Updated
- 5 February 2015 - added maxima, minima and endpoint statistics to the charts
Friday, January 30, 2015
Saturday, January 10, 2015
Polling accuracy
Leigh and Wolfers observed in 2006 that "the 'margin of error'
reported by pollsters substantially over-states the precision of
poll-based forecasts. Furthermore, the time-series volatility of the
polls (relative to the betting markets) suggest that poll movements are
often noise rather than signal" (p326). They went on to suggest, "for
forecasting purposes the pollsters' published margins of error should at
least be doubled" (p334).
Leigh and Wolfers are not alone. Walsh, Dolfin and DiNardo wrote in 2009, "Our chief argument is that pre-election presidential polling is an activity more akin to forecasting next year's GDP or the winner of a sporting match than to scientific probability sampling" (p316).
In this post I will examine these claims a little further. We start with the theory of scientific probability sampling.
We can use computer generated pseudo-random numbers to simulate the taking of many samples from a population, and we can plot the distribution of arithmetic means for those samples. A python code snippet to this effect follows.
In each simulation we draw 200,000 samples from our imaginary population. In the first simulation each sample was 400 cases in size. In the subsequent simulations the sample sizes were 800, 1200, 1600, 2400 and finally 3200 cases. For each simulation, we assume (randomly) that half the individuals in the population vote for one party and half vote for the other party. We can plot these simulations as a set of probability densities for each sample size, where the area under the curve is one unit in size. I have also reported the standard deviation (in percentage points) from the simulation (SD) against the theoretical standard deviation you would expect (TSD) for a particular sample size and vote share.
As the sample gets larger, the width of the bell curve narrows. The mean of larger samples, when randomly selected, is more likely to be closer to the population mean than the mean of the smaller samples. And so, with a sample of 1200, we can assume that there is a 95% probability that the mean of the population is within plus or minus 1.96 standard deviations (ie. plus or minus 2.8 percentage points) of the mean of our sample. This is the oft cited "margin or error", which derives from sampling error (the error that occurs from observing a sample, rather than observing the entire population).
So far so good.
Terhanian (2008) notes that telephone polling "sometimes require telephone calls to more than 25,000 different numbers to complete 1,000 15-minute interviews over a five-day period (at least in the US)". Face-to-face polling typically excludes those living in high-rise apartments and gated communities, as well as those people who are intensely private. Terhanian argues that inadequate coverage and low response rates are the most likely culprits when polls produce wildly inaccurate results.The reason for inaccuracy is that the sampling frame or approach that has been adopted does not randomly select people from the entire population. Segments of the population are excluded.
Other issues that affect poll outcomes include question design and the order in which questions are asked (McDermott and Frankovic 2003) both of which can shift poll results markedly, and house effects (the tenancy for a pollster's methodology to produce results that tend to lean to one side of politics or the other) (Jackman 2005; Curtice and Sparrow 1997).
Manski (1990) observed that while some people hold firm opinions, others do not. For some people, their voting preference is soft: what they say they would do and what they actually do differ. Manski's (2000) solution to this problem was to encourage pollsters to ask people about the firmness of their voting intention. In related research, Hoek and Gendall (1997) found that strategies to reduce the proportion of undecided responses in a poll may actually reduce poll accuracy.
A final point worth noting is that opinion polls tell us an historical fact. On the date people were polled, they claim they would have voted in a particular way. Typically, the major opinion polls do not seek to forecast how people will vote at the next election (Walsh, Dolfin and DiNardo 2009, p317). Notwithstanding this limitation, opinion polls are often reported in the media in a way that suggests a prediction on how people will vote at the next election (based on what they said last weekend when they were polled). In this context, I should note another Wolfers and Leigh (2002) finding:
Nonetheless, the margins of error that are often reported with opinion polls overstate the accuracy of those polls. These statements only refer to one of the many sources of error that impact on accuracy. While the many other sources of error are rarely as clearly identified and quantified as the sampling error, their impact on poll accuracy is no less real.
There are further complications when you want to take opinion polls and predict voter behaviour at the next election. Only polls taken immediately prior to an election are truly effective for this purpose.
All-in-all, it is not hard to see why Leigh and Wolfers (2006) said, "for forecasting purposes the pollsters' published margins of error should at least be doubled" (p334).
Janet Hoek and Philip Gendall (1997), "Factors Affecting Political Poll Accuracy: An Analysis of Undecided Respondents", Marketing Bulletin, 1997, 8, pp1-14.
Simon Jackman (2005), "Pooling the polls over an election campaign", Australian
Journal of Political Science, 40:4, pp499-51.
Andrew Leigh and Justin Wolfers (2006), "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets", Economic Record, September 2006, Vol. 82, No. 258, pp325-340.
Monika L McDermott and Kathleen A Frankovic (2003), "Horserace Polling and Survey Method Effects: An Analysis of the 2000 Campaign", The Public Opinion Quarterly, Vol. 67, No. 2 (Summer, 2003), pp244-26.
Charles F Manski (1990), “The Use of Intentions Data to Predict Behavior: A Best-Case Analysis.” Journal of the American Statistical Association, Vol 85, No 412, pp934-40.
Charles F Manski (2000), "Why Polls are Fickle", Op-Ed article, The New York Times, 16 October 2000.
Peter V Miller (2002), "The Authority and Limitations of Polls", in Jeff Manza, Fay Lomax Cook and Benjamin J Page (eds) (2002), Navigating Public Opinion: Polls, Policy and the Future of American Democracy, Oxford University Press, New York.
George Terhanian (2008), "Changing Times, Changing Modes: The Future of Public Opinion Polling?", Journal of Elections, Public Opinion and Parties, Vol. 18, No. 4, pp331–342, November 2008.
Elias Walsh, Sarah Dolfin and John DiNardo (2009), "Lies, Damn Lies and Pre-Election Polling", American Economic Review: Papers & Proceedings 2009, 99:2, pp316–322.
Justin Wolfers and Andrew Leigh (2002), "Three Tools for Forecasting Federal Elections: Lessons from 2001", Australian Journal of Political Science, Vol. 37, No. 2, pp223–240.
Leigh and Wolfers are not alone. Walsh, Dolfin and DiNardo wrote in 2009, "Our chief argument is that pre-election presidential polling is an activity more akin to forecasting next year's GDP or the winner of a sporting match than to scientific probability sampling" (p316).
In this post I will examine these claims a little further. We start with the theory of scientific probability sampling.
Polling theory
Opinion polls tell us how the nation might have voted if an election was held at the time of the poll. To achieve this magic, opinion polls depend on the central limit theorem. According to this theorem, the arithmetic means from a sufficiently large number of random samples from the entire population population will be normally distributed around the population mean (regardless of the distribution in the population).We can use computer generated pseudo-random numbers to simulate the taking of many samples from a population, and we can plot the distribution of arithmetic means for those samples. A python code snippet to this effect follows.
# --- initial
import numpy as np
import statsmodels.api as sm
import matplotlib.pyplot as plt
# --- parameters
sample_size = 400 # we will work with multiples of this
num_samples = 200000 # number of samples to be drawn in each simulation
threshold = 0.5 # proportion of the population that "vote" in a particular way
# --- model
fig = plt.figure(figsize=(8,4))
ax = fig.add_subplot(111)
for i in [1,2,3,4,6,8]:
# get sample size for this simulation
s = i * sample_size
# draw num_samples, each of size s
m = np.random.random((s, num_samples))
# get the population proportion (as a percent) that is less than the threshold
m = np.where(m < threshold, 1.0, 0.0).sum(axis=0) / (s * 1.0) * 100.0
# perform the kernel density estimation
kde = sm.nonparametric.KDEUnivariate(m)
kde.fit()
# plot
ax.plot(kde.support, kde.density, lw=1.5,
label='Sample size: {0:} SD: {1:.2f} TSD: {2:.2f}'.format(s, np.std(m),
100.0 * np.sqrt(threshold * (1 - threshold) / s)))
ax.legend(loc='best', fontsize=10)
ax.grid(True)
ax.set_ylabel(r'Density', fontsize=12)
ax.set_xlabel(r'Mean Vote Percentage for Party', fontsize=12)
fig.suptitle('The Central Limit Theorem: Probability Densities for Differnt Sample Sizes')
fig.tight_layout(pad=1)
fig.savefig('./graphs/model0', dpi=125)
In each simulation we draw 200,000 samples from our imaginary population. In the first simulation each sample was 400 cases in size. In the subsequent simulations the sample sizes were 800, 1200, 1600, 2400 and finally 3200 cases. For each simulation, we assume (randomly) that half the individuals in the population vote for one party and half vote for the other party. We can plot these simulations as a set of probability densities for each sample size, where the area under the curve is one unit in size. I have also reported the standard deviation (in percentage points) from the simulation (SD) against the theoretical standard deviation you would expect (TSD) for a particular sample size and vote share.
So far so good.
Polling practice
But sampling error is not the only problem with which opinion polls must contend. The impression of precision from a margin of error is (at least in part) misleading, as it "does not include an estimate of the effect of the many sources of non-sampling error" (Miller 2002, p225).Terhanian (2008) notes that telephone polling "sometimes require telephone calls to more than 25,000 different numbers to complete 1,000 15-minute interviews over a five-day period (at least in the US)". Face-to-face polling typically excludes those living in high-rise apartments and gated communities, as well as those people who are intensely private. Terhanian argues that inadequate coverage and low response rates are the most likely culprits when polls produce wildly inaccurate results.The reason for inaccuracy is that the sampling frame or approach that has been adopted does not randomly select people from the entire population. Segments of the population are excluded.
Other issues that affect poll outcomes include question design and the order in which questions are asked (McDermott and Frankovic 2003) both of which can shift poll results markedly, and house effects (the tenancy for a pollster's methodology to produce results that tend to lean to one side of politics or the other) (Jackman 2005; Curtice and Sparrow 1997).
Manski (1990) observed that while some people hold firm opinions, others do not. For some people, their voting preference is soft: what they say they would do and what they actually do differ. Manski's (2000) solution to this problem was to encourage pollsters to ask people about the firmness of their voting intention. In related research, Hoek and Gendall (1997) found that strategies to reduce the proportion of undecided responses in a poll may actually reduce poll accuracy.
