2008 ELECTION MODELA Monte Carlo Electoral Vote SimulationUpdated: September 20
Press REFRESH after linking to a graph to view the latest update
Chart State Poll Aggregate + Projection Trend
Chart National 5-Poll Moving Average Projection
Chart State vs. National: Vote Share Projection Trends
Chart Battleground-State Polls
Chart Battleground-State Win Probability
Chart Obama Electoral Vote Simulation Frequency
Chart Electoral Vote + Win Probability Trend
Chart Electoral Vote + Projected Vote Share Trend
Chart Undecided Voter Allocation + Win Probability
Chart Monte Carlo Electoral Vote Simulation Trials 2008 Election Model Fraud Analyzer
Uncounted & Switched Votes
Chart Effect on Obama Projected Vote Share
Chart Effect on Obama Projected Electoral Vote
This
State
National
State
National
Monte Carlo
Simulation
Update
Poll
5-Poll
2-party
2-party
Expected
9/20/2008
Aggregate
Average
Projection
Projection
Electoral Vote
Obama
McCain
46.62 (50.36)
45.95 (49.64)
48.20 (51.83)
44.80 (48.17)
51.08
48.92
52.40
47.60
323
215
15-Poll
End
Sample
Poll
NATIONAL MODEL
Pre UVA
5-Poll Mov Avg
2-Party Projection (60% UVA)
5-Poll Mov Avg
Trend
Rasmussen
Gallup
Hotline/FD
Quinnipiac
CBS/NYT
Zogby
Ipsos
Pew Research
Newsweek
AP/gFk
FOX News
NBC/WSJ
CBS/NYT
CNN
ABC/WP
Registered V
vs Likely V
Poll Averages
Date
9/19
9/19
9/18
9/16
9/16
9/15
9/15
9/14
9/11
9/10
9/09
9/08
9/07
9/07
9/07
Size
3000 LV
2796 RV
915 RV
987 LV
800 LV
1008 LV
1046 RV
2307 LV
1038 RV
812 RV
900 RV
1000 RV
655 RV
942 RV
1000 LV
RV avg
LV avg
Total
MoE
1.79%
1.85%
3.24%
3.12%
3.46%
3.09%
3.03%
2.04%
3.04%
3.44%
3.27%
3.10%
3.83%
3.19%
3.10%
Obama
48
50
45
49
49
47
45
46
46
44
42
46
44
48
47
45.6
47.7
46.4
McCain
47
44
44
45
44
45
45
46
46
48
45
45
46
48
49
45.7
46.0
45.8
Other
5
6
11
6
7
8
10
8
8
8
13
9
10
4
4
8.8
6.3
7.8
Spread
1
6
1
4
5
2
0
0
0
(4)
(3)
1
(2)
0
(2)
(0.1)
1.7
0.6
Obama
48.2
48.0
47.0
47.2
46.6
45.6
44.6
44.8
44.4
44.8
45.4
45.0
44.6
45.0
43.8
McCain
44.8
44.4
44.6
45.0
45.2
46.0
46.0
46.0
46.0
46.4
46.6
46.6
48.4
47.2
46.0
Spread
3.4
3.6
2.4
2.2
1.4
(0.4)
(1.4)
(1.2)
(1.6)
(1.6)
(1.2)
(1.6)
(3.8)
(2.2)
(2.2)
Obama
52.40
52.6
52.0
51.9
51.5
50.6
50.2
50.3
50.2
50.1
50.2
50.0
48.8
49.7
49.9
McCain
47.60
47.4
48.0
48.1
48.5
49.4
49.8
49.7
49.8
49.9
49.8
50.0
51.2
50.3
50.1
Spread
4.8
5.1
4.1
3.8
3.0
1.3
0.5
0.6
0.3
0.2
0.4
0.1
(2.4)
(0.6)
(0.2)
Win Prob
99.6
99.7
89.1
88.1
80.5
65.8
56.2
62.1
54.1
51.8
54.8
51.0
27.0
42.2
48.0
Obama’s EV and Popular Vote Win ProbabilityAssuming the election is held today, Obama’s win probability as calculated by
fivethirtyeight.com (
71.5%) is not consistent with their projected
303–235 EV.
