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2016 Election Model- 9 pre-election polls: 5 Non-MSM and 4 MSM pollsters

Richard Charnin
Aug, 4, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

The following are the basic steps used to estimate 2016 National True Vote shares.  The True Vote Model utilizes nine  pre-election polls.  Party-ID varies greatly among the polls. Therefore, Gallup’s dedicated voter affiliation (Party-ID) survey is used to adjust the national poll shares.

The 2016 Gallup national survey is used to approximate state Party-IDs by calculating the change from 2012 National Party-ID to 2016 Gallup Party-ID.  The projected state vote share is calculated by applying the average of the 9 national pre-election Party-ID poll shares to the 2016 state Party-ID. The electoral vote is then calculated. View the full set of calculations in this spreadsheet: https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1036175945

National True Vote Model: Basic Methodology

1) Compare MSM vs. non-MSM polls (Party-ID and vote shares).
2) Adjust pollsters Party-ID to Gallup voter affiliation
3) Allocate undecided voters.
4) View the effect of these adjustments to the pre-election vote shares.

  • MSM pollsters overweighted Democrats Party-ID and underweighted Independents compared to non-MSM pollsters. Clinton wins the polls by 45.8-43.6%, matching her 2.1% recorded vote margin.
  • 2 Apply Gallup voter affiliation survey of National Party-ID (40I-32D-28R)  to each of the nine polls, Trump is a 44.1-43.3% winner.
  • 3 Note: the polls did not allocate undecided voters (approximately 6%), which typically break 3-1 for the challenger. Trump was the de-facto challenger.
  • 4 Effect: Allocating  undecided voters (4.5% to Trump and 1.5% to Clinton) to the Gallup-adjusted vote shares, Trump is the winner by 48.6-44.8%.

Non-MSM………….Party-ID…………..Pre-election……….Gallup (40I-32D-28R)
Polls………………Ind Dem Rep…….. Clinton..Trump…..Clinton Trump
IBD………………..37% 34% 29%…….. 43%….45%……..41.9% 45.3%
Rasmussen……..32% 40% 28%………45%….43%……..40.6% 45.3%
Quinnipiac………26% 40% 34%………47%….40%……..44.7% 40.8%
Gravis……………27% 40% 33%………47%….45%……..43.6% 45.5%
USC/Dormsite… 30% 38% 32%………44%….47%……..41.7% 48.2%
Average………..30.4% 38.4% 31.2%…45.2%.44.0%…..42.5% 45.0%

MSM……………..Party-ID……………..Pre-election…….Gallup Adj
Polls…………….Ind Dem Rep………..Clinton Trump..Clinton Trump
Reuters…………16% 45% 38%………42% ….39%…….36.0% 36.8%
Fox News………19% 43% 38%………48%…..44%…….45.8% 43.9%
CNN……………..43% 31% 26%………49%……44%…..48.6% 44.4%
ABC ……………..29% 37% 29%………47%…..45%……46.8% 47.0%
Average………26.8% 39.0% 32.8%…46.5% 43.0%……44.3% 43.0%

Summary…………….Party-ID…………Pre-election……Gallup Adj
…………………Ind…..Dem….Rep……Clinton.Trump..Clinton Trump
9 polls……….28.8% 38.7% 31.9%…..45.8% 43.6%…..43.3% 44.1%
5 nonMSM….30.4% 38.4% 31.2%…..45.2% 44.0%….42.5% 45.0%
4 MSM………26.8% 39.0% 32.8%…..46.5% 43.0%……44.3% 43.0%

Allocating  undecided voters (4.5% to Trump and 1.5% to Clinton) to the Gallup-adjusted vote shares, Trump is the winner by 48.6-44.8%.

 
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Posted by on August 5, 2017 in 2016 election, True Vote Models

 

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Adjusted Pre-election polls in the True Vote Model indicate Trump won by 5 million votes

Richard Charnin
Aug.2, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

This analysis shows that although Clinton won the Recorded Vote by 48.3-46.2% (2.8 million votes), Trump won the True Vote.

