Race 2 accuracy

aiv4r

@isaac.net I get that was just wondering if Suunto added artificial cut of distance for masses, that usually run more than actual race distance. (mostly road, since trail folks usually do not care that much about ±400meters).

Egika

said in Race 2 accuracy:

@isaac.net sorry, you are on the wrong track.
While probably everything might theoretically be solvable by software, I doubt that Suunto is going to invest a lot into this one. But who knows…

I have to stand corrected. Seems Suunto is indeed investing into this one

sky-runner

@CHRGBR said in Race 2 accuracy:

Hello,
I can confirm my R2 shows always a litte shorter distance than my Ambit 3 (about 1%). This is not a tragedy but a software fix would be appreciated

Comparing against Ambit 3 isn’t as straightforward as it may seem. For example, when running on deeply forested trails in my area Ambit 3 was always 3-5% shorter (less accurate) than modern Suunto watches.

Joaquin

Thanks for your feedback — it helps us improve with every update.
We hear you, and we act on it.

Your feedback is extremely valuable, and our team continues working on GPS accuracy improvements and optimization through future firmware updates

jjpaz

@Joaquin Thanks!!

dreamer_

@Joaquin this is excellent news. Thank you so much!!

Joaquin

@jjpaz @dreamer_ Interesting test

This test was performed on a very short and technical mountain loop under dense tree canopy.

Loop characteristics:
• Wheel measured distance: 497 m

• Total laps: 11
• Expected real distance: 5.467 km
• Clockwise direction
• Dense forest coverage
• Repeated technical turns including one ~180° hairpin and two additional closed turns
The loop contains:
• Curve 1 → ~180° hairpin
• Curve 2 → ~90° closed turn
• Curve 3 → ~85° closed turn

These repeated direction changes make this route extremely demanding for GNSS filtering and track reconstruction.

One important detail:
all watches were worn in different wrist positions, so small variations are completely normal. Watches placed slightly higher on the arm usually record slightly more distance due to arm swing and antenna orientation.

Results:

• COROS Apex 4 → 5.37 km (-1.8%)
• Suunto Race 2 → 5.36 km (-2.0%)
• Suunto Vertical 2 → 5.33 km (-2.5%)
• Garmin 970 → 5.30 km (-3.1%)
• Amazfit T-Rex Pro 3 → 5.14 km (-6.0%)

A very interesting detail appeared when comparing GNSS raw distance vs filtered activity distance.

This is where you can clearly see the work of each brand’s algorithms trying to reconstruct the “real” trajectory under dense canopy conditions.

GNSS Distance represents the raw satellite accumulation, while Distance is the final filtered value after each brand applies its own correction, smoothing and trajectory reconstruction algorithms.

The most impressive result here was the Suunto Vertical 2:
• 5.33 km GNSS Distance
• 5.33 km final Distance

An almost perfect match between raw GNSS data and filtered output, showing extremely confident trajectory processing in this test.

COROS and Suunto Race 2 also stayed very close between raw and filtered values, while Garmin showed a more aggressive correction approach:
• 5.44 km raw GNSS
• corrected down to 5.30 km final distance

With the exception of the Amazfit, the distance difference between the other four devices is completely normal considering the different wrist positions and the extremely difficult GNSS conditions during the test.

ENJOY!!!

isaac.net

@Joaquin Thank you very much for your testing efforts. Is the software version used the same one available to users?

On the other hand, it’s good that the watch performs well when making corrections under extreme conditions, but it would be important to focus on what’s being discussed in this thread, where the correction causes errors under ideal conditions, which I believe is the most common scenario for a Race 2 user, and where the result should be perfect after the corrections.

Joaquin

@isaac.net not, working on it of course, we must do more and more Tets but looks promising

jjpaz

@Joaquin said in Race 2 accuracy:

@jjpaz @dreamer_ Interesting test

This test was performed on a very short and technical mountain loop under dense tree canopy.

Loop characteristics:
• Wheel measured distance: 497 m

• Total laps: 11
• Expected real distance: 5.467 km
• Clockwise direction
• Dense forest coverage
• Repeated technical turns including one ~180° hairpin and two additional closed turns
The loop contains:
• Curve 1 → ~180° hairpin
• Curve 2 → ~90° closed turn
• Curve 3 → ~85° closed turn

These repeated direction changes make this route extremely demanding for GNSS filtering and track reconstruction.

One important detail:
all watches were worn in different wrist positions, so small variations are completely normal. Watches placed slightly higher on the arm usually record slightly more distance due to arm swing and antenna orientation.

Results:

• COROS Apex 4 → 5.37 km (-1.8%)
• Suunto Race 2 → 5.36 km (-2.0%)
• Suunto Vertical 2 → 5.33 km (-2.5%)
• Garmin 970 → 5.30 km (-3.1%)
• Amazfit T-Rex Pro 3 → 5.14 km (-6.0%)

A very interesting detail appeared when comparing GNSS raw distance vs filtered activity distance.

This is where you can clearly see the work of each brand’s algorithms trying to reconstruct the “real” trajectory under dense canopy conditions.

GNSS Distance represents the raw satellite accumulation, while Distance is the final filtered value after each brand applies its own correction, smoothing and trajectory reconstruction algorithms.

The most impressive result here was the Suunto Vertical 2:
• 5.33 km GNSS Distance
• 5.33 km final Distance

An almost perfect match between raw GNSS data and filtered output, showing extremely confident trajectory processing in this test.

COROS and Suunto Race 2 also stayed very close between raw and filtered values, while Garmin showed a more aggressive correction approach:
• 5.44 km raw GNSS
• corrected down to 5.30 km final distance

With the exception of the Amazfit, the distance difference between the other four devices is completely normal considering the different wrist positions and the extremely difficult GNSS conditions during the test.

ENJOY!!!

@Joaquin Impressive work! Thanks!

isaac.net

@Joaquin great, thank you so much!

dreamer_

I can’t confirm the Race 2 now but I’m posting this because I can confirm the Vertical 2 in the track I was talking here:

https://forum.suunto.com/topic/15071/several-navigation-issues-feedback/39

alt text

All watches in exactly the very same wrist position, but different days. It’s pretty interesting to see how I’m having so similar distances considering I’m running in different days. But in the other hand, it’s a track I know really well. There’s road but trail with several tree zones with dense forest.

Joaquin

@dreamer_ similar distance all good

Keep in mind that my test isn’t a standard route test; it’s a course specifically designed to check trajectory/distance in challenging situations. No one will run around a loop like a hamster in real life However, it’s very useful because we can have similar sections on our routes, and this gives us enough information to know if our watches will handle them with sufficient accuracy. Obviously, this is visible in a test like this, but in real-world route tests, it might seem like all the watches perform similarly, even if one fails on a 40-meter section. But when you put it through this rigorous testing, you see exactly what’s good and what’s bad.

dreamer_

@Joaquin yes, it’s just the Vertical 2 is giving exactly the same result (and 2 times) as the Fenix 8 in my track. While the others, have slightly differences even in this track.

Thank you so much for this!! Really interesting, and very nice work

chus1962

@Joaquin Wow, great work!

Just out of curiosity, how did you get the GNSS distance?

Any program that processes a GPX file will do some kind of filtering to calculate the distance, and it will give a lower value than if I simply take the GPX points, calculate the distance between them, and add them up (which is what I understand to be the actual raw distance).

Joaquin

@dreamer_ thank you for your feedback and help ️‍

Joaquin

@chus1962 internal tools but is not the important here Users will only see the total distance processed, so it is only useful for internal engineering and software analysis.