The Election Model uses a 5000-election trial Monte Carlo simulation. The model projects that
if a fraud-free election is held today, Obama would win
323–
215 Electoral votes with
51.1% of the two-party vote. The EV win probability is a simple calculation: Obama won 4926 of 5000 simulated election trials; his
win probability is therefore
98.5% (4926/5000). It’s a snapshot which changes slightly every day.
The model indicates that for the same 303-235 EV split, Obama’s EV win probability is
92% (assuming he wins just 50% of the undecided vote). Since the probability calculations in both models are based on the
latest state polls, there is obviously a difference in
methodology between the models.
The Election Model
base case scenario assumes that Obama will win
60% of the
undecided vote. And this is conservative, as he is presumed to be the challenger (McSame is running for the third Bush term).
View the Election Model
Electoral Vote Simulation Frequency chart.
Note that 4926 (98.5%) of the 5000 simulated election trials are over 270 for Obama. Compare this result to the equivalent fivethirtyeight.com chart in which 28.5% of the trials which McCain won are in red, while the 71.5% Obama won are in blue. The chart should be 98.5% blue.Obama also leads the
National projection model (based on the average of the latest 5 national polls) with
52.4% of the 2-party vote. Note that the
national polls lead the state polls, so that we can expect a rise in Obama’s expected EV and win probability. The national model also assumes that he will win 60% of the undecided vote. The probability that he will win the popular vote is over
98%.
As of Sept.20,
electoral-vote.com has Obama leading by
273–
265;
realclearpolitics has him losing by
202–
216 (120 tossup);
fivethirtyeight.com has Obama by
303–
235. But the
2008 Election Model (
EM) had Obama leading:
323–
215. Why the difference?
Why Election Model projections differ from the Media, Academia and the BloggersThere are a variety of
election forecasting models used in academia, the media and internet election sites. The corporate MSM (CNN, MSNBC, FOX, CBS, etc.) sponsors national polls to track the “horserace” and state polls to calculate the electoral vote.
And why don’t they mention the fraud factor? If just 2% of votes cast are
uncounted (2.74% were in 2004) and 4% of Obama’s votes are
switched electronically to McCain,
McCain will win by 293–245 EV with 51.2% of the two-party vote.• The EM uses Monte Carlo (MC) simulation method to calculate the probability of winning the electoral vote. Monte Carlo is widely used to analyze diverse risk-based models when an analytical solution is impractical or impossible. The EM is updated weekly based on the latest state and national polls. The model projects the
popular and
electoral vote,
assuming both clean and fraudulent election scenarios. The EM allocates the electoral vote based on the
state win probability in calculating a more realistic
total Expected EV.
• Corporate MSM pollsters and media pundits use state and national polling data. Electoral vote projections are misleading, since they are calculated based on the latest state polls regardless of the spread; the state poll leader gets all of its electoral votes.
This is statistically incorrect; they do not consider
state win probabilities. And there is no adjustment for the
allocation of undecided voters.
For example, assume that McCain leads by 51–49% in each of five states with a total of 100 electoral votes. Most models would simply assign the 100 EV to McCain. But that is an
oversimplification: Obama could easily win one or more of the states, since his win probability is 31% :
- The state projected vote share V(i) is the state poll share PS(i) plus the undecided voter allocation UVA(i):
V(i) = PS(i)+UVA(i), for i=1,51 states
For this example, a final Obama projected vote share V(i) = .49 for all states is assumed (with distinct state poll shares PS(i) and respective undecided voter allocations UVA(i) implied). Five states total 100 EV.
