We then ordered the list, putting the highest scoring first. We then add up the total number of points and divide it by the number of helmets tested over the last few years to find the average (mean). Where it scored one star we've given it 1 point. Where a helmet was awarded five stars, we've given it 5 points. So, we reckon it's about as good information as is available and that's what we're basing this analysis on. Yes, agreed, it might not fully simulate the accident where you hit diesel while hanging off your Z1000 and bash your helmet on a curbstone at a 15 degree angle then scrail it down the road for 100 yards, but it does subject the helmet to impacts from multiple sides and show which individual helmets - all things being equal - perform best. Whatever your point of view, what is going for the SHARP testing regime is that it's held under controlled circumstances in a laboratory so each helmet should be subject to an identical test - meaning it's possible to compare the results of each test on each helmet. However, we think it's about as good as it gets - you can read what the test entails here and an analysis of SHARP data here and make your own mind up if you like. It's worth pointing out that there are some detractors of the SHARP test too, reckoning that it's not real world enough. So because of this, where there's only a handful of helmets available to score, we've usually removed the brand from the survey.Īnd of course, SHARP only tests ECE helmets bought in the UK, which may be different from helmets found in DOT or other areas. Why? Well, imagine one brand has 10 helmets tested with an average score of 3 stars, they could be below a brand with just one helmet scoring 4. If a brand's helmets haven't been chosen for testing, then they simply won't appear in our table.Īs alluded to above, to avoid sample size skewing, we've excluded some brands where a brand hasn't had a reasonable tested sample size. Our main drawback is the limited number of helmets tested for some brands which will slant the figures - SHARP choose and buy the helmets themselves, so that's bound to skew the figures. We've tended to focus on the main brands - meaning brands that are more widely known and which helmet buyers will want to know about and be able to find in motorbike shops. Or maybe they've so little distribution, that we've chosen to leave a brand out.
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GitHub - An圜hart/An圜hart-Android: An圜hart Android Chart is an amazing data visualization library for easily creating interactive charts in Android apps. It runs on API 19+ (Android 4.4) and features dozens of built-in chart types. Maybe they've not been tested enough to give a reasonably reliable amount of data - or maybe they've not been tested at all. An圜hart Android Chart is an amazing data visualization library for easily creating interactive charts in Android apps.
And we've not included every helmet brand in the list. This table relies on SHARP crash helmet testing data only (covering 2016 to 2023) so it's never going to be fully comprehensive. Any chart/study like this has it's drawbacks of course, but hopefully it's a pretty good snapshot of how safe some of the main helmet brands will perform in an accident, relative to each other.
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