Election 2020

[pbrower2a]

At this point I can defer to the expert, Nate Silver, from whom  I adapted my model. He has more data from which to derive his model, and has the means of compiling a composite of polling data that I cannot do because of a lack of computing power and software for such. 

Here is my model:


My estimates for the results for intermediate probabilities based on near-linear differentials  for three and two months out for a Senate campaign, which I see as a good analogue for a statewide campaign for a State's electoral votes:. 
 
Time to election  |1 point|5 points||10 points|20 points| 
one day............. |...64%|....95%|.....99.7%|.99.999%| 
one week........... |...60%|....89%|.......98%|...99.97%| 
one month......... |...57%|....81%|.......95%|.....99.7%|
three months......|...55%|....72%|........87%|......98%|
six months..........|...53%|....66%|.......79%|.......93%|
one year.............|....52%|...59%|.......67%|.......81%|


lead  likelihood, three months and two months 

0   50    50  10  87  91
1   55    56  11  88  92
2   59    64  12  89  93
3   64    69  13  90  94
4   69    73  14  91  95
5   72    77  15  92  96
6   76    78  16  93  97
7   80    80  17  94   97
8   83    84  18  95  97
9   85    87  19  96  97

Note that the probability that a leader wins more precipitously at 5% (9% delta) than at 1 (2% delta), so the increase from my estimate at three months cannot be linear in the range between a 1% and a 5% lead.  
. 





Numbers likely to be ill-seen:

CT 99
DE 99+
DC (don't be stupid) 
MD 99+
ME-AL 83
ME-01 96
ME-02 42
NE-AL 1
NE-01 7
NE-02 62
NE-03 0
NH 73
RI 98


Biden 0-4% saturation 8
Biden 5-20% saturation 6
Biden 21-35% saturation 5
Biden 36-40% saturation 4
Biden 41-49% saturation 2

50/50 white

Biden 51-60% saturation 2
Biden 61-70% saturation 4
Biden 71-80% saturation 5
Biden 81-95% saturation 6
Biden 95%+ saturation 8

I intend to close this thread on September 21, when reality will be closer to one month before the election (in which things really get tougher for someone behind).