We begin with a review of some necessary statistical preliminaries. Assume that the random event under consideration can be modeled as independent Bernoulli trials. Now, if all this talk of infinite trials seems silly to you, well, you are right - clearly there is not much useful about statements like this. Fortunately, you can say something about how quickly the results will approach the 'right' answer. A quantity know as the variance gives you an idea of how close you can expect to get to the average given n trials.
Variance is a really useful measure because of something know as the Central Limit Theorem.
This is handy because lots of statistically important stuff is known about Gaussian RVs. Now we need to make a small refinement. Since we are interested in WP and not the gross number of wins, we can define our RV to be the proportion of wins observed in n games. This gives us a handy yardstick with which to assess performance data. Well, we can form an answer by assuming that the observed data gives an accurate picture of the team's abilities, and then see if 0.500 is distant in a statistical sense from the observed performance.