Improving my Turnout Model - Latest Predictions

Previously I was relying upon Obama presidential 2008 vote to be solely predictive of turnout. However I've now created a turnout model for primaries with additional variables.

When I apply this to my predicted Sanders vote percentages (county-level), I get some small to medium sized changes in my predictions. Old values in parentheses.

Sanders Predicted Vote Share:
CT: 45.2% (45.3)
DE: 39.6% (35.5) <--- biggest change
IN: 53.4% - no change
KY: 44.3% (44.0)
MD: 27.6% (28.1)
NY: 33.1% (33.9)
OR: 71.8% (71.7)
PA: 42.7% (42.5)
RI: 50.6% (48.2) <--- second biggest change and it changes who wins
WI: 61.7% (61.5)
WV: 53.2% (52.5)

I'm not including the impact of whether the primaries are open or closed (the semi-open and semi-closed ones make it difficult due to a lack of sample size).

Most of my turnout model is the total percent of FB likes for both Clinton and Sanders (positive - and the most critical variable), percent Hispanic (negative), Gore 2000(positive), Obama 2008 (positive), Google searches for Clinton (positive), Google Searches for Sanders (negative), and women aged 45 to 64 (positive).