- The probability P(i) of winning each state assuming a 4% polling MoE (95% confidence):
P(i) = NORMDIST ( V(i), 0.5, .04/1.96, true )
.31 = NORMDIST( .49, 0.5, .04/1.96, true) for each of the 5 states (the NORMDIST function is available in Excel)
The
2008 Election Model would allocate 31% of 100 EV to Obama and 69% of 100 EV to McCain.
• Bloggers also track state and national polls and do not adjust for undecided voters. A few use Monte Carlo simulation, but the EV win probabilities and frequency distributions are NOT consistent with the polling data. Either the state win probabilities and/or the simulation algorithm is incorrect.
• Academic regression models predict the popular vote but are run months prior to the election. They are typically based on economic and political factors rather than state or national polling data. They do not project the electoral vote. In 2004, virtually all of them forecast Bush to win by 5-10%. But since the election was stolen, the models had to be wrong — they didn’t factor election fraud as an independent variable in the regression. In fact, they never even mentioned the F-word in describing their methodologies.
Fixing the polls: Party ID, Voted in 2000, RV vs. LVThere has been much discussion regarding the recent McCain “surge” in the national polls. Most national and state polls are sponsored by the corporate MSM. Gallup, Rasmussen and other national polls recently increased the Republican
Party ID percentage weighting. This had the immediate effect of boosting McCain’s poll numbers.
But there are 11 million more registered Democrats than registered Republicans. USA Today/Gallup changed the poll method from
RV to
LV right after the Republican convention.
Party-ID weights were manipulated to favor McCain as well.
There is a consistent discrepancy between
Registered Voter (RV) and Likely Voter (LV) Polls. The Democrats always do better in RV polls. No wonder: Since 1988, Democratic presidential candidates have won
new voters by an average 14% margin.
The manipulation of polling weights is nothing new. Recall that the 2004 and 2006 Final National Exit Polls weightings were adjusted to match the recorded vote miscount. But
all category cross-tabs had to be changed, not just Party ID. Of course, the
Final Exit Poll (state and national)
is always matched to the Recorded vote, even though it may be fraudulent — as it was in
2000,
2002,
2004 and
2006. This cannot be emphasized enough. Say it loud, again and again.
In 2004, the
12:22am National Exit Poll (NEP) had a
38–
35 Democrat/Republican
'Party ID' mix.
Kerry
won the
12:22am Preliminary NEP by
51–
48%. (
13,047 random sample, 1% MoE )
The mix was changed to
37–
37 in the
Final NEP to
'force' a match to the Recorded vote;Bush won the 1:25pm 'forced' Final NEP by 51–48%.
Likewise, the Gore/Bush
'Voted 2000' weights were changed from
39–
41 to
37–
43 in the Final ('13047' & '13660'
here).
Bush was the
official winner by 50.7–48.3% with 286 EV.
The final 2004 Election Model projection indicated that Kerry would win 337–201 EV with 51.8% of the 2-party vote. In their Jan. 2005 report, exit pollsters Edison-Mitofsky provided the average exit poll discrepancy for each state based on 1250 total precincts. Kerry won the unadjusted aggregate state exit poll vote share by 52.0–47.0% (2-party 52.5%) with 337 electoral votes — exactly matching the Election Model!
In the 2006 midterms, the 7pm Preliminary NEP had a 39–35 Democratic/Republican weighting mix. The Democrats won that NEP by 55–43%. But the weights were changed to 38–36 in the Final NEP in order to match the 52–46% recorded vote; the Dem 12% margin was cut in half. Once again, the 'Voted 2004' weights were transformed: from Bush/Kerry 47–45 at 7pm to 49–43 in the Final. The landslide was denied; 10-20 Dem seats were stolen.
The “dead heat” claimed by pollsters, bloggers and the media is a canard — unless they are factoring fraud into their models and not telling us. The media desperately wants a horserace, and so they fail to adjust the polls for undecided and newly registered voters. They avoid McCain’s gaffes, flip-flops and plagiarisms, while he supports the most unpopular president in history.
