilst developing the story).

https://datahub.io/sports-data/english-premier-league#python

Readme: This dataset contains data for last 10 seasons of English Premier League including current season. The data is updated on weekly basis via Travis-CI. The dataset is sourced from http://www.football-data.co.uk/ website and contains various statistical data such as final and half time result, corners, yellow and red cards etc.

Additional context Add any other context or screenshots about the story here.

Ethical guideline

Ideally a Turing Data Story has these properties and follows the 5 safes framework.

• [ ] The analysis you produce is openly available and reproducible.
• [ ] Any data used are open and have an explicit licence, provenance and attribution.
• [ ] Any data used are not personal data (i.e. the data is anonymous or anonymised).
• [ ] Any linkage of datasets in your data story does not lead to an increased risk of the personal identification of individuals.
• [ ] The Story must be truthful and clear about any limitations of analysis (and potential biases in data).
• [ ] The Story will not lead to negative social outcomes, such as (but not limited to) increasing discrimination or injustice.

Current status

• [ ] Scoping of the story
• [ ] Write story outline
• [ ] Add material to the story notebook
• [ ] Combine materials into a readable story
• [ ] Proofread
• [ ] Request reviews
• [ ] Address reviews
• [ ] Merge to master branch.

Updates

[andrewgait]

Adding a comment to make sure I'm subscribed to this.

[andrewgait]

Do we link the notebook that has been started from here already or wait until it's in a more "polished" state?