The hardest hikes in Germany, by the numbers
Of the 184 trails in Germany in our dataset, 37 (20 percent) rate strenuous or very strenuous on the gain-and-distance scale we use and run 3 to 30 miles with at least 1,500 ft of climb; these are the 25 with the highest rating.
Europäischer Fernwanderweg E4 - Teil Deutschland (Region Tegernsee) leads with 6,266 ft of gain over 23.4 miles, 268 ft per mile, with a steepest pitch of 41 percent.
Across the 25, gain runs from 1,620 to 6,416 ft and distance from 7.2 miles to 28.9 miles; the median gain is 3,500 ft and the median distance 22 miles.
21 of the 25 are out-and-back routes; the rest are point-to-point (4).
![Westweg [07. Hausach→Wilhelmshöhe] topographic trail print](https://cdn.outposters.com/previews/westweg-07-hausach-wilhelmshohe.jpg?v=1f3faca3)
![Westweg [02. Dobel→Forbach] topographic trail print](https://cdn.outposters.com/previews/westweg-02-dobel-forbach.jpg?v=1f3faca3)
How this list is ranked
Rating = the square root of 2 x elevation gain (ft) x distance (miles), the gain-and-distance formula Shenandoah National Park publishes for its own trails. Bands: under 50 easiest, 50 to 100 moderate, 100 to 150 moderately strenuous, 150 to 200 strenuous, 200 and over very strenuous.
This list: band strenuous (150 to 200) or very strenuous (200 and over), 3 to 30 miles, at least 1,500 ft of gain, ordered by rating desc, gain per mile desc, capped at 25. The rating column is computed from the miles and gain printed in the same row, the numbers each trail page uses, so every row can be checked from the row itself. The rating says nothing about exposure, scrambling, altitude or conditions.
Only trails with a full page count, so "Germany" here means the 184 trails in Germany in our dataset, not every trail in Germany.
Each trail page shows the full elevation profile behind these numbers and the same data drawn as a topographic print, made to order. Start with Europäischer Fernwanderweg E4 - Teil Deutschland (Region Tegernsee).
Hardest hikes elsewhere.
The same ranking for other countries in our dataset.