A final point worth noting is that opinion polls tell us an historical fact. On the date people were polled, they claim they would have voted in a particular way. Typically, the major opinion polls do not seek to forecast how people will vote at the next election (Walsh, Dolfin and DiNardo 2009, p317). Notwithstanding this limitation, opinion polls are often reported in the media in a way that suggests a prediction on how people will vote at the next election (based on what they said last weekend when they were polled). In this context, I should note another Wolfers and Leigh (2002) finding:
Not surprisingly, the election-eve polls appear to be the most accurate, although polls taken one month prior to the election also have substantial predictive power. Polls taken more than a month before the election fare substantially worse, suggesting that the act of calling the election leads voters to clarify their voting intentions. Those taken three months prior to the election do not perform much better than those taken a year prior. By contrast, polls taken two years before the election, or immediately following the preceding election, have a very poor record. Indeed, we cannot reject a null hypothesis that they have no explanatory power at all... These results suggest that there is little reason to conduct polls in the year following an election.
Conclusion
The central limit theorem allows us to take a relatively small but randomly selected sample and make statements about the whole population. These statements have a mathematically quantified reliability, which is known as the margin of error.Nonetheless, the margins of error that are often reported with opinion polls overstate the accuracy of those polls. These statements only refer to one of the many sources of error that impact on accuracy. While the many other sources of error are rarely as clearly identified and quantified as the sampling error, their impact on poll accuracy is no less real.
There are further complications when you want to take opinion polls and predict voter behaviour at the next election. Only polls taken immediately prior to an election are truly effective for this purpose.
All-in-all, it is not hard to see why Leigh and Wolfers (2006) said, "for forecasting purposes the pollsters' published margins of error should at least be doubled" (p334).
Bibliography
John Curtice and Nick Sparrow (1997), "How accurate are traditional quota opinion polls?", Journal of the Market Research Society, Jul 1997, 39:3, pp433-448.Janet Hoek and Philip Gendall (1997), "Factors Affecting Political Poll Accuracy: An Analysis of Undecided Respondents", Marketing Bulletin, 1997, 8, pp1-14.
Simon Jackman (2005), "Pooling the polls over an election campaign", Australian
Journal of Political Science, 40:4, pp499-51.
Andrew Leigh and Justin Wolfers (2006), "Competing Approaches to Forecasting Elections: Economic Models, Opinion Polling and Prediction Markets", Economic Record, September 2006, Vol. 82, No. 258, pp325-340.
Monika L McDermott and Kathleen A Frankovic (2003), "Horserace Polling and Survey Method Effects: An Analysis of the 2000 Campaign", The Public Opinion Quarterly, Vol. 67, No. 2 (Summer, 2003), pp244-26.
Charles F Manski (1990), “The Use of Intentions Data to Predict Behavior: A Best-Case Analysis.” Journal of the American Statistical Association, Vol 85, No 412, pp934-40.
Charles F Manski (2000), "Why Polls are Fickle", Op-Ed article, The New York Times, 16 October 2000.
Peter V Miller (2002), "The Authority and Limitations of Polls", in Jeff Manza, Fay Lomax Cook and Benjamin J Page (eds) (2002), Navigating Public Opinion: Polls, Policy and the Future of American Democracy, Oxford University Press, New York.
George Terhanian (2008), "Changing Times, Changing Modes: The Future of Public Opinion Polling?", Journal of Elections, Public Opinion and Parties, Vol. 18, No. 4, pp331–342, November 2008.
Elias Walsh, Sarah Dolfin and John DiNardo (2009), "Lies, Damn Lies and Pre-Election Polling", American Economic Review: Papers & Proceedings 2009, 99:2, pp316–322.
Justin Wolfers and Andrew Leigh (2002), "Three Tools for Forecasting Federal Elections: Lessons from 2001", Australian Journal of Political Science, Vol. 37, No. 2, pp223–240.
Saturday, December 20, 2014
Aggregated Polls: the first 15 months of the Abbott Government
The Federal Election was held on 7 September 2013, and the Abbott Ministry was sworn in on 18 September 2013. As the Government's fortunes have ebbed and flowed over the 15 months since the change of government, I thought it time to reflect on those changes.
First let's look at the polls over the period: we will focus on Coalition two-party preferred voting intention. In the next two charts these results are first presented as a scatter plot and then a line plot.
The simplest way to aggregate these results is through a localised regression.
But this does not adjust for the house effects (systemic biases) from individual polling houses. Nor does it factor in the sample size for the individual polls. We can do both of these with a hierarchical Bayesian model. [This is pretty much the same model as I used in the lead up to last year's Federal election (except, I have dropped the rounding effects from the model). It still assumes that the house effects sum to zero].
And to get a closer look at the estimated voting intention, I will strip away the poll results.
We will apply a smoother (using a 61-term Henderson moving average) to remove the kinks but retain the broad shape of the curve.
We can compare the smoothed Bayes model (which adjusts for house effects) with the earlier LOESS model (that does not). While the trajectories are similar, the specific results can vary from time to time.
From these charts, and focusing on the broad trajectories, I think there has been five distinct periods in the polling fortunes of the Abbott Government.
The key message here is that the 2016 Federal Election is too early to call. This is not the dead-cat bounce of the final Keating, Howard or Gillard years. The late June 2014 to mid October 2014 rebound shows that a sustained recovery is not beyond the realms of possibility. But, nor is it clear sailing for the government. It has suffered three periods of decline over the past 15 months and it is currently in a difficult position from which it needs to extract itself.
A quick word on house effects (largely for completeness): The Bayesian model estimated the house effects for each polling house as follows (relative to each other and subject to a "sum to zero constraint").
We can consolidate the above charts, adjust poll results for house effects and overlay the smoothed trajectory.
First let's look at the polls over the period: we will focus on Coalition two-party preferred voting intention. In the next two charts these results are first presented as a scatter plot and then a line plot.
The simplest way to aggregate these results is through a localised regression.
But this does not adjust for the house effects (systemic biases) from individual polling houses. Nor does it factor in the sample size for the individual polls. We can do both of these with a hierarchical Bayesian model. [This is pretty much the same model as I used in the lead up to last year's Federal election (except, I have dropped the rounding effects from the model). It still assumes that the house effects sum to zero].
We will apply a smoother (using a 61-term Henderson moving average) to remove the kinks but retain the broad shape of the curve.
We can compare the smoothed Bayes model (which adjusts for house effects) with the earlier LOESS model (that does not). While the trajectories are similar, the specific results can vary from time to time.
From these charts, and focusing on the broad trajectories, I think there has been five distinct periods in the polling fortunes of the Abbott Government.
- First a short honeymoon, that had ended by early December 2013
- We then see a four month period of stability from December 2013 to March 2014.
- The period immediately prior to and including the Federal Budget in April and May 2014 saw a four to five point decline in the polls.
- This was followed by period of rebuilding from late June 2014 to mid October 2014. Much of the ground that had been lost with the budget was recovered during this period.
- Finally, we see a second phase of rapid decline, from mid October to mid December, where that previous gain has been all but lost.
The key message here is that the 2016 Federal Election is too early to call. This is not the dead-cat bounce of the final Keating, Howard or Gillard years. The late June 2014 to mid October 2014 rebound shows that a sustained recovery is not beyond the realms of possibility. But, nor is it clear sailing for the government. It has suffered three periods of decline over the past 15 months and it is currently in a difficult position from which it needs to extract itself.
A quick word on house effects (largely for completeness): The Bayesian model estimated the house effects for each polling house as follows (relative to each other and subject to a "sum to zero constraint").
We can consolidate the above charts, adjust poll results for house effects and overlay the smoothed trajectory.
Updates
- 21 December 2014, 8.30am - updated to include ReachTEL data
- 10 January 2015 - consolidated chart added
- 7 February 2015 - updated to include maxima, minima and endpoint statistics
Saturday, September 7, 2013
Saturday morning update
This morning's polls:
Which gives an aggregation:
At this point in the blog, it is my normal practice to remind people that I anchor the above Bayesian aggregation with the assumption that the net bias across all of the polling houses sums to zero. You will need to come to your own view about where the actual level of collective systemic bias lies for all the pollsters. At the 2010 Election (with a different set of pollsters), the population voting intention was about one percentage point more in the Coalition's favour compared with the pollster average (see here). In light of the 2010 experience, it is arguably plausible to subtract (say) half a percentage point or more from the above aggregation to adjust for the collective systemic bias across all of the polling houses. [As an aside, you will note that Simon Jackman, who seeks to anchor his Bayesian models with respect to the outcome of past elections regularly produces an aggregated poll that tracks well below the vast majority of individual poll results].
If we limit our analysis to Newspoll and Nielsen.
The latest Newspoll
The latest Nielsen
My prediction? Yesterday I thought it might be in the high 50s for the number of seats won by Labor. Today, with this latest suite of polls, I suspect the low 50s for Labor is more likely. But the high 40s cannot be ruled out.
- Morgan 45.5 to 54.5 in the Coalition's favour
- Newspoll 46 to 54 in the Coalition's favour
- Nielsen 46 to 54 in the Coalition's favour
Which gives an aggregation:
At this point in the blog, it is my normal practice to remind people that I anchor the above Bayesian aggregation with the assumption that the net bias across all of the polling houses sums to zero. You will need to come to your own view about where the actual level of collective systemic bias lies for all the pollsters. At the 2010 Election (with a different set of pollsters), the population voting intention was about one percentage point more in the Coalition's favour compared with the pollster average (see here). In light of the 2010 experience, it is arguably plausible to subtract (say) half a percentage point or more from the above aggregation to adjust for the collective systemic bias across all of the polling houses. [As an aside, you will note that Simon Jackman, who seeks to anchor his Bayesian models with respect to the outcome of past elections regularly produces an aggregated poll that tracks well below the vast majority of individual poll results].
If we limit our analysis to Newspoll and Nielsen.
