Complete Features Guide

Overview

Track and compare your running volume across multiple years with day-by-day cumulative distance charts. This feature overlays multiple years on a single graph, allowing you to instantly see whether you are ahead or behind your previous best years at any point in the season.

Capabilities

• •Cumulative distance curves for up to 10+ years of running history
• •Day-by-day comparison showing exact YTD (year-to-date) position
• •Visual identification of peak training periods and off-seasons
• •Percentage comparisons between current year and historical performance
• •Toggle between calendar year and custom date ranges
• •Automatic highlighting of current year with distinct styling

Use Cases

• →Marathon training: Compare current training block to previous marathon prep cycles
• →Annual goals: Track progress toward yearly mileage targets
• →Comeback tracking: Monitor recovery progress after injury or break
• →Long-term trends: Identify multi-year growth or decline patterns

Overview

View comprehensive aggregate statistics for your running activities including total distance, total time, total elevation gain, and activity count. Filter by specific years or view year-to-date (YTD) versus full-year comparisons.

Capabilities

• •Total distance covered (kilometers or miles)
• •Total running time (hours and minutes)
• •Total elevation gain (meters or feet)
• •Total number of activities/runs
• •Year-by-year filtering for historical comparison
• •YTD toggle to compare partial years fairly
• •Average pace across all selected activities
• •Longest single run distance

Use Cases

• →Annual review: Summarize yearly running achievements
• →Training volume monitoring: Ensure adequate weekly/monthly mileage
• →Goal validation: Confirm completion of distance or time goals
• →Consistency tracking: Monitor activity frequency trends

Overview

Analyze when you run with detailed breakdowns by hour of day and day of week. This temporal analysis reveals your running habits, preferred training times, and scheduling patterns across your entire activity history.

Capabilities

• •Hour-of-day distribution (24-hour breakdown)
• •Day-of-week distribution (Monday through Sunday)
• •Heatmap visualization showing peak running times
• •Activity count aggregation for each time slot
• •Percentage calculations for each period
• •Historical data spanning entire Strava activity history

Use Cases

• →Schedule optimization: Identify most productive running times
• →Habit formation: Track consistency in training schedule
• →Travel analysis: See how running patterns change in different locations
• →Work-life balance: Understand how work schedule affects training

Overview

Automatically identify and rank all cities and locations where you have run, sorted by total distance logged. This feature uses GPS data to determine geographic locations and aggregates all activities by city.

Capabilities

• •Automatic city detection from GPS coordinates
• •Distance totals for each unique location
• •Ranking by cumulative kilometers/miles
• •Activity count per location
• •Coverage across countries and regions
• •Historical tracking of location-based running

Use Cases

• →Travel running: Track runs across different cities and countries
• →Home base identification: Confirm primary training location
• →Exploration goals: Motivate running in new locations
• →Relocation tracking: Compare running volume before and after moves

Overview

Analyze how temperature and weather conditions affect your running performance. Every run is plotted against the temperature at which it was run, allowing you to identify optimal conditions and understand seasonal adaptations.

Capabilities

• •Temperature data for each activity (Celsius/Fahrenheit)
• •Scatter plot visualization of pace vs temperature
• •Identification of optimal temperature ranges
• •Seasonal pattern recognition
• •Historical weather data across all runs
• •Performance trends across temperature ranges

Use Cases

• →Race planning: Choose events in favorable temperature ranges
• →Heat/cold adaptation: Track performance as seasons change
• →Training optimization: Schedule hard workouts during ideal conditions
• →Personal records: Understand role of weather in PRs

Overview

Travel back in time to see what you were running on this exact day in previous years. This feature provides a date-specific view of your running history, allowing anniversary comparisons and seasonal tracking.

Capabilities

• •Date-specific activity lookup across all years
• •Side-by-side comparison of same date, different years
• •Activity details for each historical instance
• •Running streak identification for specific dates
• •Seasonal pattern recognition
• •Anniversary celebration tracking

Use Cases

• →Annual comparisons: See year-over-year progress on specific dates
• →Seasonal analysis: Understand how same date performs across years
• →Running anniversaries: Celebrate milestones and streaks
• →Motivation: Reflect on past achievements from same time period

Overview

Visualize every GPS grid cell you have ever run through, color-coded by recency. This unique feature divides geographic area into cells and tracks which areas you have explored. Includes archetype classification based on exploration patterns.

Capabilities

• •GPS grid cell tracking (typically 100m x 100m cells)
• •Color gradient showing recency of exploration
• •Total area coverage calculation (square kilometers/miles)
• •Unique cell count and coverage percentage
• •Archetype classification: Explorer, Nomad, Tourist, or Routiner
• •Interactive map visualization with zoom and pan
• •Heat map overlay showing frequently covered areas

Use Cases

• →Urban exploration: Gamify discovering new streets and neighborhoods
• →Coverage goals: Set targets for geographic area coverage
• →Route variety: Identify over-used routes and unexplored areas
• →Travel documentation: Visual record of running in different cities
• →Running style analysis: Understand if you prefer familiar or new routes

Runner Archetypes

Overview

View your entire running year (or multiple years) at a glance with a GitHub-style contribution graph. Each day is represented as a colored cell, with intensity indicating training volume or activity count.

Capabilities

• •Year-long calendar grid visualization
• •Color intensity based on distance or activity count
• •Multi-year view for long-term pattern analysis
• •Streak identification (consecutive running days)
• •Rest period visualization
• •Training block recognition
• •Click-through to daily activity details

Use Cases

• →Consistency tracking: Visualize training regularity and gaps
• →Streak maintenance: Monitor and motivate daily/weekly running streaks
• →Training periodization: Identify build-up and taper periods
• →Injury/rest tracking: Clearly see forced breaks or planned recovery
• →Motivation: Maintain visual proof of consistent training