Plausible adjustments made to nine pre-election polls in the True Vote Model are the core of the analysis. These polls had Clinton winning by 45.8-43.6% with 298-240 electoral votes: Ipsos/Reuters, IBD/Tipp, Rasmussen, Quinnipiac, Fox News, CNN, ABC, Gravis, LA Times.

Adjusting  Party-ID to the Gallup voter affiliation survey, Trump won by 43.4-43.1% with 306-232 Electoral votes. After allocating 75% of undecided voters to Trump, the de-facto challenger, the True Vote Model indicates that Trump won  by 48.2-44.5% (5.1 million votes) with 336 electoral votes . Historically, challengers won a solid majority (65-90%) of undecided voters when the incumbent was unpopular. Clinton and the Democrats were unpopular, especially after she stole the primary from Bernie Sanders.

View the Model
https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=1036175945

Model Results
Pre-election poll averages based on:
Party-ID: Clinton 45.8-43.6
Gallup voter affiliation: Trump 43.4-43.1

Forecast Model (post-UVA)
Party-ID (9 Pre-election poll average):  Clinton 46.7-46.2
Gallup Party-ID: Trump 48.2-44.5

Trump Electoral votes: Pre and post UVA
Snapshot EV: pre-UVA: 306 (exact forecast); post-UVA EV: 336

Expected EV based on state win probabilities
Pre UVA: 289; post UVA: 351

Method
Calculate the average of 9 final pre-election polls (Party-ID and vote shares).
Calculate National Vote shares using Party-ID from

  • 9-poll average: 28.9I-38.7D-31.9R
  • Gallup voter affiliation survey: 40I-32D-28R

Gallup Voter Affiliation
1- Nov. 1-6: 36I, 31D, 27R (6 other)
2- Nov. 9-13: 40I, 30D, 27R (3 other)
Average (Election Day) : 38I, 30.5D, 27R (4.5 other)

Calculate State Vote shares
State Party-ID based on proportional change in National Party-ID from 2012 to 2016 Gallup survey applied to 2012 State Party-ID.
2012: 40.3D, 35.4R, 24.7I  
2016: 32D, 28R, 40I

Undecided voter allocation (UVA): 75% to Trump

Sensitivity Analysis
15 vote share/margin scenarios (pre-UVA) based on Trump % of Rep and Ind
Best Case: Trump 45.0-42.7
Base Case: Trump 43.4-43.1
Worst Case: Clinton 43.5-41.9

Electoral Vote Scenarios
Recorded EV = 306
Forecast  EV (pre-UVA) = 306
Forecast True EV (post-UVA) = 336
Difference between 306 EV and 336 EV due to MI (16) and NJ (14)

Expected EV
(based on state win probabilities post UVA)
EV = 351
Exp EV = sum [(P(i) * EV(i)], i= 1, 51
(P(i) = probability of winning state, EV(i) =  State Electoral vote
Margin of Error (MoE) = 2.5%

 
 

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Seth Rich/DNC Mortality Probability

Richard Charnin
Updated: 7/22/17

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

It’s not just about Seth Rich. Applied Mathematics indicates a virtual 100% probability of a cover-up.

Assume N=10,000 DNC/Wikileaks related individuals:
-There were 8 suspicious deaths (5 homicides) in 3 months from April 2016.
The probability of at least 5 homicides in 3 months is 1 in 6.5 million.
– There were 14 suspicious deaths (10 homicides) in 15 months since April 2016.
The probability of at least 10 homicides in 15 months is 1 in 814 million.
Assume N=30,000: The probability of at least 10 homicides is 1 in 41,730.

