Netron vs Statistics for Strava
| Tagline | Interactive visualizer for neural network and machine learning model graphs | Self-hosted statistics dashboard for your personal Strava activity data |
| Category | Product & Web Analytics | Product & Web Analytics |
| Replaces | Google Analytics, Mixpanel, Amplitude | Google Analytics, Hotjar |
| GitHub stars | 33k | 1.8k |
| Language | Python | Docker |
| License | MIT | AGPL-3.0 |
| Self-host difficulty | 1/5 Effortless | 3/5 Moderate |
| Deploy options | Manual | Docker Docker Compose |
| Managed hosting | ||
| Last updated | yesterday | yesterday |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Netron
- Purely a model visualization tool; no runtime analytics, dashboards, or event tracking
- Does not replace web or product analytics SaaS in any meaningful way
- No team collaboration or sharing features beyond exporting images
- No support for real-time or streaming model inference monitoring
Statistics for Strava
- Limited to Strava as a data source; no support for Garmin, Wahoo, or other fitness platforms
- Read-only analytics — no goal setting, training plans, or social features
- No mobile app; dashboard is web-only
- Requires a valid Strava API OAuth application to be configured before first run
Bottom line
Choose Netron if you want the lower-effort setup; choose Netron for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.
Netron
Interactive visualizer for neural network and machine learning model graphs
Statistics for Strava
Self-hosted statistics dashboard for your personal Strava activity data