Polling data source:
Electoral-vote.com
RealClearPolitics.com
THE 2008 ELECTION MODEL
Last
Aggregate
5-poll
2-party
2-party
Monte Carlo
Simulation
Update
State
National
State
National
Expected
9/20/2008
Average
Average
Projection
Projection
Electoral Vote
60% UVA
Obama
McCain
46.62
45.95
48.20
44.80
51.08
48.92
52.40
47.60
323
215
2004 Final
75% UVA
Kerry
Bush
47.88
46.89
47.80
46.60
51.80
48.20
51.77
48.23
337
201
Sensitivity Analysis — Impact of Uncounted and Switched Votes on Obama
Uncounted
1%
2%
3%
Switched
2%
4%
6%
Vote%
50.1
49.0
48.0
EV
292
259
226
Vote%
49.8
48.8
47.8
EV
276
245
212
Vote%
49.6
48.5
47.5
EV
261
230
199
Sensitivity Analysis — Impact of Aggregate State Projected Vote Share
Undecided Voter Allocation Scenario
Base Case
Obama
40%
50%
60%
70%
80%
Projected 2-Party Vote Share
Obama
McCain
49.6
50.4
50.3
49.7
51.08
48.92
52.2
47.8
52.6
47.4
MoE
Obama Popular Vote Win Probability (Normdist)
1.0 %
2.0 %
3.0 %
21.4
34.6
39.6
74.7
63.0
58.8
98.3
85.5
76.0
100.0
98.4
92.4
100.0
99.4
95.3
Obama Electoral Vote (Monte Carlo - 5000 election trials)
Mean
Median
283.4
283
303.5
303
322.6
324
343.9
345
350.8
353
Maximum
Minimum
372
176
393
223
398
236
409
262
415
278
Obama Electoral Vote Win Probability (Monte Carlo)
Trial Wins
Probability
3441
68.8
4577
91.5
4926
98.50
4998
99.96
5000
100.0
95% EV Confidence Interval
Upper
Lower
335
232
352
255
368
277
384
304
389
313
States Won
Obama
23
24
27
29
29
2008 POLLING ANALYSIS AND PROJECTIONS National Model —
see atopState Model(2-party vote shares)
Click state abbreviation for election fraud articles
L A T E S T P O L L S
OBAMA vs KERRY
MONTE CARLO EV SIMULATION
Pre-Undecided Voter Allocation
Projection
Projection
JK Exit Poll
Recorded
Diff
Diff
Obama
Obama
Sprd*wt
Battlegrnd
EVote
Poll
Date
9/17
9/17
9/14
7/14
9/14
9/17
9/16
9/13
9/15
9/17
9/17
9/12
9/9
9/17
9/17
9/17
9/10
9/12
9/12
9/10
9/5
8/5
9/17
9/17
9/16
9/15
9/8
9/17
9/14
9/15
9/16
9/16
9/15
9/16
9/8
9/17
9/11
9/15
9/17
9/13
9/17
9/9
8/20
9/16
9/13
9/13
9/17
9/10
9/16
9/17
9/10
EV
538
9
3
10
6
55
9
7
3
3
27
15
4
4
21
11
7
6
8
9
4
10
12
17
10
6
11
3
5
5
4
15
5
31
15
3
20
7
7
21
4
8
3
11
34
5
3
13
11
5
10
3
Obama
46.62 %
34
38
39
37
52
48
55
90
53
48
42
63
27
53
46
51
31
37
38
50
52
49
49
49
37
45
42
34
45
51
51
50
52
47
41
46
32
48
47
59
37
37
32
44
28
58
47
48
45
50
34
McCain
45.95 %
60
55
56
47
36
42
37
9
42
48
54
32
68
37
48
42
63
55
54
40
38
37
44
44
55
50
53
60
46
45
42
43
40
48
55
45
64
43
45
36
59
54