The latest Newspoll
The latest Nielsen
My prediction? Yesterday I thought it might be in the high 50s for the number of seats won by Labor. Today, with this latest suite of polls, I suspect the low 50s for Labor is more likely. But the high 40s cannot be ruled out.
Friday, September 6, 2013
Thursday, September 5, 2013
Betting market update
This morning's 7.30am run revealed a swag of safe Coalition seats where Centrebet is not offering odds at the moment (bottom 13 rows). The results follow.
The summary results (on the favourite wins basis):
Cathy McGowan's chances have improved materially in the seat of Indi. Adam Bandt seems to be doing better in the seat of Melbourne. Clive Palmer's chances look unchanged in Fairfax. Andrew Wilkie looks safe in Denison and Bob Katter looks safe in Kennedy.
| State | Labor | Coalition | Other | current | favourite | change | |
|---|---|---|---|---|---|---|---|
| Brand | WA | 48.0 | 48.0 | 3.9 | Labor | ? | ? |
| Lingiari | NT | 44.4 | 48.1 | 7.5 | Labor | Coalition | TRUE |
| Blair | QLD | 49.0 | 46.5 | 4.5 | Labor | Labor | FALSE |
| Lyons | TAS | 42.8 | 51.7 | 5.5 | Labor | Coalition | TRUE |
| Kingsford Smith | NSW | 43.4 | 52.3 | 4.3 | Labor | Coalition | TRUE |
| Hindmarsh | SA | 52.5 | 43.5 | 4.0 | Labor | Labor | FALSE |
| Capricornia | QLD | 52.8 | 41.5 | 5.7 | Labor | Labor | FALSE |
| Petrie | QLD | 43.4 | 52.9 | 3.7 | Labor | Coalition | TRUE |
| Page | NSW | 53.1 | 41.8 | 5.1 | Labor | Labor | FALSE |
| Indi | VIC | 3.3 | 53.6 | 43.1 | Coalition | Coalition | FALSE |
| McEwen | VIC | 55.4 | 40.3 | 4.3 | Labor | Labor | FALSE |
| Werriwa | NSW | 55.6 | 40.5 | 3.9 | Labor | Labor | FALSE |
| Barton | NSW | 56.4 | 38.0 | 5.6 | Labor | Labor | FALSE |
| Lilley | QLD | 38.0 | 58.3 | 3.7 | Labor | Coalition | TRUE |
| Franklin | TAS | 59.4 | 33.8 | 6.8 | Labor | Labor | FALSE |
| Bendigo | VIC | 62.3 | 31.7 | 5.9 | Labor | Labor | FALSE |
| Melbourne | VIC | 62.8 | 2.6 | 34.6 | Other | Labor | TRUE |
| McMahon | NSW | 64.2 | 32.7 | 3.1 | Labor | Labor | FALSE |
| Moreton | QLD | 30.3 | 65.0 | 4.7 | Labor | Coalition | TRUE |
| Eden-Monaro | NSW | 30.4 | 65.3 | 4.3 | Labor | Coalition | TRUE |
| Richmond | NSW | 66.1 | 26.8 | 7.1 | Labor | Labor | FALSE |
| Parramatta | NSW | 27.3 | 67.1 | 5.6 | Labor | Coalition | TRUE |
| Brisbane | QLD | 27.5 | 67.8 | 4.7 | Coalition | Coalition | FALSE |
| Rankin | QLD | 69.4 | 26.1 | 4.5 | Labor | Labor | FALSE |
| Chisholm | VIC | 69.4 | 24.8 | 5.8 | Labor | Labor | FALSE |
| Griffith | QLD | 70.3 | 24.4 | 5.3 | Labor | Labor | FALSE |
| Flynn | QLD | 22.8 | 70.9 | 6.3 | Coalition | Coalition | FALSE |
| Bruce | VIC | 70.9 | 22.8 | 6.3 | Labor | Labor | FALSE |
| Bonner | QLD | 21.9 | 73.0 | 5.1 | Coalition | Coalition | FALSE |
| La Trobe | VIC | 20.5 | 74.0 | 5.5 | Labor | Coalition | TRUE |
| Wakefield | SA | 74.2 | 20.6 | 5.2 | Labor | Labor | FALSE |
| Newcastle | NSW | 74.9 | 18.0 | 7.1 | Labor | Labor | FALSE |
| Adelaide | SA | 75.3 | 19.4 | 5.3 | Labor | Labor | FALSE |
| Oxley | QLD | 75.7 | 21.0 | 3.3 | Labor | Labor | FALSE |
| Greenway | NSW | 21.1 | 75.8 | 3.1 | Labor | Coalition | TRUE |
| Solomon | NT | 18.3 | 76.5 | 5.1 | Coalition | Coalition | FALSE |
| Dawson | QLD | 17.5 | 76.6 | 5.9 | Coalition | Coalition | FALSE |
| Dobell | NSW | 15.6 | 76.7 | 7.7 | Other | Coalition | TRUE |
| Melbourne Ports | VIC | 76.9 | 16.4 | 6.8 | Labor | Labor | FALSE |
| Fairfax | QLD | 5.1 | 78.3 | 16.6 | Coalition | Coalition | FALSE |
| Forde | QLD | 16.7 | 78.3 | 5.0 | Coalition | Coalition | FALSE |
| Throsby | NSW | 78.9 | 14.4 | 6.7 | Labor | Labor | FALSE |
| Fisher | QLD | 12.2 | 79.0 | 8.8 | Other | Coalition | TRUE |
| Swan | WA | 16.9 | 79.2 | 3.9 | Coalition | Coalition | FALSE |
| Robertson | NSW | 11.2 | 79.3 | 9.5 | Labor | Coalition | TRUE |
| Fowler | NSW | 79.4 | 16.9 | 3.7 | Labor | Labor | FALSE |
| Chifley | NSW | 79.9 | 14.6 | 5.5 | Labor | Labor | FALSE |
| Perth | WA | 80.0 | 13.3 | 6.7 | Labor | Labor | FALSE |
| Longman | QLD | 14.7 | 80.3 | 5.0 | Coalition | Coalition | FALSE |
| Reid | NSW | 14.8 | 80.5 | 4.8 | Labor | Coalition | TRUE |
| Fremantle | WA | 80.7 | 13.4 | 5.9 | Labor | Labor | FALSE |
| Makin | SA | 81.2 | 14.9 | 4.0 | Labor | Labor | FALSE |
| Hasluck | WA | 15.0 | 81.7 | 3.3 | Coalition | Coalition | FALSE |
| Dunkley | VIC | 10.8 | 82.1 | 7.1 | Coalition | Coalition | FALSE |
| Ryan | QLD | 10.1 | 82.2 | 7.8 | Coalition | Coalition | FALSE |
| Hunter | NSW | 82.2 | 12.6 | 5.2 | Labor | Labor | FALSE |
| Macquarie | NSW | 12.6 | 82.3 | 5.1 | Coalition | Coalition | FALSE |
| Jagajaga | VIC | 82.6 | 11.6 | 5.8 | Labor | Labor | FALSE |
| Braddon | TAS | 12.6 | 82.6 | 4.7 | Labor | Coalition | TRUE |
| Leichhardt | QLD | 10.9 | 82.8 | 6.3 | Coalition | Coalition | FALSE |
| Wright | QLD | 5.6 | 83.0 | 11.4 | Coalition | Coalition | FALSE |
| Hinkler | QLD | 6.5 | 83.1 | 10.4 | Coalition | Coalition | FALSE |
| Herbert | QLD | 11.8 | 83.2 | 5.1 | Coalition | Coalition | FALSE |
| Casey | VIC | 9.6 | 83.3 | 7.1 | Coalition | Coalition | FALSE |
| Blaxland | NSW | 83.3 | 12.7 | 3.9 | Labor | Labor | FALSE |
| Fadden | QLD | 7.7 | 83.5 | 8.7 | Coalition | Coalition | FALSE |
| Ballarat | VIC | 83.9 | 10.3 | 5.9 | Labor | Labor | FALSE |
| Isaacs | VIC | 83.9 | 11.0 | 5.1 | Labor | Labor | FALSE |
| Batman | VIC | 83.9 | 5.7 | 10.4 | Labor | Labor | FALSE |
| Gilmore | NSW | 9.6 | 84.1 | 6.2 | Coalition | Coalition | FALSE |
| Sydney | NSW | 84.3 | 5.7 | 10.1 | Labor | Labor | FALSE |
| Denison | TAS | 10.6 | 5.0 | 84.4 | Other | Other | FALSE |
| Deakin | VIC | 9.2 | 84.5 | 6.4 | Labor | Coalition | TRUE |
| Watson | NSW | 84.6 | 11.1 | 4.4 | Labor | Labor | FALSE |
| Stirling | WA | 8.6 | 84.7 | 6.7 | Coalition | Coalition | FALSE |
| Banks | NSW | 11.1 | 84.7 | 4.2 | Labor | Coalition | TRUE |
| Corangamite | VIC | 9.2 | 84.8 | 6.0 | Labor | Coalition | TRUE |
| Bowman | QLD | 9.2 | 84.9 | 5.9 | Coalition | Coalition | FALSE |
| Shortland | NSW | 85.2 | 9.7 | 5.1 | Labor | Labor | FALSE |
| Bass | TAS | 9.9 | 85.4 | 4.7 | Labor | Coalition | TRUE |
| Cunningham | NSW | 85.4 | 8.7 | 5.9 | Labor | Labor | FALSE |
| Aston | VIC | 8.7 | 85.4 | 5.9 | Coalition | Coalition | FALSE |
