Overview
Rate Limiting and JavaScript both elevate Sporting Goods's active barrier profile
| Value | |
|---|---|
| WAF | 89% |
| Antibot | 26% |
| CAPTCHA | 24% |
| JavaScript | 41% |
| Rate Limiting | 49% |
| TLS | 32% |
WAF leads at 89%. Rate Limiting (49%) and JavaScript (41%) together form a multi-layer active stack — more than most sectors deploy alongside WAF.
Barrier Landscape
Rate Limiting is Sporting Goods's dominant secondary barrier by a wide margin
| Value | |
|---|---|
| WAF | 89% |
| Antibot | 26% |
| CAPTCHA | 24% |
| JavaScript | 41% |
| Rate Limiting | 49% |
| TLS | 32% |
| Has robots.txt | 78% |
| Blocks AI crawlers | 7% |
WAF at 89% and Rate Limiting at 49% together form the sector's main defensive layer. JavaScript (41%) follows at a distance. The barrier profile is concentrated rather than broadly spread.
Heavy barrier stacking is common in Sporting Goods — most sites carry three or more
| % of sites | |
|---|---|
| 0 barriers | 5% |
| 1 barrier | 23% |
| 2 barriers | 20% |
| 3 barriers | 30% |
| 4 barriers | 7% |
| 5 barriers | 10% |
| 6 barriers | 5% |
52% of Sporting Goods sites carry three or more barriers — well above the norm. Three-barrier stacks are most common. Just 5% of sites carry none.
Sporting Goods is among the hardest sectors to access programmatically
| Mean recommended tier | |
|---|---|
| All sites | 2.50 |
A mean recommended tier of 2.50 and a median of Easy place Sporting Goods toward the harder end of the sectors surveyed. 15% of sites are Simple to access; 43% require Moderate or above.
Easy is the most common access tier across Sporting Goods sites
| % of sites | |
|---|---|
| 1 - Simple | 15.3% |
| 2 - Easy | 41.8% |
| 3 - Moderate | 25.5% |
| 4 - Complex | 12.2% |
| 5 - Advanced | 5.1% |
Easy (42%) is the most common tier. Simple and Easy together account for 57% of sites, while 26% land at Moderate and 17% at Complex or Advanced.
robots.txt
Nearly four in five of Sporting Goods sites publish a robots.txt
| % of sites | |
|---|---|
| Publish a valid robots.txt | 78% |
78% of Sporting Goods sites have a valid robots.txt. The remaining 22% leave crawl policy entirely undefined — a meaningful gap for a sector of this scale.
Sporting Goods sites name a handful of agents in robots.txt — few commit to comprehensive policies
| % of sites | |
|---|---|
| 0 | 26% |
| 1 | 41% |
| 2–4 | 15% |
| 5–9 | 9% |
| 10–15 | 2% |
| 16+ | 7% |
The mean of 5.9 named agents reflects limited bot-policy investment in Sporting Goods. 26% of sites name no agents; 41% name exactly one. Only 7% maintain a list of 16 or more named bots.
SEO crawlers draw the most robots.txt attention in Sporting Goods
| % of sites | |
|---|---|
| AI crawlers | 10% |
| SEO / search indexing | 18% |
| SEO audit tools | 12% |
| Commercial scrapers | 2% |
| Social / content scrapers | 3% |
| Archive / research crawlers | 6% |
| Monitoring / uptime bots | 0% |
SEO / search indexing bots are mentioned by 18% of Sporting Goods sites. AI crawlers follow at 10%. All figures are percentages of all 100 Sporting Goods sites surveyed.
Path-level mixed rules dominate Sporting Goods robots.txt posture
| % of sites | |
|---|---|
| Uniform per-agent rules | 37% |
| Path-level mixed rules | 39% |
| Allow-only (no Disallow rules) | 0% |
| Mixed AI posture | 3% |
| Blanket Disallow: / | 0% |
Path-level mixed rules lead at 39%, with uniform per-agent rules at 37%. Mixed AI posture reaches 3%.
