Case Study: Custom Analytics Dashboard for Tampa Bay Lightning

Challenge

Before this project, coaches and front office staff had no direct access to the team’s internal performance data. If they needed information, they had to request a custom report from a data analyst or go without the data entirely. This slowed down decision making and took valuable time from the analytics team. Hockey Operations wanted a way for non technical staff to browse data on their own, even when they were not exactly sure what they were looking for, and to help them ask better informed questions when deeper analysis was required.

Coaches and front office staff had no direct access to most of the internal data the team tracked. Before this project, if they needed information, they had to request a custom report from a data analyst. This slowed down decision making and took valuable time from the analytics team. Hockey Operations wanted a way for non technical staff to browse data on their own, even when they were not exactly sure what they were looking for, and to help them ask better informed questions when deeper analysis was required.

Context

The organization had a large collection of performance datasets covering multiple seasons and time periods. The information could be sliced by date range, season, or game segments and included categories such as power play efficiency, penalty kill performance, and systems-based metrics like forecheck results.

There was no existing dashboard or reporting interface. Everything required a manual request from a data analyst. Access was limited to the analytics staff, but the end users were non technical members of Hockey Operations.

This included the general manager, scouting personnel, assistant coaches, and the head coach.

Solution

Product Work

Met with the Director of Hockey Analytics and members of the statistical staff to gather use cases and translate them into user stories for the initial version of the application.
Designed and built a working prototype to collect real user feedback and guide the development of future features.
Facilitated follow up sessions to collect input on improvements, new statistical categories, and broader team needs.
Used rapid prototyping during live meetings to edit the interface in real time. This allowed stakeholders to see ideas immediately, refine them quickly, and reduce iteration cycles.
Created terminology, labels, and content patterns that made complex hockey data clear and approachable for non technical users.

Engineering Work

Built the entire front end application using Dash, combining Python, React, HTML, and CSS.
Worked closely with a data engineer to create the collection of SQL queries that powered the dashboard.
Structured the application to allow easy exploration of dense statistical information through a spreadsheet-style interface.
Designed the UI in a way that balanced complexity with clarity, making it possible for coaches and front office staff to navigate large datasets without needing analyst assistance.

Outcome

This dashboard became the first custom product launched in a new internal portal for coaches and front office staff. It introduced a self service model for exploring team performance data and reduced reliance on manual reporting from analysts. Although the organization has since adopted a wave of white labeled, cloud-based tools, this dashboard remains in active use because of the unique value it provides and the custom workflow it supports.