| Kooyong | VIC | 6.6 | 85.5 | 7.9 | Coalition | Coalition | FALSE |
| Lalor | VIC | 85.7 | 7.2 | 7.1 | Labor | Labor | FALSE |
| Bennelong | NSW | 9.9 | 85.7 | 4.4 | Coalition | Coalition | FALSE |
| Canning | WA | 9.9 | 85.7 | 4.4 | Coalition | Coalition | FALSE |
| Kingston | SA | 86.0 | 9.3 | 4.7 | Labor | Labor | FALSE |
| McMillan | VIC | 8.0 | 86.0 | 6.0 | Coalition | Coalition | FALSE |
| Lyne | NSW | 8.8 | 86.1 | 5.2 | Other | Coalition | TRUE |
| Canberra | ACT | 86.1 | 8.0 | 5.9 | Labor | Labor | FALSE |
| Dickson | QLD | 8.8 | 86.1 | 5.1 | Coalition | Coalition | FALSE |
| Hume | NSW | 7.3 | 86.3 | 6.4 | Coalition | Coalition | FALSE |
| Corio | VIC | 86.4 | 7.3 | 6.4 | Labor | Labor | FALSE |
| Flinders | VIC | 6.7 | 86.5 | 6.8 | Coalition | Coalition | FALSE |
| Cook | NSW | 6.7 | 86.5 | 6.8 | Coalition | Coalition | FALSE |
| Lindsay | NSW | 9.4 | 86.7 | 3.9 | Labor | Coalition | TRUE |
| Maribyrnong | VIC | 86.8 | 7.3 | 5.9 | Labor | Labor | FALSE |
| Cowan | WA | 8.9 | 86.8 | 4.3 | Coalition | Coalition | FALSE |
| Sturt | SA | 8.0 | 86.8 | 5.1 | Coalition | Coalition | FALSE |
| Higgins | VIC | 6.7 | 86.8 | 6.4 | Coalition | Coalition | FALSE |
| Paterson | NSW | 8.0 | 86.9 | 5.1 | Coalition | Coalition | FALSE |
| McPherson | QLD | 6.8 | 86.9 | 6.3 | Coalition | Coalition | FALSE |
| Grey | SA | 6.8 | 87.0 | 6.3 | Coalition | Coalition | FALSE |
| Gippsland | VIC | 6.8 | 87.0 | 6.2 | Coalition | Coalition | FALSE |
| Barker | SA | 6.8 | 87.1 | 6.2 | Coalition | Coalition | FALSE |
| Calare | NSW | 7.3 | 87.1 | 5.6 | Coalition | Coalition | FALSE |
| Boothby | SA | 8.1 | 87.1 | 4.8 | Coalition | Coalition | FALSE |
| Grayndler | NSW | 87.2 | 5.2 | 7.6 | Labor | Labor | FALSE |
| North Sydney | NSW | 5.9 | 87.2 | 6.9 | Coalition | Coalition | FALSE |
| Goldstein | VIC | 6.8 | 87.3 | 5.9 | Coalition | Coalition | FALSE |
| Scullin | VIC | 87.3 | 6.8 | 5.9 | Labor | Labor | FALSE |
| Moore | WA | 6.8 | 87.3 | 5.9 | Coalition | Coalition | FALSE |
| Holt | VIC | 87.5 | 7.4 | 5.1 | Labor | Labor | FALSE |
| Hotham | VIC | 87.5 | 7.4 | 5.1 | Labor | Labor | FALSE |
| Hughes | NSW | 8.1 | 87.5 | 4.4 | Coalition | Coalition | FALSE |
| Macarthur | NSW | 8.1 | 87.5 | 4.4 | Coalition | Coalition | FALSE |
| Forrest | WA | 6.6 | 87.7 | 5.7 | Coalition | Coalition | FALSE |
| Wide Bay | QLD | 5.9 | 87.7 | 6.4 | Coalition | Coalition | FALSE |
| Warringah | NSW | 5.2 | 87.8 | 7.0 | Coalition | Coalition | FALSE |
| Charlton | NSW | 87.8 | 2.6 | 9.6 | Labor | Labor | FALSE |
| Calwell | VIC | 88.0 | 6.8 | 5.2 | Labor | Labor | FALSE |
| Gorton | VIC | 88.0 | 6.8 | 5.2 | Labor | Labor | FALSE |
| Fraser | ACT | 88.1 | 5.9 | 6.0 | Labor | Labor | FALSE |
| Curtin | WA | 4.2 | 88.1 | 7.7 | Coalition | Coalition | FALSE |
| Gellibrand | VIC | 88.3 | 5.2 | 6.4 | Labor | Labor | FALSE |
| Menzies | VIC | 5.3 | 88.4 | 6.4 | Coalition | Coalition | FALSE |
| Cowper | NSW | 7.5 | 88.6 | 3.9 | Coalition | Coalition | FALSE |
| Mayo | SA | 5.3 | 88.7 | 6.0 | Coalition | Coalition | FALSE |
| Tangney | WA | 6.0 | 88.8 | 5.2 | Coalition | Coalition | FALSE |
| Port Adelaide | SA | 89.1 | 6.0 | 4.9 | Labor | Labor | FALSE |
| Pearce | WA | 5.2 | 89.2 | 5.6 | Coalition | Coalition | FALSE |
| Farrer | NSW | 6.0 | 89.5 | 4.4 | Coalition | Coalition | FALSE |
| Wills | VIC | 89.9 | 3.5 | 6.6 | Labor | Labor | FALSE |
| Kennedy | QLD | 4.1 | 5.1 | 90.8 | Other | Other | FALSE |
| Wannon | VIC | 4.4 | 91.5 | 4.1 | Coalition | Coalition | FALSE |
| O'Connor | WA | 3.3 | 93.0 | 3.7 | Coalition | Coalition | FALSE |
| Durack | WA | 3.3 | 93.9 | 2.8 | Coalition | Coalition | FALSE |
| Berowra | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Bradfield | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Mackellar | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Mitchell | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| New England | NSW | NA | 0.0 | 0.0 | Other | Coalition | TRUE |
| Parkes | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Riverina | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Wentworth | NSW | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Groom | QLD | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Maranoa | QLD | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Moncrieff | QLD | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Mallee | VIC | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
| Murray | VIC | NA | 0.0 | 0.0 | Coalition | Coalition | FALSE |
The summary results (on the favourite wins basis):
| Coalition | Labor | Other | |
|---|---|---|---|
| Seat count | 94.5 | 53.5 | 2 |
Cathy McGowan's chances have improved materially in the seat of Indi. Adam Bandt seems to be doing better in the seat of Melbourne. Clive Palmer's chances look unchanged in Fairfax. Andrew Wilkie looks safe in Denison and Bob Katter looks safe in Kennedy.
Wednesday, September 4, 2013
Wednesday: ReachTEL 48-52
Today's ReachTEL has the Coalition on 52 per cent (down one point
from the previous ReachTEL) and Labor on 48 (up one). In terms of the
primary vote: Palmer United is on 4.4 per cent nationally (and one
guesses, much higher in Queensland).
ReachTEL, alone among pollsters, has Labor on the same TPP as it did when Rudd was initially restored in late June. It will be interesting to see if the other pollsters turn in a late flow to Labor
Moving to the Bayesian aggregation, and we are at one of those turning points where a single data point can significantly affect the aggregation. Will await confirmation from the other polling houses this week.
ReachTEL, alone among pollsters, has Labor on the same TPP as it did when Rudd was initially restored in late June. It will be interesting to see if the other pollsters turn in a late flow to Labor
Moving to the Bayesian aggregation, and we are at one of those turning points where a single data point can significantly affect the aggregation. Will await confirmation from the other polling houses this week.
Tuesday, September 3, 2013
Betting market update
In past 24 hours Centrebet's individual seat market has moved two more seats in the Coalition's favour (on a favourite wins basis).
