WAR/Regression Question

[Bravos of Steel]

Hey guys,

I'm doing my senior comprehensive project on team dominance in the MLB Free Agent Market, and I'm analyzing the WAR statistic to find out if teams actually use specific knowledge management tactics to gain an advantage. I just ran a regression, wanting to find out if a player's contract is a function of his WAR value. Basically, just looked at all the type A and B FAs of the last 4 years, how much each team spent in total during free agency, and the player WAR values. I need some help with an interpretation. This is what I got:

Multiple R = 0.899
R Square = .808
Adjusted R Square = .8015
Standard Error = 43.2
Observations = 30 (teams)

Intercept = -34.8325
Wins Above Replacement (Before being Signed) = 13.3791

I believe these are the variables that matter the most. I'm having a really tough time interpreting this. Any math/statistical whizzes out there that can help me out with this? Thanks!

[kab21]

I slept thru all of my stats classes. Actually all of my math classes. Wait, actually all of my classes so I'm not going to help you with stats. But I wondering about one of your inputs.

Did you use multi-year WAR values? WAR fluctuates wildly since offensive stats don't eliminate luck like FIP for pitchers do. And defensive stats usually need multiple seasons to be relevant.