The Phantom Trend

Like Nate Silver, only less accurate


  • Electorate

  • Party

  • Type

  • Y-axis Range

  • Poll Data

  • Primary Trends To Show


Recent Changes


The Model

These trendlines are fitted using a linear state space model. The underlying state variables are the primary votes for each party in each State and Territory. The model fits a simple local level model to each component, but it uses a factor model for the covariance of each week's innovations. Estimates of national votes and TPPs are made using population weights and last election's state-by-state preference flows.

Each polling source has a fixed house effect in the form of a Gaussian error distribution. Elections are assumed to be perfect observations. I match the timing of each polling sample, so that e.g. Newspoll's quarterly averages are modelled as noisy observations of the underlying data averaged over a quarter.

The complete code and data for the model are available on GitHub.

See Also

There's another statistical polling model over at Mark The Ballot (now back online, woohoo!). The Poll Bludger and Dr Kevin Bonham both publish regularly updated polling aggregates which they put together using their own judgement.


Shouts out to Thomas McMahon who supplied a bunch of this data. And massive thanks to the Poll Bludger and the Ghost Who Votes, who curated the rest.

The Author

I'm Jamie Hall, a data scientist at Kaggle, formerly of the RBA's modelling department. Feel free to drop me a line on Twitter or email if you have comments, questions, suggestions or bug reports.

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