2016
4/18: John Jones, lawyer who defended Assange, run over by train.
May : Michael Ratner (Wikileaks NY lawyer), cancer.
6/22: John Ashe, ex-UN official, barbell fell on neck. He was going to testify on DNC and Clinton.
6/23: Mike Flynn,48, died day he reported on Clinton Foundation (unknown).
7/10: Seth Rich, DNC staffer, shot twice in back.
7/25: Joe Montano,47, DNC, heart attack day before the DNC convention.
8/01: Victor Thorn, gunshot wound, author of books on Clintons.
8/02: Shawn Lucas, DNC process server, lethal combination of drugs.
Oct : Gavin McFayden (Wikileaks founder), cancer.
Nov : Monica Petersen, investigator of Clinton Foundation, child trafficking, found dead in Haiti. Homicide?
2017
May : Peter Smith, GOP operative, found dead from asphyxiation in a Minnesota hotel room just days after talking to the Wall Street Journal about his efforts to obtain Hillary’s Clinton’s missing emails. Homicide?
May : Beranton Whisenant, prosecutor investigating DNC, found dead on Hollywood, FL beach. Homicide.
July: Klaus Eberwein, former Haiti Government official found dead in a motel room with a gunshot wound to the head. Was to testify on Clinton Foundation connection to Haitian earthquake charity. Homicide?
July 20: Joseph Rago,34, WSJ reporter/editor, asked Russians for info on Clinton, was Obama critic, found dead. Homicide?

How many DNC voter data admins were there? How many DNC process servers? How many HRC biographers? How many Assange lawyers? How many Wikileaks founders? How many UN officials preparing to testify? How many DNC officials? How many investigative reporters on the Clintons? Are any of these deaths being investigated? Any suspects?

What is the probability that in a random group of N individuals, n would die unnaturally in T years, given the group weighted average mortality rate R? The expected number of unnatural deaths is E = N*R*T.  The probability of n unnatural deaths is a function of  E and n: the larger the difference between E and n, the lower the probability.

The  Poisson distribution function calculates the probability of rare events. The probability of n homicides when E are expected is P = poisson (n,E,false).

You can run the spreadsheet calculator for any combination of N, n, R and T. https://docs.google.com/spreadsheets/d/1htajNqLQrV9M4jmwWUN7MweelfN2ZCwr8KB-YeO7r10/edit#gid=0

There were 7 suspicious DNC/Wikileaks deaths in 3 months:
n = 7
R = 0.0002 (DC homicide rate; 135 homicides/681170 pop.)
T = 3 months (0.25 Year).
N = relevant DNC/Wikileaks population.
E = N*R*T =N*0.0002*0.25 (expected number of homicides).

Assume N = 1,000 DNC/Wikileaks related  persons, then for
n=3 homicides: P= 1 in 52 thousand
n=4 homicides: P= 1 in 4.2 million
n=5 homicides: P= 1 in 422 million
n=6 homicides: P= 1 in 51 billion
n=7 homicides: P= 1 in 7.2 trillion

Assume: n=7, T= 0.25 (3 months), R=0.0002 and
N= 500, P = 1 in 902.1 trillion
N= 1,000, P = 1 in 7.2 trillion
N= 3,000, P = 1 in 3.6 billion
N= 10,000, P = 1 in 1.1 million

Since N is unknown, let’s view a SENSITIVITY ANALYSIS table over a range of N for n=5,6,7,8,9:

Probability of n homicides in a random group of
n 10,000 20,000 30,000 40,000
5 0.02% 0.31% 1.41% 3.61%
6 0.00% 0.05% 0.35% 1.20%
7 0.00% 0.01% 0.08% 0.34%
8 0.00% 0.00% 0.01% 0.09%
9 0.00% 0.00% 0.00% 0.02%

The analysis assumes the 7 DNC/Wikileaksdeaths were all homicides. If they were a combination of  homicides,  accidents,  suicides and heart attacks, we need to use a weighted mortality rate. This is conservative since “accidents” and “suicides” were likely homicides. The heart attack was also highly suspicious.

………………..National Weighted for T=.25 (3 months)
COD………. n Rate……… Rate
Accident.. 2 0.00038 0.00076
Suicide…. 1 0.00012 0.00012
Homicide. 3 0.00005 0.00015
Natural?.. 1 0.00173 0.00173 heart attack/cancer
Total…….7 0.00228 0.00039

For n=7, N= 1000, R = 0.00039, T = 0.25 (3 months)
Probability: P = 1 in 60 billion.

For n=5 homicides, N=1000, T= 0.27 (14 weeks), R = 0.00005
P = 1 in 275 billion

For n =7 (5 homicides, 2 heart attacks), N=1000, T= 0.25, R = 0.00052
P = 1 in 8 billion.

