A regression model $Y = a + b_0 X_0 + b_1 X_1$ (the slightly awkward and non-standard notation matches your predictor names) plots as $a + b_0 X_0$ for $X_1 = 0$ and $a + b_0 X_0 + b_1$ for $X_1 =  1$, i.e. two parallel lines in $X_0, Y$ space. Here you can see a tilt in the main cluster of points which does not match the regression especially well, but you can also see that data points in the NE and E corners of each plot exert leverage pulling up the regression surface. 

[![enter image description here][1]][1]

Although not shown here, a quadratic in $X_0$ does not seem to offer worthwhile improvement. 

The narrow range of the outcome from about 0.48 to 0.55 seems unusual, at least until the OP offers some kind of explanation. 


  [1]: https://i.sstatic.net/7Jhnm.png