The individual seat probabilities follow:
If I add probabilities in a similar manner to yesterday, I get
| Coalition | Labor | Other | |
|---|---|---|---|
| Seat count | 93.5 | 54.5 | 2 |
The individual seat probabilities follow:
| State | Labor | Coalition | Other | current | favourite | change | |
|---|---|---|---|---|---|---|---|
| Brand | WA | 48.0 | 48.0 | 3.9 | Labor | ? | ? |
| Lingiari | NT | 44.4 | 48.1 | 7.5 | Labor | Coalition | TRUE |
| Petrie | QLD | 50.0 | 46.2 | 3.8 | Labor | Labor | FALSE |
| Blair | QLD | 50.9 | 44.6 | 4.5 | Labor | Labor | FALSE |
| Lilley | QLD | 44.9 | 51.3 | 3.8 | Labor | Coalition | TRUE |
| Lyons | TAS | 42.8 | 51.7 | 5.5 | Labor | Coalition | TRUE |
| Kingsford Smith | NSW | 43.4 | 52.3 | 4.3 | Labor | Coalition | TRUE |
| Hindmarsh | SA | 52.5 | 43.5 | 4.0 | Labor | Labor | FALSE |
| Capricornia | QLD | 52.8 | 41.5 | 5.7 | Labor | Labor | FALSE |
| Page | NSW | 53.1 | 41.8 | 5.1 | Labor | Labor | FALSE |
| McEwen | VIC | 55.4 | 40.3 | 4.3 | Labor | Labor | FALSE |
| Werriwa | NSW | 57.4 | 38.7 | 3.9 | Labor | Labor | FALSE |
| Franklin | TAS | 59.4 | 33.8 | 6.8 | Labor | Labor | FALSE |
| Barton | NSW | 60.2 | 34.2 | 5.6 | Labor | Labor | FALSE |
| Brisbane | QLD | 32.1 | 63.1 | 4.7 | Coalition | Coalition | FALSE |
| McMahon | NSW | 64.2 | 32.7 | 3.1 | Labor | Labor | FALSE |
| Bendigo | VIC | 64.2 | 29.9 | 5.9 | Labor | Labor | FALSE |
| Moreton | QLD | 30.3 | 65.0 | 4.7 | Labor | Coalition | TRUE |
| Eden-Monaro | NSW | 30.4 | 65.3 | 4.3 | Labor | Coalition | TRUE |
| Indi | VIC | 4.0 | 65.3 | 30.7 | Coalition | Coalition | FALSE |
| Richmond | NSW | 66.1 | 26.8 | 7.1 | Labor | Labor | FALSE |
| Parramatta | NSW | 27.3 | 67.1 | 5.6 | Labor | Coalition | TRUE |
| Flynn | QLD | 24.8 | 68.9 | 6.3 | Coalition | Coalition | FALSE |
| Chisholm | VIC | 69.4 | 24.8 | 5.8 | Labor | Labor | FALSE |
| Rankin | QLD | 70.9 | 24.6 | 4.5 | Labor | Labor | FALSE |
| Bruce | VIC | 72.1 | 21.6 | 6.3 | Labor | Labor | FALSE |
| Griffith | QLD | 72.8 | 21.9 | 5.3 | Labor | Labor | FALSE |
| Melbourne | VIC | 73.0 | 2.6 | 24.5 | Other | Labor | TRUE |
| Bonner | QLD | 21.9 | 73.0 | 5.1 | Coalition | Coalition | FALSE |
| La Trobe | VIC | 20.5 | 74.0 | 5.5 | Labor | Coalition | TRUE |
| Wakefield | SA | 74.2 | 20.6 | 5.2 | Labor | Labor | FALSE |
| Newcastle | NSW | 74.9 | 18.0 | 7.1 | Labor | Labor | FALSE |
| Adelaide | SA | 75.3 | 19.4 | 5.3 | Labor | Labor | FALSE |
| Dobell | NSW | 16.5 | 75.8 | 7.7 | Other | Coalition | TRUE |
| Greenway | NSW | 21.1 | 75.8 | 3.1 | Labor | Coalition | TRUE |
| Solomon | NT | 18.3 | 76.5 | 5.1 | Coalition | Coalition | FALSE |
| Dawson | QLD | 17.5 | 76.6 | 5.9 | Coalition | Coalition | FALSE |
| Melbourne Ports | VIC | 76.9 | 16.4 | 6.8 | Labor | Labor | FALSE |
| Robertson | NSW | 12.0 | 77.9 | 10.1 | Labor | Coalition | TRUE |
| Fairfax | QLD | 5.1 | 78.3 | 16.6 | Coalition | Coalition | FALSE |
| Forde | QLD | 16.7 | 78.3 | 5.0 | Coalition | Coalition | FALSE |
| Longman | QLD | 16.7 | 78.3 | 5.0 | Coalition | Coalition | FALSE |
| Oxley | QLD | 78.7 | 18.0 | 3.3 | Labor | Labor | FALSE |
| Throsby | NSW | 78.9 | 14.4 | 6.7 | Labor | Labor | FALSE |
| Fisher | QLD | 12.2 | 79.0 | 8.8 | Other | Coalition | TRUE |
| Swan | WA | 16.9 | 79.2 | 3.9 | Coalition | Coalition | FALSE |
| Fowler | NSW | 79.4 | 16.9 | 3.7 | Labor | Labor | FALSE |
| Chifley | NSW | 79.9 | 14.6 | 5.5 | Labor | Labor | FALSE |
| Perth | WA | 80.0 | 13.3 | 6.7 | Labor | Labor | FALSE |
| Reid | NSW | 14.8 | 80.5 | 4.8 | Labor | Coalition | TRUE |
| Braddon | TAS | 14.8 | 80.5 | 4.7 | Labor | Coalition | TRUE |
| Fremantle | WA | 80.7 | 13.4 | 5.9 | Labor | Labor | FALSE |
| Makin | SA | 81.2 | 14.9 | 4.0 | Labor | Labor | FALSE |
| Hasluck | WA | 15.0 | 81.7 | 3.3 | Coalition | Coalition | FALSE |
| Casey | VIC | 10.8 | 82.1 | 7.1 | Coalition | Coalition | FALSE |
| Dunkley | VIC | 10.8 | 82.1 | 7.1 | Coalition | Coalition | FALSE |
| Ryan | QLD | 10.1 | 82.2 | 7.8 | Coalition | Coalition | FALSE |
| Hunter | NSW | 82.2 | 12.6 | 5.2 | Labor | Labor | FALSE |
| Macquarie | NSW | 12.6 | 82.3 | 5.1 | Coalition | Coalition | FALSE |
| Jagajaga | VIC | 82.6 | 11.6 | 5.8 | Labor | Labor | FALSE |
| Leichhardt | QLD | 10.9 | 82.8 | 6.3 | Coalition | Coalition | FALSE |
| Wright | QLD | 5.6 | 83.0 | 11.4 | Coalition | Coalition | FALSE |
| Hinkler | QLD | 6.5 | 83.1 | 10.4 | Coalition | Coalition | FALSE |
| Herbert | QLD | 11.8 | 83.2 | 5.1 | Coalition | Coalition | FALSE |
| Blaxland | NSW | 83.3 | 12.7 | 3.9 | Labor | Labor | FALSE |
| Bass | TAS | 11.8 | 83.5 | 4.7 | Labor | Coalition | TRUE |
| Fadden | QLD | 7.7 | 83.5 | 8.7 | Coalition | Coalition | FALSE |
| Ballarat | VIC | 83.9 | 10.3 | 5.9 | Labor | Labor | FALSE |
| Isaacs | VIC | 83.9 | 11.0 | 5.1 | Labor | Labor | FALSE |
| Batman | VIC | 83.9 | 5.7 | 10.4 | Labor | Labor | FALSE |
| Sydney | NSW | 84.3 | 5.7 | 10.1 | Labor | Labor | FALSE |
| Denison | TAS | 10.6 | 5.0 | 84.4 | Other | Other | FALSE |
| Deakin | VIC | 9.2 | 84.5 | 6.4 | Labor | Coalition | TRUE |
| Watson | NSW | 84.6 | 11.1 | 4.4 | Labor | Labor | FALSE |
| Stirling | WA | 8.6 | 84.7 | 6.7 | Coalition | Coalition | FALSE |
| Banks | NSW | 11.1 | 84.7 | 4.2 | Labor | Coalition | TRUE |
| Corangamite | VIC | 9.2 | 84.8 | 6.0 | Labor | Coalition | TRUE |
| Bowman | QLD | 9.2 | 84.9 | 5.9 | Coalition | Coalition | FALSE |
| Shortland | NSW | 85.2 | 9.7 | 5.1 | Labor | Labor | FALSE |
| Cunningham | NSW | 85.4 | 8.7 | 5.9 | Labor | Labor | FALSE |
| Aston | VIC | 8.7 | 85.4 | 5.9 | Coalition | Coalition | FALSE |
| Kooyong | VIC | 6.6 | 85.5 | 7.9 | Coalition | Coalition | FALSE |
| Lalor | VIC | 85.7 | 7.2 | 7.1 | Labor | Labor | FALSE |
| Bennelong | NSW | 9.9 | 85.7 | 4.4 | Coalition | Coalition | FALSE |
| Canning | WA | 9.9 | 85.7 | 4.4 | Coalition | Coalition | FALSE |
| Gilmore | NSW | 8.0 | 85.8 | 6.3 | Coalition | Coalition | FALSE |
| Berowra | NSW | 6.7 | 85.8 | 7.5 | Coalition | Coalition | FALSE |
| Kingston | SA | 86.0 | 9.3 | 4.7 | Labor | Labor | FALSE |
| McMillan | VIC | 8.0 | 86.0 | 6.0 | Coalition | Coalition | FALSE |
| Lyne | NSW | 8.8 | 86.1 | 5.2 | Other | Coalition | TRUE |
| Canberra | ACT | 86.1 | 8.0 | 5.9 | Labor | Labor | FALSE |
| Dickson | QLD | 8.8 | 86.1 | 5.1 | Coalition | Coalition | FALSE |
| Hume | NSW | 7.3 | 86.3 | 6.4 | Coalition | Coalition | FALSE |
| Corio | VIC | 86.4 | 7.3 | 6.4 | Labor | Labor | FALSE |
| Flinders | VIC | 6.7 | 86.5 | 6.8 | Coalition | Coalition | FALSE |
| Cook | NSW | 6.7 | 86.5 | 6.8 | Coalition | Coalition | FALSE |
| Lindsay | NSW | 9.4 | 86.7 | 3.9 | Labor | Coalition | TRUE |