For n=9 (5 homicides, 2 heart attacks and 2 cancers):
R=0.0008, N=1000, T=0.5 (6 months)
P = 1 in 2.5 billion.

There were n=6 suspicious DNC/Wikileaks deaths in T=5 weeks (0.10 years). Mortality rate R=0.0002. Assuming a random group of N individuals, the probability that it was just a coincidence is
N Probability
500  1 in 900 trillion
1000 1 in 14 trillion
3000 1 in 20 billion
30000 1 in 32000

https://mpdc.dc.gov/page/district-crime-data-glance

Probability of 0-7 homicides in a random group of 40,000 over 3 months

No automatic alt text available.

No automatic alt text available.

JFK WITNESS DEATHS
In 1964-78, there were an estimated 1500 JFK-related material witnesses, of whom 122 died suspiciously. Seventy-eight(78) of the 122 were officially ruled unnatural. Of the 78, 34 were homicides, 24 accidents, 16 suicides and 4 unknown. The probability of 78 unnatural deaths: 2.7E-31 (1 in a million trillion trillion).

Just 12 accidents and 3 suicides were expected statistically, therefore approximately 60 of the 78 unnatural deaths were likely homicides.

Of the remaining 44 “natural” deaths (heart attacks, sudden cancers, other), approximately 25-30 were homicides based on the total number of expected deaths. Therefore, there were 85-90 homicides among the 122 suspicious deaths. For 10,000 witnesses, Probability: 5.5E-47

<https://richardcharnin.wordpress.com/2013/02/25/executive-action-jfk-witness-deaths-and-the-london-times-actuary/
https://docs.google.com/spreadsheets/d/1FmXudDf6pqisxq_mepIC6iuG47RkDskPDWzQ9L7Lykw/edit#gid=3

Simkin JFK Index of 656 key individuals: 44 homicides, Probability = 4.7 E-60 https://docs.google.com/spreadsheets/d/1FmXudDf6pqisxq_mepIC6iuG47RkDskPDWzQ9L7Lykw/edit#gid=81

 
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Posted by on May 20, 2017 in 2016 election, JFK, Uncategorized

 

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Election Justice USA: Evidence of Massive Election Fraud in the Primaries

Richard Charnin
April 29, 2017

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

An excellent article from “Project Censored 2017”. http://projectcensored.org/clintonistasdnc-illegally-stole-democratic-primaries-bernie-sanders/

On July 25th, 2016, Election Justice USA (EJUSA) released a hundred-page report compiling evidence of massive election fraud during the 2016 Democratic primaries. Election Justice USA is a non-partisan organization that consists of attorneys, technologists, journalists, statisticians, and activists.

Essentially, EJUSA concludes that Bernie Sanders may have lost an upper estimate of 184 pledged delegates due to specific irregularities and instances of fraud. Their conclusions? The combination of voter suppression, registration tampering, voter purging, and the manipulation of computerized voting machines, likely cost Bernie Sanders the election.
….
Additionally, Election Justice USA found that the computer counts differed widely from the exit poll projections, but only for the Democratic Party primaries. According to election analyst Richard Charnin, Bernie Sanders’ exit poll share exceeded his recorded vote share by greater than the margin of error in 11 of 26 primaries: Alabama, Arizona, Georgia, Massachusetts, New York, Ohio, Mississippi, South Carolina, Texas, Wisconsin, and West Virginia.

Charnin reported that the probability of this occurring is 1 in 77 billion, which raises the strong possibility of election fraud. Yet, almost no discrepancies were found in the data for the Republican Party primaries. This is particularly remarkable, because the exit polls were conducted on the same day, in the same precincts, with the same interviewers, and used the same methodologies for both the parties. So, this evidence suggests that the computer counts were only accurate for the Republican Party, while the computer counts for the Democratic Party primaries remain largely unverified.

more….

 

 
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Posted by on April 29, 2017 in 2016 election

 

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MY COMMENTS TO THE MSM ON THE RIGGING OF THE 2016 PRE-ELECTION POLLS

The MSM just interviewed the authors of  Shattered: Inside Hillary Clinton’s Doomed Campaign on the reasons for Clinton’s loss.  I commented to Chris Mathews and Brian Williams of MSNBC as well as FOX and CBS on how MSM pollsters rigged the pre-election polls for Clinton.

