Of course that's true. I tried to do something similar at one point last year and I found a decent r, but also found that most of the correlation was coming from runs scored in the first three innings (when the reading would be inherently most accurate.)
Again though, I was really spotty with doing it and kept no records, so I never got to actually look at whether incorporating or omitting specific data sets would improve my prediction or worsen it in the aggregate. For all I know, the days I used my hacky wind data were the days the wind was unpredictable in a statistically significant way. I'd have no way of regressing that. I would win after analyzing something new that I thought of and then keep doing it, but who knows how many wins came from random variance and how many came from an improved process (or at the expense of one) Thinking about it, it could even be advantageous for this format if the data does skew that way.
I'll be really curious to hear about your findings when you've run the numbers on this. Any chance I could see the r's for various stats vs. windspeed once you've made them?