| Wentworth | NSW | 5.1 | 86.7 | 8.2 | Coalition | Coalition | FALSE |
| Maribyrnong | VIC | 86.8 | 7.3 | 5.9 | Labor | Labor | FALSE |
| Cowan | WA | 8.9 | 86.8 | 4.3 | Coalition | Coalition | FALSE |
| Sturt | SA | 8.0 | 86.8 | 5.1 | Coalition | Coalition | FALSE |
| Higgins | VIC | 6.7 | 86.8 | 6.4 | Coalition | Coalition | FALSE |
| Paterson | NSW | 8.0 | 86.9 | 5.1 | Coalition | Coalition | FALSE |
| McPherson | QLD | 6.8 | 86.9 | 6.3 | Coalition | Coalition | FALSE |
| Grey | SA | 6.8 | 87.0 | 6.3 | Coalition | Coalition | FALSE |
| Gippsland | VIC | 6.8 | 87.0 | 6.2 | Coalition | Coalition | FALSE |
| Barker | SA | 6.8 | 87.1 | 6.2 | Coalition | Coalition | FALSE |
| Calare | NSW | 7.3 | 87.1 | 5.6 | Coalition | Coalition | FALSE |
| Boothby | SA | 8.1 | 87.1 | 4.8 | Coalition | Coalition | FALSE |
| Bradfield | NSW | 5.9 | 87.2 | 6.9 | Coalition | Coalition | FALSE |
| Grayndler | NSW | 87.2 | 5.2 | 7.6 | Labor | Labor | FALSE |
| Mackellar | NSW | 5.2 | 87.2 | 7.6 | Coalition | Coalition | FALSE |
| North Sydney | NSW | 5.9 | 87.2 | 6.9 | Coalition | Coalition | FALSE |
| Goldstein | VIC | 6.8 | 87.3 | 5.9 | Coalition | Coalition | FALSE |
| Scullin | VIC | 87.3 | 6.8 | 5.9 | Labor | Labor | FALSE |
| Moore | WA | 6.8 | 87.3 | 5.9 | Coalition | Coalition | FALSE |
| Holt | VIC | 87.5 | 7.4 | 5.1 | Labor | Labor | FALSE |
| Hotham | VIC | 87.5 | 7.4 | 5.1 | Labor | Labor | FALSE |
| Hughes | NSW | 8.1 | 87.5 | 4.4 | Coalition | Coalition | FALSE |
| Macarthur | NSW | 8.1 | 87.5 | 4.4 | Coalition | Coalition | FALSE |
| Forrest | WA | 6.6 | 87.7 | 5.7 | Coalition | Coalition | FALSE |
| Wide Bay | QLD | 5.9 | 87.7 | 6.4 | Coalition | Coalition | FALSE |
| Mallee | VIC | 6.8 | 87.7 | 5.4 | Coalition | Coalition | FALSE |
| Warringah | NSW | 5.2 | 87.8 | 7.0 | Coalition | Coalition | FALSE |
| Charlton | NSW | 87.8 | 2.6 | 9.6 | Labor | Labor | FALSE |
| Moncrieff | QLD | 6.9 | 87.9 | 5.2 | Coalition | Coalition | FALSE |
| Calwell | VIC | 88.0 | 6.8 | 5.2 | Labor | Labor | FALSE |
| Gorton | VIC | 88.0 | 6.8 | 5.2 | Labor | Labor | FALSE |
| Fraser | ACT | 88.1 | 5.9 | 6.0 | Labor | Labor | FALSE |
| Curtin | WA | 4.2 | 88.1 | 7.7 | Coalition | Coalition | FALSE |
| Murray | VIC | 6.8 | 88.1 | 5.0 | Coalition | Coalition | FALSE |
| New England | NSW | 4.2 | 88.2 | 7.5 | Other | Coalition | TRUE |
| Gellibrand | VIC | 88.3 | 5.2 | 6.4 | Labor | Labor | FALSE |
| Menzies | VIC | 5.3 | 88.4 | 6.4 | Coalition | Coalition | FALSE |
| Cowper | NSW | 7.5 | 88.6 | 3.9 | Coalition | Coalition | FALSE |
| Maranoa | QLD | 5.3 | 88.7 | 6.0 | Coalition | Coalition | FALSE |
| Mayo | SA | 5.3 | 88.7 | 6.0 | Coalition | Coalition | FALSE |
| Mitchell | NSW | 6.9 | 88.7 | 4.4 | Coalition | Coalition | FALSE |
| Parkes | NSW | 6.9 | 88.7 | 4.4 | Coalition | Coalition | FALSE |
| Tangney | WA | 6.0 | 88.8 | 5.2 | Coalition | Coalition | FALSE |
| Port Adelaide | SA | 89.1 | 6.0 | 4.9 | Labor | Labor | FALSE |
| Riverina | NSW | 6.9 | 89.1 | 4.0 | Coalition | Coalition | FALSE |
| Pearce | WA | 5.2 | 89.2 | 5.6 | Coalition | Coalition | FALSE |
| Farrer | NSW | 6.0 | 89.5 | 4.4 | Coalition | Coalition | FALSE |
| Wills | VIC | 89.9 | 3.5 | 6.6 | Labor | Labor | FALSE |
| Groom | QLD | 6.1 | 90.5 | 3.4 | Coalition | Coalition | FALSE |
| Kennedy | QLD | 4.1 | 5.1 | 90.8 | Other | Other | FALSE |
| Wannon | VIC | 4.4 | 91.5 | 4.1 | Coalition | Coalition | FALSE |
| O'Connor | WA | 3.3 | 93.0 | 3.7 | Coalition | Coalition | FALSE |
| Durack | WA | 3.3 | 93.9 | 2.8 | Coalition | Coalition | FALSE |
If I add probabilities in a similar manner to yesterday, I get
| Coalition | Labor | Other | |
|---|---|---|---|
| Seat count | 96 | 52 | 2 |
Monday, September 2, 2013
Monday evening update
Essential has released its latest poll data (recasting the four previous rolling fortnights as weekly data). While the pathway differs a little, the endpoint is in the middle of the pack.
Turning to the betting market: in aggregate, today's result (on a favourite-wins basis) is unchanged on Saturday's update.
The individual seat probabilities follow (expressed as a percent). Of note: Cathy McGowan (Independent) seems to be improving her odds in Indi.
If, rather than count favourites, we add probabilities to see the likely outcome (and make the odd adjustment), we get the following outcome:
And (for transparency) my adjusted calculations for adding probabilities (again expressed as percentages) follow:
Turning to the betting market: in aggregate, today's result (on a favourite-wins basis) is unchanged on Saturday's update.
| Coalition | Labor | Other | |
|---|---|---|---|
| Seat count | 91 | 57 | 2 |
The individual seat probabilities follow (expressed as a percent). Of note: Cathy McGowan (Independent) seems to be improving her odds in Indi.
| State | Labor | Coalition | Other | current | favourite | change | |
|---|---|---|---|---|---|---|---|
| Lingiari | NT | 46.9 | 45.6 | 7.5 | Labor | Labor | FALSE |
| Brand | WA | 46.1 | 49.9 | 4.0 | Labor | Coalition | TRUE |
| Kingsford Smith | NSW | 50.5 | 45.3 | 4.3 | Labor | Labor | FALSE |
| Lyons | TAS | 42.8 | 51.7 | 5.5 | Labor | Coalition | TRUE |
| Lilley | QLD | 52.6 | 43.6 | 3.7 | Labor | Labor | FALSE |
| Hindmarsh | SA | 53.8 | 42.3 | 3.9 | Labor | Labor | FALSE |
| Blair | QLD | 54.2 | 42.6 | 3.3 | Labor | Labor | FALSE |
| Petrie | QLD | 54.8 | 42.1 | 3.1 | Labor | Labor | FALSE |
| Capricornia | QLD | 56.3 | 37.9 | 5.7 | Labor | Labor | FALSE |
| Page | NSW | 56.7 | 38.2 | 5.1 | Labor | Labor | FALSE |
| McEwen | VIC | 57.1 | 38.5 | 4.3 | Labor | Labor | FALSE |
| Werriwa | NSW | 57.4 | 38.7 | 3.9 | Labor | Labor | FALSE |
| Franklin | TAS | 59.4 | 33.8 | 6.8 | Labor | Labor | FALSE |
| Barton | NSW | 60.2 | 34.2 | 5.6 | Labor | Labor | FALSE |
| Brisbane | QLD | 34.5 | 60.8 | 4.7 | Coalition | Coalition | FALSE |
| Parramatta | NSW | 31.8 | 62.6 | 5.6 | Labor | Coalition | TRUE |
| Moreton | QLD | 32.1 | 63.1 | 4.7 | Labor | Coalition | TRUE |
| McMahon | NSW | 64.2 | 32.7 | 3.1 | Labor | Labor | FALSE |
| Bendigo | VIC | 64.2 | 29.9 | 5.9 | Labor | Labor | FALSE |
| Eden-Monaro | NSW | 30.4 | 65.3 | 4.3 | Labor | Coalition | TRUE |
| Indi | VIC | 4.0 | 65.3 | 30.7 | Coalition | Coalition | FALSE |
| Richmond | NSW | 66.1 | 26.8 | 7.1 | Labor | Labor | FALSE |
| Flynn | QLD | 24.8 | 68.9 | 6.3 | Coalition | Coalition | FALSE |
| Chisholm | VIC | 69.4 | 24.8 | 5.8 | Labor | Labor | FALSE |
| Bruce | VIC | 72.1 | 21.6 | 6.3 | Labor | Labor | FALSE |
| Griffith | QLD | 72.8 | 21.9 | 5.3 | Labor | Labor | FALSE |
| Melbourne | VIC | 73.0 | 2.6 | 24.5 | Other | Labor | TRUE |
| Rankin | QLD | 73.5 | 22.0 | 4.5 | Labor | Labor | FALSE |