FYI: Your guests may not have looked at my 2016 Election model. It was based adjustments to final pre-election polls which were biased for Clinton. The Democratic Party-ID share was overstated at the expense of Independents who went solidly for Trump. In addition, there is strong evidence that votes were stolen from Jill Stein – by Clinton.

The 2016 Model projected Trump’s 306 RECORDED EV. But he actually had approximately 351 TRUE EV after adjusting for late undecided voters. https://richardcharnin.wordpress.com/2016/11/07/2016-election-model-forecast/

Recorded Vote: Clinton 48.3-46.2%, Trump 306-232 EV
Recorded Vote Forecast: Trump 44.4-42.9% with 306-232 EV
True Vote Model: Trump 48.5-44.3% with 351-187 EV

Note: I exactly forecast the RECORDED EV in the last three elections: 365, 332, 306. In each case the winner did better in the True Vote than the Recorded vote.

Here is the proof: https://richardcharnin.wordpress.com/2014/09/14/summary-2004-2012-election-forecast-1968-2012-true-vote-model/

 

 

 

 
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Posted by on April 24, 2017 in 2016 election

 

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SUMMARY VOTE SHARE/ ELECTORAL VOTE ANALYSIS

Richard Charnin
Dec.20, 2016

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

Clinton won the national popular vote by 2.8 million votes.  She won California by 4.27 million, New York by 1.7 million and Illinois by 945,000 votes – a total of 6.9 million.  Her margins in these states were implausible.  Trump won the other 48 states by 4.1 million.

The 28 unadjusted state exit polls are implausible. Trump won the True Vote. He won Independents by 7.7% over Clinton. Independents outnumbered Democrats by 6.7%.

Unadjusted Exit Polls
1-Use Party-ID from the CNN exit poll (matched to reported vote).
2-Independent vote shares adjusted to match the adj. exit poll.

CNN Exit Poll (Reported Vote)
Clinton Trump Trump EV
65,719 62,890 306
48.2% 46.2% (total reported vote)
49.3% 45.2% 224 (28 exit poll states)
43.7% 50.4% 82 (23 other states)

Unadjusted State Exit Polls (implausible)
Clinton Trump Trump EV
48.5% 44.8% 241
49.6% 43.6% 159 (28 exit poll states)
43.7% 50.4% 82 (23 other states)

True Vote Model 1 (use state-adjusted Gallup National Party-ID)
Clinton Trump Trump EV
47.3% 46.5% 279
48.1% 45.6% 197 (28 exit poll states)
43.7% 50.4% 82 (23 other states)

True Vote Model 2: Sensitivity Analysis (Gallup Party-ID)

Scenario 1: Undecided Voters to Trump: 50%
Clinton Trump Trump EV
45.1% 47.5% 306
45.5% 46.8% 224 (28 exit poll states)
43.7% 50.4% 82 (23 other states)

Scenario 2: Undecided Voters to Trump: 60%
Clinton Trump Trump EV
44.7% 47.9% 313
45.0% 47.3% 231 (28 exit poll states)
43.7% 50.4% 82 (23 other states)

Scenario 3: Undecided Voters to Trump: 70%
Clinton Trump Trump EV
44.3% 48.3% 342
44.5% 47.8% 260 (28 exit poll states)
43.7% 50.4% 82 (23 other states)

https://docs.google.com/spreadsheets/d/1R9Y3ae2uyW8SUxVUnnOt9ZyvheAxa0fAhesAw_nhciM/edit#gid=0

