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This research attempts to contrast bid competitiveness with respect to the average bid auction (ABA) and the non-ABA bidding formats used by the Public Works Department (PWD) of Malaysia. The research uses the ordinary least square regression and the Monte-Carlo simulation to point out significant predictors which affect the bid ratio and fitting probability distributions to bidding data, respectively. This research shows that the bidding strategy adopted is dependent on the different formats used. In the ABA format, bidders are more likely to submit identical bid prices. In the non-ABA format, they bid according to the first-price auction (FPA) strategy, which suggests greater variation between bid prices as a winning strategy and the reduction in the bid price to an estimated price ratio when more bidders bid. In addition, bidders lose more money when the distance between the project location and a firm’s operational office is greater. Best-fit probability density functions follow a gamma distribution for the ABA format and a Weibull distribution for the non-ABA format. The location and number of bidders affect bidders’ strategy to win. A competitive bidding price depends on a number of bidders who enter the auction. It increases the intensity of competition and it reduces the purchasing cost. The number of bidders is important because the cost of bidding may become a sunk cost. The probability to win an auction depends on the expected number of bidders. This affects bidders' decisions on whether to bid or not to bid. The research uses several statistical analyses to examine the 195 bidding data collected from Public Works Department of Malaysia. It …