The data collected in support of a baseless hypothesis might be good, but since it has been collected based on a preconceived notion of its role in the hypothesis, it is meaningless.
"I think men like playing first person shooter video games because of their hunter gatherer tendencies. Let me conduct an experiment to see if I can indicate this to be true. Yup, there's an association between the two variables. Men play more first person shooter video games than other types of games, and they play these more than women do. These games simulate hunting, and in the past men hunted more than women. Therefore, my hypothesis is supported."
Of course, the only reason this supports your hypothesis is because you made up the conclusion to begin with. The data might be sound, and the association might be real (and due to any number of other factors), but the inference is false, because you're merely fitting the data into a preconceived role or conclusion in your mind, and in your silly hypothesis. You've decided your conclusion in advance, and then you're letting your results justify your conclusion, even though they might indicate any number of other things that haven't been hypothesised yet.
"If A exists, then so must B. I found A, therefore B exists."
Unfortunately, the former is an assumption. Therefore, the implication in the latter is not always true. Bad researchers don't get this.