| Bonner | QLD | 22.1 | 73.6 | 4.3 | Coalition | Coalition | FALSE |
| La Trobe | VIC | 20.5 | 74.0 | 5.5 | Labor | Coalition | TRUE |
| Hasluck | WA | 22.3 | 74.4 | 3.3 | Coalition | Coalition | FALSE |
| Newcastle | NSW | 74.9 | 18.0 | 7.1 | Labor | Labor | FALSE |
| Dobell | NSW | 16.5 | 75.8 | 7.7 | Other | Coalition | TRUE |
| Greenway | NSW | 21.1 | 75.8 | 3.1 | Labor | Coalition | TRUE |
| Solomon | NT | 18.3 | 76.5 | 5.1 | Coalition | Coalition | FALSE |
| Wakefield | SA | 76.6 | 17.5 | 5.9 | Labor | Labor | FALSE |
| Dawson | QLD | 17.5 | 76.6 | 5.9 | Coalition | Coalition | FALSE |
| Melbourne Ports | VIC | 76.9 | 16.4 | 6.8 | Labor | Labor | FALSE |
| Adelaide | SA | 77.4 | 16.5 | 6.1 | Labor | Labor | FALSE |
| Perth | WA | 77.8 | 15.6 | 6.6 | Labor | Labor | FALSE |
| Robertson | NSW | 12.0 | 77.9 | 10.1 | Labor | Coalition | TRUE |
| Forde | QLD | 16.7 | 78.3 | 5.0 | Coalition | Coalition | FALSE |
| Longman | QLD | 16.7 | 78.3 | 5.0 | Coalition | Coalition | FALSE |
| Oxley | QLD | 78.7 | 18.0 | 3.3 | Labor | Labor | FALSE |
| Throsby | NSW | 78.9 | 14.4 | 6.7 | Labor | Labor | FALSE |
| Fisher | QLD | 12.2 | 79.0 | 8.8 | Other | Coalition | TRUE |
| Leichhardt | QLD | 14.5 | 79.2 | 6.3 | Coalition | Coalition | FALSE |
| Swan | WA | 16.9 | 79.2 | 3.9 | Coalition | Coalition | FALSE |
| Fowler | NSW | 79.4 | 16.9 | 3.7 | Labor | Labor | FALSE |
| Chifley | NSW | 79.9 | 14.6 | 5.5 | Labor | Labor | FALSE |
| Fairfax | QLD | 5.1 | 80.4 | 14.5 | Coalition | Coalition | FALSE |
| Reid | NSW | 14.8 | 80.5 | 4.8 | Labor | Coalition | TRUE |
| Braddon | TAS | 14.8 | 80.5 | 4.7 | Labor | Coalition | TRUE |
| Fremantle | WA | 80.7 | 13.4 | 5.9 | Labor | Labor | FALSE |
| Makin | SA | 81.2 | 14.9 | 4.0 | Labor | Labor | FALSE |
| Casey | VIC | 10.8 | 82.1 | 7.1 | Coalition | Coalition | FALSE |
| Dunkley | VIC | 10.8 | 82.1 | 7.1 | Coalition | Coalition | FALSE |
| Ryan | QLD | 10.1 | 82.2 | 7.8 | Coalition | Coalition | FALSE |
| Herbert | QLD | 12.7 | 82.2 | 5.1 | Coalition | Coalition | FALSE |
| Hunter | NSW | 82.2 | 12.6 | 5.2 | Labor | Labor | FALSE |
| Macquarie | NSW | 12.6 | 82.3 | 5.1 | Coalition | Coalition | FALSE |
| Jagajaga | VIC | 82.6 | 11.6 | 5.8 | Labor | Labor | FALSE |
| Wright | QLD | 5.6 | 83.0 | 11.4 | Coalition | Coalition | FALSE |
| Hinkler | QLD | 6.5 | 83.1 | 10.4 | Coalition | Coalition | FALSE |
| Blaxland | NSW | 83.3 | 12.7 | 3.9 | Labor | Labor | FALSE |
| Bass | TAS | 11.8 | 83.5 | 4.7 | Labor | Coalition | TRUE |
| Fadden | QLD | 7.7 | 83.5 | 8.7 | Coalition | Coalition | FALSE |
| Ballarat | VIC | 83.9 | 10.3 | 5.9 | Labor | Labor | FALSE |
| Isaacs | VIC | 83.9 | 11.0 | 5.1 | Labor | Labor | FALSE |
| Batman | VIC | 83.9 | 5.7 | 10.4 | Labor | Labor | FALSE |
| Sydney | NSW | 84.3 | 5.7 | 10.1 | Labor | Labor | FALSE |
| Denison | TAS | 10.6 | 5.0 | 84.4 | Other | Other | FALSE |
| Deakin | VIC | 9.2 | 84.5 | 6.4 | Labor | Coalition | TRUE |
| Watson | NSW | 84.6 | 11.1 | 4.4 | Labor | Labor | FALSE |
| Stirling | WA | 8.6 | 84.7 | 6.7 | Coalition | Coalition | FALSE |
| Banks | NSW | 11.1 | 84.7 | 4.2 | Labor | Coalition | TRUE |
| Corangamite | VIC | 9.2 | 84.8 | 6.0 | Labor | Coalition | TRUE |
| Shortland | NSW | 85.2 | 9.7 | 5.1 | Labor | Labor | FALSE |
| Cunningham | NSW | 85.4 | 8.7 | 5.9 | Labor | Labor | FALSE |
| Aston | VIC | 8.7 | 85.4 | 5.9 | Coalition | Coalition | FALSE |
| Kooyong | VIC | 6.6 | 85.5 | 7.9 | Coalition | Coalition | FALSE |
| Bowman | QLD | 9.3 | 85.6 | 5.1 | Coalition | Coalition | FALSE |
| Lalor | VIC | 85.7 | 7.2 | 7.1 | Labor | Labor | FALSE |
| Bennelong | NSW | 9.9 | 85.7 | 4.4 | Coalition | Coalition | FALSE |
| Canning | WA | 9.9 | 85.7 | 4.4 | Coalition | Coalition | FALSE |
| Gilmore | NSW | 8.0 | 85.8 | 6.3 | Coalition | Coalition | FALSE |
| Berowra | NSW | 6.7 | 85.8 | 7.5 | Coalition | Coalition | FALSE |
| Kingston | SA | 86.0 | 9.3 | 4.7 | Labor | Labor | FALSE |
| McMillan | VIC | 8.0 | 86.0 | 6.0 | Coalition | Coalition | FALSE |
| Lyne | NSW | 8.8 | 86.1 | 5.2 | Other | Coalition | TRUE |
| Canberra | ACT | 86.1 | 8.0 | 5.9 | Labor | Labor | FALSE |
| Dickson | QLD | 8.8 | 86.1 | 5.1 | Coalition | Coalition | FALSE |
| Hume | NSW | 7.3 | 86.3 | 6.4 | Coalition | Coalition | FALSE |
| Corio | VIC | 86.4 | 7.3 | 6.4 | Labor | Labor | FALSE |
| Flinders | VIC | 6.7 | 86.5 | 6.8 | Coalition | Coalition | FALSE |
| Cook | NSW | 6.7 | 86.5 | 6.8 | Coalition | Coalition | FALSE |
| Lindsay | NSW | 9.4 | 86.7 | 3.9 | Labor | Coalition | TRUE |
| Wentworth | NSW | 5.1 | 86.7 | 8.2 | Coalition | Coalition | FALSE |
| Maribyrnong | VIC | 86.8 | 7.3 | 5.9 | Labor | Labor | FALSE |
| Cowan | WA | 8.9 | 86.8 | 4.3 | Coalition | Coalition | FALSE |
| Sturt | SA | 8.0 | 86.8 | 5.1 | Coalition | Coalition | FALSE |
| Higgins | VIC | 6.7 | 86.8 | 6.4 | Coalition | Coalition | FALSE |
| Paterson | NSW | 8.0 | 86.9 | 5.1 | Coalition | Coalition | FALSE |
| McPherson | QLD | 6.8 | 86.9 | 6.3 | Coalition | Coalition | FALSE |
| Grey | SA | 6.8 | 87.0 | 6.3 | Coalition | Coalition | FALSE |
| Gippsland | VIC | 6.8 | 87.0 | 6.2 | Coalition | Coalition | FALSE |
| Barker | SA | 6.8 | 87.1 | 6.2 | Coalition | Coalition | FALSE |
| Calare | NSW | 7.3 | 87.1 | 5.6 | Coalition | Coalition | FALSE |
| Boothby | SA | 8.1 | 87.1 | 4.8 | Coalition | Coalition | FALSE |
| Bradfield | NSW | 5.9 | 87.2 | 6.9 | Coalition | Coalition | FALSE |
| Grayndler | NSW | 87.2 | 5.2 | 7.6 | Labor | Labor | FALSE |
| Mackellar | NSW | 5.2 | 87.2 | 7.6 | Coalition | Coalition | FALSE |
| North Sydney | NSW | 5.9 | 87.2 | 6.9 | Coalition | Coalition | FALSE |
| Goldstein | VIC | 6.8 | 87.3 | 5.9 | Coalition | Coalition | FALSE |
| Scullin | VIC | 87.3 | 6.8 | 5.9 | Labor | Labor | FALSE |
| Moore | WA | 6.8 | 87.3 | 5.9 | Coalition | Coalition | FALSE |
| Holt | VIC | 87.5 | 7.4 | 5.1 | Labor | Labor | FALSE |
| Hotham | VIC | 87.5 | 7.4 | 5.1 | Labor | Labor | FALSE |
| Hughes | NSW | 8.1 | 87.5 | 4.4 | Coalition | Coalition | FALSE |
| Macarthur | NSW | 8.1 | 87.5 | 4.4 | Coalition | Coalition | FALSE |
| Forrest | WA | 6.6 | 87.7 | 5.7 | Coalition | Coalition | FALSE |
| Wide Bay | QLD | 5.9 | 87.7 | 6.4 | Coalition | Coalition | FALSE |
| Mallee | VIC | 6.8 | 87.7 | 5.4 | Coalition | Coalition | FALSE |
| Warringah | NSW | 5.2 | 87.8 | 7.0 | Coalition | Coalition | FALSE |
| Charlton | NSW | 87.8 | 2.6 | 9.6 | Labor | Labor | FALSE |
| Moncrieff | QLD | 6.9 | 87.9 | 5.2 | Coalition | Coalition | FALSE |
| Calwell | VIC | 88.0 | 6.8 | 5.2 | Labor | Labor | FALSE |
| Gorton | VIC | 88.0 | 6.8 | 5.2 | Labor | Labor | FALSE |
| Fraser | ACT | 88.1 | 5.9 | 6.0 | Labor | Labor | FALSE |