OHIO
Reported Party-ID Clinton Trump Johnson Stein
Dem 34% 87% 12% 0% 1%
Rep 37% 8% 89% 2% 1%
Ind 29% 38% 52% 8% 2%
Calc 100% 43.6% 52.1% 3.1% 1.3%
Reported 99.3% 43.6% 51.7% 3.2% 0.8%
Votes 5,496 2,394 2,841 174 46
    Margin 447 8.1%  
Exit Poll Party-ID Clinton Trump Johnson Stein
Dem 34% 87% 12% 0% 1%
Rep 37% 8% 89% 2% 1%
Ind 29% 50% 35% 8% 7%
Match 100% 47.0% 47.2% 3.1% 2.7%
Unadj.EP 100% 47.0% 47.1% 3.2% 2.7%
Votes 5,496 2,583 2,589 176 148
    Margin 5 0.1%
True Vote Gallup adj. Clinton Trump Johnson Stein
Dem 32.4% 87% 12% 0% 1%
Rep 33.4% 8% 89% 2% 1%
Ind 34.2% 38% 52% 8% 2%
TVM1 100.0% 43.9% 51.4% 3.4% 1.3%
95.1% 41.6% 46.7% 4.4% 2.4%
TVM 100% 43.6% 49.6% 4.0% 2.8%
Votes 5,496 2,396 2,729 220 152
    Margin 332 5.1%  
 
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Posted by on December 20, 2016 in 2016 election

 

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2016 Election Model Forecast

Richard Charnin
Nov. 7, 2016

77 Billion to One: 2016 Election Fraud
Matrix of Deceit: Forcing Pre-election and Exit Polls to Match Fraudulent Vote Counts
Proving Election Fraud: Phantom Voters, Uncounted Votes and the National Poll
LINKS TO  POSTS

Unlike corporate mainstream polls, the 2016 Election Model  provides two forecasts:  the Recorded Vote and the True Vote. Pollsters are usually quite accurate in their projections of the Recorded Vote. But they avoid the fraud factor. The fraudulent Recorded Vote is never the same as the True Vote. Clinton won the recorded vote by 48.3-46.2%.

The  Election Model  is based on the effects of changes in party affiliation (Dem, Rep, Ind) from 2012 to 2016. Clinton led the final 9-poll average 45.8-43.3% (298-240 EV). 

Election Model forecast: State party-ID weights were adjusted to Gallup party-affiliation survey weights. Gallup is the only poll dedicated to tracking national  party affiliation. 

After adjusting the polls for the Gallup voter affiliation  (40I-32D-28R), undecided voters were allocated (UVA) to derive the final adjusted TRUE poll share. Typically the challenger (in this case Trump) wins the majority (75%) of the undecided vote.

Recorded Vote: Trump wins 44.4-42.9% with 306-232 EV.
True Vote: 75% of undecided voters allocated to Trump.
Trump wins 48.5-44.3% with 351-187 EV.

Forecast Methodology

The 2016 party-ID for each state is calculated by applying a proportional  change  from the 2012 party-ID based on  the Gallup 2016 national survey. The popular vote win probability and corresponding Electoral Vote are estimated for each pre-election poll. State votes are forecast by applying national poll shares to the state party-ID.

The electoral vote is  calculated two ways: 1)  the total EV  (snapshot) in which the winner of the state wins all  of the state electoral votes and 2) the statistically expected EV (state win probability times the state electoral vote). Sensitivity Analysis tables show the effect of incremental vote shares on the total vote.

Sensitivity Analysis: Undecided Voter Allocation (UVA) effect on expected Electoral and Popular vote win probability 

UVA  Trump Clinton  EV   WinProb
50%….47.1….45.6…….310….. 75%
60%….47.6….45.1…….332….. 86%
75%….48.5….44.3…….351….. 96%

Note: The 2008 and 2012 election models exactly forecast the electoral vote (365 and 332 for Obama). But the True Votes were quite different. The 2008 model forecast that Obama would win 420 votes with a 58% share, exactly matching the state unadjusted exit poll aggregate. He led the unadjusted National Exit Poll by 61-37%.  

