I’m Chris, Head of Analytics at Arsenal and hiring manager for this role (https://www.linkedin.com/in/chris-dove-43b7a85)
I’m happy to answer any questions about the role, our department, football analytics, working at Arsenal, etc.
I also work in IT, albeit in a different field, mostly with Kubernetes clusters, DevOps tools and private clouds. Is your team working with these technologies, does Arsenal have some separate team for this sort of infrastructure-related work? I won't lie, from time to time I check Arsenal job postings but I never once saw anything related to the infra, which is why I'm asking.
Does your team and department taking of analytics primarily on the footballing side? Like player performance? How does your teams work typically get incorporated and what does the day to day look like? Do you manage your own tech stack as well?
> Does your team and department taking of analytics primarily on the footballing side? Like player performance?
Yes, we work primarily on the footballing side and across the spectrum in that space: Player/team performance for the men's first team, women's first team, and boys academy age groups U16 and up, player recruitment / squad planning, etc.
> How does your teams work typically get incorporated
We produce a mix of interactive tools, regular static reports (e.g. opposition analysis, post-match analysis, etc.), and live dashboards that come from specific stakeholder requests such as coaching staff or execs, or that we build proactively to address a specific football-related question.
> what does the day to day look like?
It really varies from day to day and role to role within the team. A data engineer might be adding another data provider to an entity resolution ETL pipeline, a research scientist might be incorporating feedback from first team coaching staff into a work-in-progress model, a data analyst might be putting together an in-depth opposition analysis report for an upcoming match, and an operations analyst might be helping train operators on a new data labeling task.
> Do you manage your own tech stack as well?
We do manage most of our tech stack, although we get a lot of support on front-end from a great sister team in the IT dept.
As in, perhaps decisions about unexpected red cards ?
It has already had a big impact for ball crossing the goal line judgments if you put computer vision in the broader AI category (e.g. Hawkeye in the PL)
It was mainly sneaking in some levity.
That call was poor.
It's a similar conflict of interest, if not outright corruption as Justice Clarence Thomas getting free all expenses paid fishing trips and other goodies from a billionaire who wants to influence Supreme Court decisions.
Regardless of their sophistication, 3rd party data products in football tend to rely on manually collected and maintained player metadata. It can be unreliable. If I could reliably have a durable unique ID for every player, manager, and team in world football along with reliable timestamps for every moment each said player entered and left play, that would be pretty great. When joining together disparate data sources, discrepancies in things this simple cause all sorts of pain downstream.
https://moj-analytical-services.github.io/splink/
(Disclaimer: I am the lead author, but the tool is FOSS)