56
54
64
36
47
43
49
47
62
Diff
0.68
(26)
(17)
(17)
(10)
16
6
18
81
11
0
(12)
31
(41)
16
(2)
9
(32)
(18)
(16)
10
14
12
5
5
(18)
(5)
(11)
(26)
(1)
6
9
7
12
(1)
(14)
1
(32)
5
2
23
(22)
(17)
(24)
(10)
(36)
22
0
5
(4)
3
(28)
Obama
51.08 %
37.6
42.2
42.0
46.6
59.2
54.0
59.8
90.6
56.0
50.4
44.4
66.0
30.0
59.0
49.6
55.2
34.6
41.8
42.8
56.0
58.0
57.4
53.2
53.2
41.8
48.2
45.0
37.6
50.4
53.4
55.2
54.2
56.8
50.0
43.4
51.4
34.4
53.4
51.8
62.0
39.4
42.4
39.2
45.2
32.8
61.6
50.6
53.4
48.6
51.8
36.4
Final Kerry
51.80 %
42.0
39.8
48.8
51.0
55.8
50.8
56.5
86.3
57.8
52.3
46.5
52.5
38.3
57.0
41.3
54.5
39.3
42.8
49.0
58.3
56.3
70.8
54.3
55.0
47.3
49.3
41.3
37.3
50.5
51.5
56.0
50.5
60.0
49.0
42.5
52.3
36.3
54.5
53.8
62.0
44.3
46.5
49.2
40.0
29.3
58.3
48.5
55.0
50.0
54.8
33.5
IMS WPE
52.49
42.3
40.6
45.0
45.7
60.7
50.6
62.9
91.5
61.9
51.5
42.4
58.7
32.6
57.1
40.8
51.2
37.5
40.3
44.0
56.1
60.2
66.4
55.0
56.3
49.5
49.5
37.6
37.4
53.4
57.8
58.1
53.6
65.1
50.0
35.0
54.6
34.2
51.9
55.7
62.7
46.2
36.3
43.6
42.4
28.4
67.2
50.3
57.4
40.7
52.6
32.9
Kerry
48.76
37.2
35.9
44.8
45.0
54.9
47.5
54.9
90.1
53.9
47.6
41.8
54.6
30.6
55.4
39.7
49.7
37.0
40.1
42.6
54.1
56.5
62.6
51.7
51.6
40.2
46.6
39.0
33.0
48.4
50.7
53.5
49.5
59.0
44.0
35.9
49.2
34.8
51.9
51.4
60.0
41.3
38.8
43.0
38.6
26.3
59.5
45.9
53.4
43.6
50.2
29.4
Projection
(0.72)
(4.4)
2.5
(6.8)
(4.4)
3.5
3.3
3.3
4.3
(1.7)
(1.9)
(2.1)
13.5
(8.3)
2.0
8.4
0.7
(4.7)
(1.0)
(6.2)
(2.2)
1.7
(13.4)
(1.1)
(1.8)
(5.5)
(1.1)
3.8
0.4
(0.1)
1.9
(0.8)
3.7
(3.2)
1.1
0.9
(0.9)
(1.9)
(1.1)
(2.0)
0.0
(4.9)
(4.1)
(10.0)
5.2
3.6
3.4
2.1
(1.6)
(1.4)
(3.0)
2.9
UnadjEP
(1.41)
(4.7)
1.6
(3.0)
0.9
(1.5)
3.4
(3.1)
(0.9)
(5.9)
(1.1)
2.0
7.3
(2.6)
1.9
8.8
4.0
(2.9)
1.5
(1.2)
(0.1)
(2.2)
(9.0)
(1.8)
(3.1)
(7.7)
(1.3)
7.4
0.2
(3.0)
(4.4)
(2.9)
0.6
(8.3)
(0.0)
8.4
(3.2)
0.2
0.6
(3.9)
(0.7)
(6.8)
6.1
(4.4)
2.8
4.4
(5.6)
0.3
(4.0)
7.9
(0.8)
3.5
Exp EV
321.7
0.0
0.0
0.0
0.3
55.0
8.8
7.0
3.0
3.0
15.6
0.0
4.0
0.0
21.0
4.6
7.0
0.0
0.0
0.0
4.0
10.0
12.0
16.0
9.4
0.0
2.0
0.0
0.0
2.9
3.8
14.9
4.9
31.0
7.5
0.0
15.1
0.0
6.7
17.0
4.0
0.0
0.0
0.0
0.3
0.0
3.0
8.0
10.5
1.2
8.1
0.0
Win Prob
98.5
0.0
0.0
0.0
4.8
100.0
97.5
100.0
100.0
99.8
57.8
0.3
100.0
0.0
100.0
42.2
99.5
0.0
0.0
0.0
99.8
100.0
100.0
94.2
94.2
0.0
18.6
0.7
0.0
57.8
95.2
99.5
98.0
100.0
50.0
0.1
75.4
0.0
95.2
81.1
100.0
0.0
0.0
0.0
0.9
0.0
100.0
61.6
95.2
24.6
81.1
0.0
Rank
100%
2.1
19.2
6.1
5.4
3.2
3.7
3.2
0.9
0.8
9.5
12.6
2.2
11.6
9.2
3.5
2.0
4.7
Evote
201
9
27
11
17
10
11
5
4
