@kingofhell99,
@starburst98—
The first number is an attempt at Bayesian averaging; the second is the ordinary average of individual scores.
A Bayesian rating starts with what is called a “prior mean” or just “prior”, and a weighting; it is as if a bunch of folk have already scored the series. When the first actual scores are entered, they begin to count in the calculation; over time, the
relative significance of the prior and its weighting become ever smaller.
If the prior is reasonable, and if the weighting is appropriate, then a few yahoos don't cause a series to be scored unreasonably high or low. If the weighting is too low, then the prior has almost no effect; if the weighting is too high and the prior is unreasonable, then it takes forever for score to become close to representative.
Based upon my observations, I'd say that the prior is too high, and that the weighting is
much too great. I recommend
completely ignoring it except to the extent that you're interested in observing
bad statistical practice or can't see the raw mean. But I don't think that the raw mean will ever be a great measure of general opinion, both because of sample-selection bias and because people don't have commensurate senses of scale. And, even if we had a good sense of general opinion, it wouldn't tell you whether you would or should like the series.