Shill bidding occurs when fake bids are introduced into an auction on the seller’s behalf in to artificially inflate the final price. The seller either has associates bid in the seller’s auctions, or the seller controls multiple fake bidder accounts that are used for shill bidding. We proposed a reputation system referred to as the Shill Score that indicates how likely a bidder is to be engaging in price inflating behaviour in a specific seller’s auctions. A potential bidder can observe the other bidders’ Shill Scores, and if they are high, the bidder can elect not to participate as there is some evidence that shill bidding occurs in the seller’s auctions. However, if a seller is in collusion with other sellers, or controls multiple seller accounts, the seller can spread the risk between the various sellers and can reduce suspicion on the shill bidder. Collusive seller behaviour impacts one of the characteristics of shill bidding the Shill Score examines; consequently, collusive behaviour can reduce a bidder’s Shill Score. This paper extends the Shill Score to detect shill bidding where multiple sellers are working in collusion with each other. We propose the first algorithm to provide evidence of whether groups of sellers are colluding. Based on how tight the association is between the sellers and the level of apparent shill bidding that is occurring in the auctions, a suspect bidder’s Shill Score is adjusted appropriately to remove any advantage from seller collusion. Performance is demonstrated using simulated and commercial auction data and extensive experimental results are presented.