PiwikDeviceDetector - overview

Here you find the details of this provider

We analyzed 6136 user agents
Group Percent Total Actions
Results found 99.02 %
6076 Not found
Browser found 90.91 %
5578 Detected names Not found
Engine found 82.69 %
5074 Detected names Not found
Operating system found 88.04 %
5402 Detected names Not found
Device detected 92.73 %
5690
Device model found 76.74 %
4709 Detected models
Device brand found 77.92 %
4781 Detected brands
Device type found 88.07 %
5404 Detected types
As mobile detected 74.59 %
4577
As bot detected 98.44 %
316 Not detected as bot
Bot name found 98.44 %
316
Bot type found 88.16 %
283

I'm done here

More informations

The primary goal of this project is simple. I wanted to know which user agent parser is the most accurate in each part - device detection, bot detection and so on...

The secondary goal is to provide a source for all user agent parsers to improve their detection based on this results.

You can also improve this further, by suggesting ideads at ThaDafinser/UserAgentParserComparison

The comparison is based on the abstraction by ThaDafinser/UserAgentParser
Comparison created 2015-11-20 13:30:55 | by ThaDafinser