Sponsored search advertisement slots are currently sold via Generalized Second Price (GSP) auctions. Despite the simplicity of their rules, these auctions are far from being fully understood. Our observations on real ad-auction data show that advertisers usually enter many distinct auctions with different opponents and with varying parameters. We describe some of our findings from these observations and propose a simple probabilistic model taking them into account. This model can be used to predict the number of clicks received by the advertisers and the total price they can expect to pay depending on their bid, or even to estimate the players valuations, all at a very low computational cost.