Tag Running is a web-based concept designed to reframe how recreational runners—particularly aging or returning athletes—track and interpret their progress. While running is an inherently personal pursuit, our understanding of achievement has become heavily stat-driven. Yet, as Good Run Guide describes, many runners find that once their peak personal bests are behind them, it becomes difficult to benchmark progress or maintain motivation.
Tag Running reimagines this experience by focusing on True Age Grading—a system that adjusts run times based on age and gender but presents the data in a more accessible, visual, and emotionally resonant way.
Key Issues with the Current Process
Limited Visibility and Usability
Age-graded times exist but are buried in single columns on sites like Parkrun or tucked away on outdated platforms with poor UX.
Lack of Motivation for Most Runners
The current system focuses on elite comparisons (world record pace) and provides little encouragement for new or mid-tier runners—especially anyone below a 60% grading, who sees no actionable insight.
Disconnect in Data Relevance
Parkrun’s grading model doesn’t reflect the unique difficulty of different courses. A flat 5K isn’t the same as a hilly trail run, so runners feel a disconnect between how they feel and how they score.
Opaque Grading System
The difference between 61% and 68% is unclear, and there’s no narrative or feedback to help runners improve or set goals. The system lacks context, clarity, and continuity.
Design Approach
User Discovery
Analysed how runners engage with Parkrun—searching by course, gender, age, and start time. This informed the filtering system. Acknowledged accessibility concerns around binary gender collection in the source data.
Visual Storytelling
Replaced dry data tables with a dynamic chart that offers clarity at a glance. Inspired by sports performance apps, the visualisations and messaging are designed to feel empowering rather than judgmental.
UI & UX Considerations
Incorporated Parkrun’s colour palette to maintain familiarity, with light-touch branding that feels like an extension of the existing ecosystem. Microcopy and alert messages help set user expectations, particularly where data is missing or skewed.
Scoring Over Percentages
Introduced a new scoring system—a higher, more abstract number that tracks personal growth in a gamified way, providing motivation even below traditional performance thresholds.
Key Features
Course-Specific Benchmarking
Users can search and compare performance by Parkrun course, with historical age-graded data visualised clearly.
Personal Growth Insights
The system contextualises a user’s current level—local, regional, or national standard—with potential to track improvement over time.
Visualised Goal-Setting
Instead of vague targets, runners receive tangible goals (“Drop 2 minutes to hit next tier”) linked to future runs or training blocks.
UX Writing to Support All Levels
Carefully written microcopy encourages all users, particularly beginners or those returning after injury or time off.
Next Steps
Data Expansion
Complete collection and cleaning of Parkrun course data across a wider sample to ensure national coverage.
Training Integration
Link results to tailored training plans (e.g. “Drop 2 minutes in 6 weeks” prompts with a suggested program).
Local Club Integration
Based on the user’s level and location, suggest relevant running clubs to support next steps in real life.
Social Features
Explore ways for users to share results as graphic summaries—ideal for personal milestones or social accountability.
Edge Case Testing
Resolve limitations in the current scoring system (e.g. handling 99:99 finish times or extreme outliers) to ensure robustness across all data inputs.
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