https://www.covers.com/nfl/next-chicago-bears-stadium-odds ↗

The page presents a single sports-betting offer from Kalshi with an associated promo code and trade-initiation CTA, surfaced within a NewsArticle wrapper that includes organizational and contact metadata. Structured data covers article and publisher properties but omits all commerce schema types—Product, Offer, BuyAction, and Review entities are absent despite the vertical classification and the presence of a named offer and merchant link. Both citation-index bots successfully fetched the page and resolved it by explicit URL mention in downstream references. IA enrichment would render the Kalshi offer and associated trade action as discrete, machine-readable commerce entities, making the promo-code condition and merchant binding inferable by systems that parse structured commerce signals rather than relying on article text alone.

What humans see vs what AI extracts today vs with IA enrichment

The gap between these columns is the enrichment IA layers on top of the page for AI extractors. Edge-level blocking is a separate dimension — see the bot-accessibility section.

Human view

AI Bot Today — During Live Search

On the page

Brand

Kalshi

Offers detected (1)

• Use Promo Code COVERS

CTAs (1)

Trade on this market now with Kalshi

Outbound merchant URLs (1)

kalshi.com

In the JSON-LD layer

Types present (7)

ContactPoint, NewsArticle, Organization, Person, PostalAddress, ProfilePage, WebPage

Commerce types present

none

Commerce types missing

Product, Offer, AggregateOffer, BuyAction, Review, AggregateRating

The gap

Offers visible to humans1

Offers in machine-readable form0

Click-throughs wrapped as BuyAction0 of 1

AI bot — with IA enrichment

IA enrichment adds (derived from existing page content)

• + 1 Offer entities — one per detected offer
• + 1 Product entity (Kalshi)
• + 1 BuyAction nodes wrapping existing outbound link

Result for AI extractors

A bot fetching the URL pulls all 1 offer from JSON-LD in microseconds — no LLM inference, no prose parsing, no guessing at which discount applies.

View IA-rendered flattened HTML

Chicago Bears Stadium Odds: Illinois vs Indiana — Covers

View IA-generated JSON-LD @graph

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "NewsArticle",
      "headline": "Chicago Bears Stadium Odds: Illinois vs Indiana",
      "url": "https://www.covers.com/nfl/next-chicago-bears-stadium-odds",
      "publisher": {
        "@type": "Organization",
        "name": "Covers"
      }
    }
  ]
}
</script>

Bot accessibility

Render risk — what AI bots can actually parse

Schema audit

potentialAction — commerce paths

Affiliate footprint