| Curtin | WA | 4.2 | 88.1 | 7.7 | Coalition | Coalition | FALSE |
| Murray | VIC | 6.8 | 88.1 | 5.0 | Coalition | Coalition | FALSE |
| New England | NSW | 4.2 | 88.2 | 7.5 | Other | Coalition | TRUE |
| Gellibrand | VIC | 88.3 | 5.2 | 6.4 | Labor | Labor | FALSE |
| Menzies | VIC | 5.3 | 88.4 | 6.4 | Coalition | Coalition | FALSE |
| Cowper | NSW | 7.5 | 88.6 | 3.9 | Coalition | Coalition | FALSE |
| Mayo | SA | 5.3 | 88.7 | 6.0 | Coalition | Coalition | FALSE |
| Mitchell | NSW | 6.9 | 88.7 | 4.4 | Coalition | Coalition | FALSE |
| Parkes | NSW | 6.9 | 88.7 | 4.4 | Coalition | Coalition | FALSE |
| Tangney | WA | 6.0 | 88.8 | 5.2 | Coalition | Coalition | FALSE |
| Port Adelaide | SA | 89.1 | 6.0 | 4.9 | Labor | Labor | FALSE |
| Riverina | NSW | 6.9 | 89.1 | 4.0 | Coalition | Coalition | FALSE |
| Pearce | WA | 5.2 | 89.2 | 5.6 | Coalition | Coalition | FALSE |
| Maranoa | QLD | 5.3 | 89.4 | 5.2 | Coalition | Coalition | FALSE |
| Farrer | NSW | 6.0 | 89.5 | 4.4 | Coalition | Coalition | FALSE |
| Wills | VIC | 89.9 | 3.5 | 6.6 | Labor | Labor | FALSE |
| Groom | QLD | 6.1 | 90.5 | 3.4 | Coalition | Coalition | FALSE |
| Kennedy | QLD | 4.1 | 5.1 | 90.8 | Other | Other | FALSE |
| Wannon | VIC | 4.4 | 91.5 | 4.1 | Coalition | Coalition | FALSE |
| O'Connor | WA | 3.3 | 93.0 | 3.7 | Coalition | Coalition | FALSE |
| Durack | WA | 3.3 | 93.9 | 2.8 | Coalition | Coalition | FALSE |
If, rather than count favourites, we add probabilities to see the likely outcome (and make the odd adjustment), we get the following outcome:
| Coalition | Labor | Other | |
|---|---|---|---|
| Seat count | 95 | 53 | 2 |
And (for transparency) my adjusted calculations for adding probabilities (again expressed as percentages) follow:
| Labor | Coalition | Other | |
|---|---|---|---|
| Lingiari | 50.7 | 49.3 | 0.0 |
| Brand | 48.0 | 52.0 | 0.0 |
| Kingsford Smith | 52.7 | 47.3 | 0.0 |
| Lyons | 45.3 | 54.7 | 0.0 |
| Lilley | 54.7 | 45.3 | 0.0 |
| Hindmarsh | 56.0 | 44.0 | 0.0 |
| Blair | 56.0 | 44.0 | 0.0 |
| Petrie | 56.6 | 43.4 | 0.0 |
| Capricornia | 59.8 | 40.2 | 0.0 |
| Page | 59.7 | 40.3 | 0.0 |
| McEwen | 59.7 | 40.3 | 0.0 |
| Werriwa | 59.7 | 40.3 | 0.0 |
| Franklin | 63.7 | 36.3 | 0.0 |
| Barton | 63.8 | 36.2 | 0.0 |
| Brisbane | 36.2 | 63.8 | 0.0 |
| Parramatta | 33.7 | 66.3 | 0.0 |
| Moreton | 33.7 | 66.3 | 0.0 |
| McMahon | 66.3 | 33.7 | 0.0 |
| Bendigo | 68.2 | 31.8 | 0.0 |
| Eden-Monaro | 31.8 | 68.2 | 0.0 |
| Indi | 0.0 | 68.0 | 32.0 |
| Richmond | 71.2 | 28.8 | 0.0 |
| Flynn | 26.5 | 73.5 | 0.0 |
| Chisholm | 73.7 | 26.3 | 0.0 |
| Bruce | 76.9 | 23.1 | 0.0 |
| Griffith | 76.9 | 23.1 | 0.0 |
| Melbourne | 74.9 | 0.0 | 25.1 |
| Rankin | 77.0 | 23.0 | 0.0 |
| Bonner | 23.1 | 76.9 | 0.0 |
| La Trobe | 21.7 | 78.3 | 0.0 |
| Hasluck | 23.1 | 76.9 | 0.0 |
| Newcastle | 80.6 | 19.4 | 0.0 |
| Dobell | 0.0 | 100.0 | 0.0 |
| Greenway | 0.0 | 100.0 | 0.0 |
| Solomon | 0.0 | 100.0 | 0.0 |
| Wakefield | 100.0 | 0.0 | 0.0 |
| Dawson | 0.0 | 100.0 | 0.0 |
| Melbourne Ports | 100.0 | 0.0 | 0.0 |
| Adelaide | 100.0 | 0.0 | 0.0 |
| Perth | 100.0 | 0.0 | 0.0 |
| Robertson | 0.0 | 100.0 | 0.0 |
| Forde | 0.0 | 100.0 | 0.0 |
| Longman | 0.0 | 100.0 | 0.0 |
| Oxley | 100.0 | 0.0 | 0.0 |
| Throsby | 100.0 | 0.0 | 0.0 |
| Fisher | 0.0 | 100.0 | 0.0 |
| Leichhardt | 0.0 | 100.0 | 0.0 |
| Swan | 0.0 | 100.0 | 0.0 |
| Fowler | 100.0 | 0.0 | 0.0 |
| Chifley | 100.0 | 0.0 | 0.0 |
| Fairfax | 0.0 | 100.0 | 0.0 |
| Reid | 0.0 | 100.0 | 0.0 |
| Braddon | 0.0 | 100.0 | 0.0 |
| Fremantle | 100.0 | 0.0 | 0.0 |
| Makin | 100.0 | 0.0 | 0.0 |
| Casey | 0.0 | 100.0 | 0.0 |
| Dunkley | 0.0 | 100.0 | 0.0 |
| Ryan | 0.0 | 100.0 | 0.0 |
| Herbert | 0.0 | 100.0 | 0.0 |
| Hunter | 100.0 | 0.0 | 0.0 |
| Macquarie | 0.0 | 100.0 | 0.0 |
| Jagajaga | 100.0 | 0.0 | 0.0 |
| Wright | 0.0 | 100.0 | 0.0 |
| Hinkler | 0.0 | 100.0 | 0.0 |
| Blaxland | 100.0 | 0.0 | 0.0 |
| Bass | 0.0 | 100.0 | 0.0 |
| Fadden | 0.0 | 100.0 | 0.0 |
| Ballarat | 100.0 | 0.0 | 0.0 |
| Isaacs | 100.0 | 0.0 | 0.0 |
| Batman | 100.0 | 0.0 | 0.0 |
| Sydney | 100.0 | 0.0 | 0.0 |
| Denison | 0.0 | 0.0 | 100.0 |
| Deakin | 0.0 | 100.0 | 0.0 |
| Watson | 100.0 | 0.0 | 0.0 |
| Stirling | 0.0 | 100.0 | 0.0 |
| Banks | 0.0 | 100.0 | 0.0 |
| Corangamite | 0.0 | 100.0 | 0.0 |
| Shortland | 100.0 | 0.0 | 0.0 |
| Cunningham | 100.0 | 0.0 | 0.0 |
| Aston | 0.0 | 100.0 | 0.0 |
| Kooyong | 0.0 | 100.0 | 0.0 |
| Bowman | 0.0 | 100.0 | 0.0 |
| Lalor | 100.0 | 0.0 | 0.0 |
| Bennelong | 0.0 | 100.0 | 0.0 |
| Canning | 0.0 | 100.0 | 0.0 |
| Gilmore | 0.0 | 100.0 | 0.0 |
| Berowra | 0.0 | 100.0 | 0.0 |
| Kingston | 100.0 | 0.0 | 0.0 |
| McMillan | 0.0 | 100.0 | 0.0 |
| Lyne | 0.0 | 100.0 | 0.0 |
| Canberra | 100.0 | 0.0 | 0.0 |
| Dickson | 0.0 | 100.0 | 0.0 |
| Hume | 0.0 | 100.0 | 0.0 |
| Corio | 100.0 | 0.0 | 0.0 |
| Flinders | 0.0 | 100.0 | 0.0 |
| Cook | 0.0 | 100.0 | 0.0 |
| Lindsay | 0.0 | 100.0 | 0.0 |
| Wentworth | 0.0 | 100.0 | 0.0 |
| Maribyrnong | 100.0 | 0.0 | 0.0 |
| Cowan | 0.0 | 100.0 | 0.0 |
| Sturt | 0.0 | 100.0 | 0.0 |
| Higgins | 0.0 | 100.0 | 0.0 |
| Paterson | 0.0 | 100.0 | 0.0 |
| McPherson | 0.0 | 100.0 | 0.0 |
| Grey | 0.0 | 100.0 | 0.0 |
| Gippsland | 0.0 | 100.0 | 0.0 |
| Barker | 0.0 | 100.0 | 0.0 |
| Calare | 0.0 | 100.0 | 0.0 |
| Boothby | 0.0 | 100.0 | 0.0 |
| Bradfield | 0.0 | 100.0 | 0.0 |
| Grayndler | 100.0 | 0.0 | 0.0 |
| Mackellar | 0.0 | 100.0 | 0.0 |
| North Sydney | 0.0 | 100.0 | 0.0 |
| Goldstein | 0.0 | 100.0 | 0.0 |
| Scullin | 100.0 | 0.0 | 0.0 |
| Moore | 0.0 | 100.0 | 0.0 |
| Holt | 100.0 | 0.0 | 0.0 |
| Hotham | 100.0 | 0.0 | 0.0 |
| Hughes | 0.0 | 100.0 | 0.0 |
| Macarthur | 0.0 | 100.0 | 0.0 |
| Forrest | 0.0 | 100.0 | 0.0 |
| Wide Bay | 0.0 | 100.0 | 0.0 |
| Mallee | 0.0 | 100.0 | 0.0 |
| Warringah | 0.0 | 100.0 | 0.0 |
| Charlton | 100.0 | 0.0 | 0.0 |
| Moncrieff | 0.0 | 100.0 | 0.0 |
| Calwell | 100.0 | 0.0 | 0.0 |
| Gorton | 100.0 | 0.0 | 0.0 |
| Fraser | 100.0 | 0.0 | 0.0 |
| Curtin | 0.0 | 100.0 | 0.0 |
| Murray | 0.0 | 100.0 | 0.0 |
| New England | 0.0 | 100.0 | 0.0 |
| Gellibrand | 100.0 | 0.0 | 0.0 |
| Menzies | 0.0 | 100.0 | 0.0 |
| Cowper | 0.0 | 100.0 | 0.0 |
| Mayo | 0.0 | 100.0 | 0.0 |
| Mitchell | 0.0 | 100.0 | 0.0 |
| Parkes | 0.0 | 100.0 | 0.0 |
| Tangney | 0.0 | 100.0 | 0.0 |
| Port Adelaide | 100.0 | 0.0 | 0.0 |
| Riverina | 0.0 | 100.0 | 0.0 |
| Pearce | 0.0 | 100.0 | 0.0 |
| Maranoa | 0.0 | 100.0 | 0.0 |
| Farrer | 0.0 | 100.0 | 0.0 |
| Wills | 100.0 | 0.0 | 0.0 |
| Groom | 0.0 | 100.0 | 0.0 |
| Kennedy | 0.0 | 0.0 | 100.0 |
| Wannon | 0.0 | 100.0 | 0.0 |
| O'Connor | 0.0 | 100.0 | 0.0 |
| Durack | 0.0 | 100.0 | 0.0 |
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