I have performed a logistic regression with whether or not an athlete was re-contracted by their sports team as the DV. One of the significant predictors of the final model was draft order (OR 0.888).
Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -120.69457 46.78377 -2.580 0.009885 ** Debut.first.year 0.67977 0.21772 3.122 0.001795 ** Grouped.by.fives -0.11849 0.02361 -5.019 5.21e-07 *** Draft.year 0.06109 0.02334 2.617 0.008863 ** Maturity -0.65844 0.40981 -1.607 0.108118 Games.second.season.DC 1.87716 0.34011 5.519 3.40e-08 *** Interstate.vic.team 0.47625 0.19390 2.456 0.014044 * Rising.star 1.50635 0.44429 3.390 0.000698 *** Team.EOS.ladder.second.year.raw -0.04403 0.02062 -2.135 0.032728 *
I understand that this indicates that being selected later in the draft results in a reduced odds of being re-contracted. There are 8 predictors overall therefore my question is, does this indicate that being selected later in the draft results in a reduced odds of being re-contracted when all other predictors are held constant? Does this then mean that draft order is associated with being re-contracted irrespective of rising star nomination, maturity, draft year etc?
The text books I have read and online forums are quite vague and I am struggling to understand the relationship between the regression coefficients.