Shill bidding is a fraudulent in-auction strategy where a seller participates as a bidder in his own auctions. This is the first paper on shill bidding that is based on a data set which includes personal details. Along with bidding histories, I can prove that on the investigated platform 0.3% of all auctions were influence by obvious shill bidders. The majority of the proven shill bidders' behavior in this paper does not fulfill any of the shill bidder types' criteria discussed in the literature. I adopt two algorithms which aim to identify shill bidders based on public information. On average, these approaches assign a higher probability of being a shill bidder to the accounts of bidders who certainly shilled on auctions in my data set. However, a reliable identification of proven shill bidders and honest bidders is only possible to a limited extent.