Baiduspider leads named Disallow rules in Sporting Goods robots.txt
| Disallowed | Allowed (whitelisted) | |
|---|---|---|
| * | 73% | 37% |
| Baiduspider | 13% | 1% |
| GPTBot | 6% | 2% |
| CCBot | 6% | — |
| ChatGPT-User | 3% | 3% |
| OAI-SearchBot | 3% | 3% |
| AhrefsBot | 6% | — |
| MJ12bot | 6% | — |
| HTTrack | 5% | — |
| Gigabot | 5% | — |
| Googlebot | 1% | 4% |
| PerplexityBot | 2% | 3% |
| BLEXBot | 4% | — |
| Ezooms | 4% | — |
| TurnitinBot | 4% | — |
| Offline Explorer | 4% | — |
| WebCopier | 4% | — |
| Google-Extended | 1% | 3% |
| YouBot | 2% | 2% |
| AdsBot-Google | 1% | 2% |
| facebookexternalhit | 2% | 1% |
| PetalBot | 3% | — |
| Pinterestbot | 2% | 1% |
| Exabot | 3% | — |
| YandexBot | 3% | — |
Values are percentages of all 100 Sporting Goods sites surveyed. The wildcard (*) leads at 73% Disallow. Among named agents, Baiduspider leads at 13%. GPTBot, CCBot, AhrefsBot, and MJ12bot follow at 6% each.
Industry Cohort
Sporting Goods sits mid-table within the Retail & E-commerce cohort
| WAF | Antibot | CAPTCHA | JavaScript | Rate Limit | TLS | robots.txt | Blocks AI | Tier | |
|---|---|---|---|---|---|---|---|---|---|
| Apparel & Fashion | 91% | 21% | 15% | 49% | 54% | 32% | 69% | 4% | Tier 3 |
| Beauty & Cosmetics | 91% | 30% | 36% | 40% | 31% | 30% | 76% | 13% | Tier 2 |
| Computer & Video Games | 94% | 27% | 26% | 44% | 22% | 13% | 81% | 23% | Tier 1 |
| Computer Hardware | 93% | 30% | 20% | 42% | 33% | 15% | 73% | 13% | Tier 2 |
| Computers & Electronics | 86% | 13% | 17% | 34% | 18% | 15% | 73% | 9% | Tier 2 |
| Consumer Electronics | 92% | 27% | 27% | 46% | 29% | 20% | 83% | 9% | Tier 2 |
| Equipment & Supplies | 96% | 27% | 31% | 41% | 26% | 14% | 68% | 8% | Tier 2 |
| Food & Beverages | 92% | 24% | 26% | 51% | 31% | 11% | 68% | 23% | Tier 2 |
| Furniture | 97% | 33% | 28% | 49% | 40% | 21% | 67% | 5% | Tier 2 |
| Jewelry & Luxury | 83% | 28% | 23% | 41% | 42% | 34% | 80% | 9% | Tier 2 |
| Packaging & Containers | 95% | 18% | 35% | 42% | 17% | 11% | 80% | 6% | Tier 1 |
| Retail | 96% | 19% | 15% | 51% | 33% | 20% | 85% | 29% | Tier 2 |
| Sporting Goods | 89% | 26% | 24% | 41% | 49% | 32% | 78% | 7% | Tier 2 |
| Sports | 98% | 11% | 15% | 61% | 23% | 11% | 89% | 33% | Tier 1 |
| Textiles & Nonwovens | 92% | 6% | 38% | 35% | 17% | 14% | 78% | 7% | Tier 1 |
| Tobacco | 98% | 30% | 52% | 38% | 30% | 15% | 76% | 3% | Tier 1 |
| Wholesalers & Liquidators | 94% | 24% | 22% | 44% | 30% | 13% | 80% | 7% | Tier 2 |
| Wine & Spirits | 95% | 24% | 28% | 47% | 32% | 15% | 84% | 14% | Tier 1 |
Across Retail & E-commerce, Sporting Goods's barrier rates are broadly in line with peers. WAF at 89%, JavaScript at 41%, and AI blocking at 7% all sit near the cohort median. Tier difficulty (mean 2.37) is above the group average.