Federal 2028
The House of Representatives has 150 seats, so 76 is more than half. A party with 76 can form government in its own right (the Coalition counts as one party here). Short of that, someone has to win over crossbench MPs, and that is a minority government.
When I say “hung”, I mean that in that pretend election nobody reached 76.
No date has been set. The House must go to an election by late 2028, and a half-Senate election must be held in time for new senators to start on 1 July 2028, so the two usually go together in the first half of 2028.
I assume an election date (shown at the top) to decide how much opinion can still move. Until the date is called, treat everything I say as “if the election were held then, on today’s polling”.
I play the election 50,000 times, each with its own dose of luck: a national polling miss here, a state or local swing there. “6 in 10” means 6 in 10 of those pretend elections.
It’s a way of showing how things could land, not a promise of how they will.
Who wins
how many
Median seats in each party's simulations, with the range covering the middle 80%. The dashed line is the 76 seats needed for a majority in the 150-seat House.
The solid bar ends at the median: half the pretend elections gave that party more seats, half fewer.
The pale stripe covers the middle 80% of runs. One run in ten landed below it and one in ten above. A wide stripe means I’m less sure.
All 150,
seat by seat
Squares are grouped by state, with the big states split into capital and regions; the map shows where each seat is, with close-ups of the capitals. The colour is the favourite; a stronger colour means a surer favourite. Pick a party in the key to see only the seats it is favoured in, or select a seat to find it in the table.
Seats on the edge
All 150 as a table →In each pretend election where a party wins a majority, I line up the seats it won from safest to shakiest. The one in 76th place is that run’s tipping point: lose it and the majority goes.
The seat shown is the one that landed 76th most often, so it’s a good guide to where government is decided.
A fair price is just 1 ÷ the chance. An 80% chance is $1.25. Bookmakers shave that so they make money; mine don’t, because they’re only another way of reading the probability.
They’re not tips or betting advice.
Every seat,
every party
Projected primary vote share in each House of Representatives division. “Coalition” is the Liberal, National, LNP or CLP candidates combined; “Ind” is independents, including the teals; “Other” is everyone else on the ballot, including Katter’s Australian Party and Centre Alliance. A party with a blank cell is not expected to stand. Sort by name or by any party's vote.
Polls only?
Or polls plus?
Every forecast here comes in two versions. Polls only uses the polls, past election results, the candidates standing, preference flows and each electorate's history. Polls + context uses all of that plus a small amount of information about the economy.
Both versions run the same 50,000 simulated elections with the same random numbers. Any difference between them comes from context, not chance.
Why include the economy at all?
Voters judge governments partly on how life is going. Research on Australian federal elections finds that unemployment and inflation move the governing party's vote, by modest amounts; studies of nearly two hundred state elections find the same pattern for state governments.
Why so cautious?
The same research is clear that these effects are small and noisy. Once you account for what voters already think, objective economic data adds little, and some popular beliefs (for instance that interest-rate cuts reward governments) don't hold up in the evidence. So the context adjustment is:
- Small and capped. It can nudge a forecast but never overturn it.
- Uncertain by design. Each simulation draws its own strength for the effect, so context widens the range of outcomes as well as shifting it.
- A prior, not a poll. It adjusts the starting expectation, never the polls themselves.
- Fading. As more good polling arrives, polls take over and context fades towards zero. Close to election day it usually moves the result by only a few tenths of a point.
The specific indicators and how much each counts are not published.
What context changed
The Senate
A half-Senate election fills 40 of the 76 seats: six in each state and both seats in each territory. The 36 state senators elected in 2025 continue. The top row shows the continuing senators and the bottom row the median forecast; the table shows each state. This is a group-level quota approximation, not a full replica of the official count.
The Senate has 76 senators, and 39 is a majority (38 is a tie, and a tied vote fails). State senators serve six-year terms, so half of each state’s twelve are up at a normal election.
With six seats in a state, a group needs one-seventh, about 14.3%, of that state’s vote (one “quota”) to be sure of a seat; in the territories it is a third. Preferences decide the last seats.
The polls
The weighted national poll average each week, with a band covering the middle 80% of plausible values. Dots are individual polls. Polls missing a sample size, dates or question wording are listed but left out of the average.
The line is my best single guess at each party’s vote that week. The band around it covers the middle 80% of plausible values given the polls so far. Wide band, shaky ground.
The dots are the individual polls, which bounce around the line the way polls do.
Some pollsters lean a little one way every time, from how they weight or reach people. Once a pollster has several polls, I estimate that lean against the others and take it off, cautiously, before averaging.
It’s not an accusation, just a habit.
Latest polls in this forecast
How the polls become a forecast
The forecast is built from polls alone. It blends the latest polls with the average of the past year of polling, leaning further towards the latest polls the more good, recent polling there is. Past election results do not pull the national forecast; they decide where each party's vote falls seat by seat.
