A good explanation of correlation coefficients can be found here.
Essentially, the coefficient is any number between 0 and 1. The nearer the number is to 1 the better the correlation. 0 means an absence of correlation; 1 a perfect correlation. Anything above 0.5 is meaningful; anything around 0.75 is El Dorado.
Standard deviation essentially measures how far different points are from their mean average. A decent explanation is here. For our purposes (post #10) standard deviation is being used to show the extent to which different tennis players are inconsistent in different tournaments. I used it to measure players’ progress through different rounds.
A low standard deviation (eg Dodig 0.8) means that a player generally reaches a similar stage of the tournament in each of the tournaments he enters; a high standard deviation (eg Gulbis 1.9) means that a player has in all likelihood regularly reached finals and been knocked out at the first round stage.