Overview Leaderboard Methodology
Industry Report

GPS Running Watches

Durable sport-focused watches with built-in GPS and advanced metrics for runners and multisport athletes.

Brands tracked: 30
Brands analyzed: 30
Last updated: 2026-04-23
Model: OpenAI GPT-5
Prompts: 245
Total responses: 1,225
Top Brand Overall?
Garmin
96/100

Highest overall AI Visibility Score in this industry.

LBA Leader?
Apple
94

Highest score on the LBA metric in this industry.

Authority Leader?
Garmin
100

Highest score on the Authority metric in this industry.

TOM Leader?
Garmin
100

Highest score on the TOM metric in this industry.

Garmin is the default answer in AI responses for GPS Running Watches

Garmin and COROS together dominate AI responses for GPS Running Watches. Both brands consistently surface unprompted, with the model treating them as the default answers for most category queries. Brands outside the top two face a structural disadvantage: users are usually given these two before the model even considers alternatives.

Brand Leaderboard All 30 GPS Running Watches brands ranked

Ranked by overall AI Visibility Score (smoothed geometric mean of LBA, Authority, and TOM with an LBA-based floor on Authority and TOM, see methodology). Click any brand for the full report.

# Brand LBA Authority TOM Overall
1
Garmin
garmin.com
 88
100
100
96
2
COROS
coros.com
 78
98
93
89
3
Suunto
suunto.com
 72
42
64
58
4
Apple
apple.com
 94
23
80
57
5
Polar
polar.com
 84
30
69
57
6
Fitbit
fitbit.com
 83
8
8
20
7
Nike
nike.com
 79
8
8
19
8
Samsung
samsung.com
 75
7
10
19
9
adidas
adidas.com
 69
7
7
17
10
Amazfit
amazfit.com
 68
7
7
17
11
TomTom
tomtom.com
 71
7
7
17
12
G-Shock
gshock.com
 66
7
7
16
13
Timex
timex.com
 66
7
7
16
14
Wahoo
wahoofitness.com
 64
6
6
16
15
Huawei
huawei.com
 61
6
6
15
16
Xiaomi
xiaomi.com
 62
6
6
15
17
Sony
sony.com
 49
5
5
13
18
T
TicWatch
ticwatch.com
 52
5
5
13
19
Magellan
magellangps.com
 49
5
5
12
20
S
Sigma
sigma-sport.com
 48
5
5
12
21
Under Armour
underarmour.com
 45
5
5
12
22
HONOR
honor.com
 41
4
4
11
23
Kiprun
kiprun.com
 45
4
4
11
24
Mio
mioglobal.com
 44
4
4
11
25
OnePlus
oneplus.com
 44
4
4
11
26
B
Bryton
brytonsport.com
 32
3
3
9
27
New Balance
newbalance.com
 32
3
3
9
28
OPPO
oppo.com
 35
4
4
9
29
Epson
epson.com
 30
3
3
8
30
Soleus
soleusrunning.com
 28
3
3
8

How is this calculated? Methodology

Every brand in this leaderboard is scored against the same set of 245 shared GPS Running Watches prompts. The same prompts, same model, same iterations. So differences in scores reflect actual differences in AI visibility, not differences in measurement.

Overall AI Visibility Score
Smoothed geometric mean of LBA, Authority and TOM. Authority and TOM are floored at LBA × 0.1 before the geometric mean (the same floor used in the per-metric cards above, so brand cards and the composite tell the same story). Formula: composite = ((LBA + 5)(Authority + 5)(TOM + 5))^(1/3) - 5. The floor keeps brands the model clearly recognises but doesn't yet recommend from collapsing to zero, while a single genuinely weak metric still pulls the composite down. Full methodology.
Shared industry prompts
For Authority and TOM, all brands in the industry are scored against the same 245 category prompts (e.g. "best SEO tools for agencies"). This makes brand-to-brand comparisons valid - everyone faces identical inputs. LBA prompts are per-brand because they ask brand-specific questions.
Latent Brand Association (LBA)
5 brand probes + 1 control prompt, each run 5 times in recall mode (no web search). LBA = quality × meta × stability × share × recognition × 100. Read the full LBA methodology →
LLM Authority
50 organic category prompts (discovery, comparison, problem and transactional intents), each run once in recall mode and once in retrieval mode. Score = frequency × log-decayed prominence × intent weight, then 50/50 averaged across the two modes. Read the full Authority methodology →
Top of Mind (TOM)
15 high-volume discovery prompts (sourced from Keywords Everywhere search-volume data), each run 5 times in pure recall mode (no web). Score = frequency × (0.5 + 0.5 × log-prominence), volume-weighted. Read the full TOM methodology →