One poll is a snapshot of a sample of people, and it can miss by a couple of points on luck alone. If I jumped on every new poll, the forecast would lurch about.
So I blend the recent polls with the average of the past year. The more good, recent polling there is, the more the latest ones count.
Which polls count
Published national voting-intention polls for the House of Representatives. A poll needs a sample size, fieldwork dates and a published question so it can be checked; polls missing any of these are listed in the poll table with the reason, but left out of the average. Polls more than a year old are ignored.
How much each poll counts
- Recency. A poll's weight fades smoothly with age, and fades faster in the final six months of the campaign, when opinion is settling.
- Disclosure. Pollsters that meet the Australian Polling Council's full disclosure standard count most; pollsters that publish complete methods without that standard count a little less; polls with only partial methods count much less and are flagged.
- Who paid. A poll commissioned by a party or an interest group is discounted unless it is released in full.
- Sample size. Bigger samples have smaller sampling error, and that is the only way sample size enters. Every poll also carries a floor of non-sampling error, so one very large poll cannot swamp the rest.
- One pollster is one pollster. That error floor is shared across all of a pollster's polls, so ten polls from one firm do not count as ten independent views.
- House effects. Once a pollster has several usable polls, its consistent lean relative to the other pollsters is estimated, cautiously, and removed before averaging.
Recent polls and the past year
- The baseline is the past year of polling, averaged with a long memory, so it reflects where opinion has settled rather than the latest swing. Past election results are used only if there is no polling at all.
- The share given to the latest polls grows with the amount of good, recent polling and with how precise that polling is. The rest goes to the past-year baseline, so a single unusual poll cannot swing the forecast.
- A gap in polling does not erase the polls. If weeks pass with no new poll, the last polls keep their relative weight; the time since then is treated as extra uncertainty.
- Time to election day matters. The further away the election, the more opinion can still move, so the latest polls are a less certain guide and the past-year baseline keeps more weight.
- Every simulation adds error: sampling error, pollster error, movement before election day and a national polling miss shared by every seat.
- Big shifts carry big uncertainty. A party far from its last election result, as One Nation is now, gets wider error in both directions. In past One Nation surges the final polls have been about four points out, sometimes too high and sometimes too low, so the model widens the range rather than pulling the forecast back towards the old result.
From national vote to seats
Each seat starts from its 2025 result (in South Australia, Tasmania and the ACT, which have new boundaries, an estimate of the 2025 result on those boundaries) and moves with the national forecast. Where a poll also reports state results (Newspoll and others publish state breakdowns), the model compares each state's figure with the same poll's national number and shifts each party's vote between states to match, part-way, depending on how many voters in that state were asked. The national totals do not change. One Nation stood in every seat outside the ACT in 2025, so its starting point is real local votes almost everywhere. Until nominations close, each party's chance of standing in a seat is simulated.
Where the forecast differs from the latest polls, it is because the past year of polling differs from the latest polls, not because of past elections. As new polls arrive, the forecast follows them.
Take the data
The forecast files include both models: polls only, and polls + context.
National top line
Chance of a majority in the House of Representatives, chance of having the most seats, projected seats (median and 80% range), national primary vote, and Senate totals.
Seat by seat
Projected primary vote share for ALP, Coalition, Greens, One Nation, independents and Other in all 150 divisions, plus each seat's favourite and its chance of winning.
All tracked polls
Every statewide poll we track, including those that have fallen out of the model (older than a year, or missing sample size, dates or question), with whether each is in the model, why not, and its primary vote.
How it works
- Start from the map. Every seat begins from its 2025 primary vote, which says where each party is strong; the national level comes from the polls.
- Read the polls. Polls are averaged with more weight on recent, larger and better-documented polls, adjusted for each pollster's habitual lean, and steadied by the average of the past year of polling. How the blend works →
- Simulate 50,000 elections. Each simulation draws a national result, then state and regional, neighbouring-seat and local swings, so seats move together the way real seats do.
- Count preferences. House elections use full (compulsory) preferential voting: every ballot numbers every box, so no vote exhausts. Each simulation eliminates candidates one by one and passes on their preferences using the 2025 count, so the final two can be anyone, including One Nation, Greens or independents. In 2025 Coalition candidates were rarely knocked out while One Nation was still in the count, so how Coalition voters rank One Nation is estimated from every 2025 count nationally, with Liberal and National voters pooled. This matters: it is the main reason One Nation can win seats on a primary vote close to Labor's.
- Count the outcomes. A probability is the share of simulations in which something happens. Odds are fair odds with no bookmaker margin.
On the green House ballot you must number every box. If your first choice is knocked out, your vote moves to your next choice, and so on until two candidates are left.
Because every ballot keeps counting to the end, preference flows decide many seats. I count each seat that way in every simulation, so the final two can be any pair.
Polls are noisy and every model is a simplification. A 25% chance happens one time in four.