5
15
20
7
21
13
11
5
10
Flip (*)
86
AL
AK
AZ
AR
CA
CO*
CT
DC
DE
FL*
GA
HI
ID
IL
IN
IA*
KS
KY
LA
ME
MD
MA
MI
MN
MS
MO
MT
NE
NV*
NH
NJ
NM*
NY
NC
ND
OH*
OK
OR
PA
RI
SC
SD
TN
TX
UT
VT
VA*
WA
WV
WI
WY
The Election Calculator Model
The
2004 Election Calculator was developed as a response to the Final 2004 National Exit Poll.
The Final was forced to match the recorded vote using impossible weightings.
Read more about the 1988-2004 Election Calculator
here.
The
2008 Election Calculator projects Obama will win the
True Vote by
71 – 59m.
Read more about the 2008 Election Calculator
here.
The Great Election Fraud Lockdown: Uncounted, Stuffed and Switched VotesProfessional statistical organizations, media pundits and election forecasters who projected a Bush victory never discuss
Election Fraud.
On the contrary, a complicit media has been in a permanent election fraud lockdown, as it relentlessly promotes the fictional propaganda that Bush won BOTH elections. They want you to believe that Democrats always do better in the exit polls, because Republican voters are
reluctant responders. But they never consider other, more plausible explanations — such as
uncounted votes and
stuffed ballots. Read more
here.
Apparently, the MSM and election fraud naysayers are unaware that millions of ballots are either uncounted or stuffed. And that these anomalies have always favored a Bush: in 1988, 1992, 2000 and 2004. That is one reason why the Democratic
True vote (and exit poll share) is
always greater than the
Recorded vote.
The MSM does not want you to know the facts and assumes that you won’t try to reconcile the preliminary exit polls, census and recorded vote totals. If you try, expect to be labeled as a conspiracy nut.
These are the facts:
a) In most states, total votes cast exceeded votes recorded (uncounted ballots exceeded stuffed). In Florida, Ohio and about 10 other states, total votes recorded exceeded votes cast (ballot stuffing exceeded uncounted ballots).
b) The majority (70-80%) of uncounted ballots are in Democratic minority precincts. In 2000, according to the 2004 Census, a net
5.4 million of
110.8m total votes cast (4.9%) were uncounted, of which approximately 4.0m were Gore votes.
c) In 2004, Bush won the recorded vote by 62–59m with 286 EV. But
3.4m of
125.7 million total votes cast were uncounted (2.7%) and 2.5m were for Kerry. Adding back the uncounted votes, the recorded Bush 3.0m margin is cut in half, 62.9 - 61.5m.