The 2012 model forecast that Obama would win 51.5% recorded and 55% True vote (380 EV}.  The exit pollsters did not poll in 19 states. https://richardcharnin.wordpress.com/2014/09/14/summary-2004-2012-election-forecast-1968-2012-true-vote-model/

 9-POLL  AVG  Gallup
 Before UVA Pct Stein Clinton Trump Johnson
Ind 40% 5% 33% 44% 8%
Dem 32% 1% 89% 6% 2%
Rep 28% 1% 5% 89% 3%
Total 94.6% 2.6% 42.9% 44.4% 4.7%
Electoral Vote 538 0 232 306 0
 Expected EV      228   310 
REPORTED Party-ID      Vote   EVote  
POLL Ind Dem Rep Clinton Trump Clinton Trump
Ipsos 16% 45% 38% 43.0% 39.0% 317 221
IBD 37% 34% 29% 41.0% 43.0% 216 322
Rasmussen 32% 40% 28% 45.0% 43.0% 313 225
Quinnipiac 26% 40% 34% 47.0% 40.0% 378 160
Fox News 19% 43% 38% 48.0% 44.0% 317 221
CNN 43% 31% 26% 49.0% 44.0% 362 176
ABC 29% 37% 29% 47.0% 43.0% 317 221
Gravis 27% 40% 33% 47.0% 45.0% 294 244
LA Times 30% 38% 32% 42.6% 48.2% 180 358
Average 28.8% 38.7% 31.9% 45.5% 43.2% 299 239

 

Gallup Adj.  Vote   EVote   Trump UVA
40I-32D-28R Clinton Trump Clinton Trump WinProb WinProb
Ipsos 37.9% 36.4% 288 250 25.2% 96.2%
IBD 40.2% 43.2% 216 322 88.3% 99.5%
Rasmussen 41.1% 45.3% 187 351 94.4% 99.6%
Quinnipiac 44.7% 40.8% 335 203 6.5% 35.8%
Fox News 44.2% 43.9% 255 283 45.3% 66.1%
CNN 48.6% 44.4% 335 203 7.0% 13.7%
ABC 46.8% 47.0% 249 289 53.9% 58.0%
Gravis 43.6% 45.5% 216 322 75.0% 97.5%
LA Times 40.3% 49.8% 51 487 100.0% 100.0%
Average 42.9% 44.4% 237 301 74.7% 96.6%
Recorded EV before UVA   232 306   96.1%
True EV       after UVA 187 351   100%
 Forecast Vote Recorded  Electoral
 before UVA Clinton % Trump % Clinton Trump
Total 42.9 44.4 232 306
AK 32.4 49.6 0 3
AL 37.4 51.0 0 9
AR 39.4 48.6 0 6
AZ 37.9 47.6 0 11
CA 45.7 41.0 55 0
CO 39.1 46.5 0 9
CT 44.2 40.5 7 0
DC 66.0 23.6 3 0
DE 47.6 39.7 3 0
FL 42.2 44.8 0 29
GA 40.5 47.7 0 16
HI 46.7 41.8 4 0
IA 39.4 46.1 0 6
ID 33.2 54.5 0 4
IL 45.8 42.4 20 0
IN 39.4 48.6 0 11
KS 33.9 52.3 0 6
KY 47.9 41.8 8 0
LA 38.6 45.7 0 8
MA 45.9 37.2 11 0
MD 51.4 36.7 10 0
ME 40.9 44.1 0 4
MI 44.1 44.0 16 0
MN 43.6 44.7 0 10
MO 40.3 48.0 0 10
MS 39.4 49.0 0 6
MT 36.1 52.3 0 3
NC 44.5 42.3 15 0
ND 38.3 50.0 0 3
NE 35.8 52.0 0 5
NH 38.1 46.6 0 4
NJ 42.8 41.2 14 0
NM 46.5 41.1 5 0
NV 42.7 44.4 0 6
NY 49.3 37.7 29 0
OH 41.6 46.7 0 18
OK 42.5 46.5 0 7
OR 42.9 43.3 0 7
PA 46.6 42.3 20 0
RI 48.7 35.4 4 0
SC 40.3 48.0 0 9
SD 37.5 50.4 0 3
TN 37.9 50.3 0 11
TX 40.1 47.5 0 38
UT 31.2 57.3 0 6
VA 41.2 47.0 0 13
VT 46.7 41.0 3 0
WA 42.8 46.6 0 12
WI 42.7 45.7 0 10
WV 48.2 39.5 5 0
WY 26.8 61.9 0 3
 
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Posted by on November 7, 2016 in 2016 election

 

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