The ability of using data from daily operations and transactions to understanding customer behavior can provide valuable information to sellers in the e-commerce industry. To recognize which factors may have influence on the sales outcome of functional products in the e-commerce industry, in this study we conduct research based on linear regression on three sport goods. The data we use are collected from company-T, a sport good provider on Amazon.com. According to previous literature and marketing reports, we propose five hypotheses regarding factors that may have impact on the sales outcome. Across all three products, we find two of our hypotheses are fully supported. In particular, the sales outcome is higher when more customers click on the product page, and sales quantity is lower in weekends than in weekdays. For the other three hypotheses, they are partially supported by part of the three products. First, the more reviews made by customers, the higher sales for some products but the opposite for the other. Second, the influence from the prices of similar products made by competitors are positive for some products but negative for the others. Lastly, our results suggest that the sales outcome tends to be better in weeks before holidays. Our findings may help e-commerce sellers determine their selling and marketing strategy.