Repeat a lie often enough, and it becomes conventional wisdom. Although the media commissioned exit polls which indicated that Kerry won by 5%, they never explained why
mathematically impossible weights were used in the
Final Exit Poll to
'force' a match to the
recorded vote count.
In the Three-Card Monte con, the mark is tricked into betting that he can find the money card among three face-down cards. A rigged election is the Vote Scam equivalent of the Three-card Monte. What you see in the
exit polls is not what you get in the
recorded count; the
recorded vote is never equal to the
True vote. In this con game, the voter is the mark. Any model which correctly calculates the True vote is doomed to fail in a rigged election.
Allocating Undecided Voters: Sensitivity AnalysisIn the 2008 Election Model, Obama is considered to be the challenger, since McCain is running for Bush’s third term. Typically, challengers win 60–90% of the
undecided vote (
UVA), if the incumbent is unpopular.
The
State Model includes a sensitivity (risk) analysis of five Obama undecided voter (UVA) scenario assumptions ranging from 40–80%, with
60% as the
base case. This enables one to view the effects of various projection assumptions on the expected electoral vote and win probability. Electoral vote forecasting models which do not provide a risk factor sensitivity analysis are incomplete.
The
National Model calculates a 5-poll moving average projection assuming the 60% UVA scenario.
In 2004,
final state and national Pre-Election Polls had the race nearly tied at 47%. Bush had a
48% approval rating. That’s one reason why the Gallup poll projected that Kerry would win 88% of the late undecided vote.
The
2004 Election Model allocated 75% of the undecided vote to Kerry as the
base case of a five UVA sensitivity analysis. The
base case scenario projected that Kerry would have an expected
337 electoral votes with
51.8% of the two-party vote. His electoral vote win probability was over
99%.
Calculating the Expected Electoral Vote: A Simple SummationIt’s hard to understand why election forecasting blogs and academics and the media, who employ the latest state polls as input to their models, don’t use basic probability, statistics and simulation concepts in forecasting the electoral vote and corresponding win probability.
A meta-analysis or simulation is not required to calculate the expected electoral vote. Of course, the individual state vote projections depend on the particular forecasting method used.
This is the procedure in the
2008 Election Model for calculating the expected electoral vote:
- The state projected vote share V(i) is the state poll PS(i) plus the undecided voter allocation UVA(i):
V(i) = PS(i)+UVA(i), for i=1,51 states
- The probability P(i) of winning each state assuming a 4% polling MoE (95% confidence):
P(i) = NORMDIST ( V(i), 0.5, .04/1.96, true )
- The expected electoral vote EVS(i) for each state (win probability times electoral vote):
EVS(i) = P(i)* EV(i)
- The total expected electoral vote EV as the sum of the state electoral votes:
EV = Σ EVS(i), for i = 1,51 states
Calculating the Probability of Winning the Electoral Vote: Monte Carlo SimulationThe Excel-based Election Model is very straightforward as shown above. After updating the database for the latest state polling data, the vote shares are projected. The normal distribution function calculates the corresponding state win probability. The expected state EV is the product of the win probability and electoral vote. The sum of the 51 state expected EVs is the total expected EV.
The final step is to calculate the EV Win Probability. The Election Model uses a
Monte Carlo (MC) simulation. MC is widely used for analyzing complex systems, when an analytical solution is prohibitive due to the virtually infinite number of possible combinations of risk-based variables (i.e. state win probabilities). A random number generator (RND) is used in the simulated election trials. The EV win probability is just a simple division: the number of winning election trials divided by 5000 (total trials).
The Monte Carlo mean and median EV of the election trials match are always within one of the EV summation formula. This proves that 5000 election trials are sufficient to derive a theoretically accurate win probability. The simulation illustrates the Law of Large Numbers (LLN).
With all due respect to Professor Sam Wang, his
Meta-Analysis program is an unnecessarily complex combinatorial algorithm when compared to Excel and Monte Carlo simulation for calculating the expected Electoral Vote and Win Probability.