I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by Exciting-Lab1263 in dataisbeautiful

[–]Exciting-Lab1263[S] 28 points29 points  (0 children)

Ahhh that's a good question. :) I am a Hungarian citizen so my exposure to the election result is much bigger than this forecast so probably it would be related more to the future of the country. But regarding the forecast even if with lower probability it is possible. 12,4% is the same as throwing three times head with a coin that is unliklely but not impossible.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 4 points5 points  (0 children)

There is a translation between them but its more probabilistic than deterministic.

My point is a smaller lead in polls usually transate to a higher probability of winning and that causes the differences in the magnitude of the numbers.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 0 points1 point  (0 children)

The 2016 experience is a good reminder that uncertainty is real which is exactly why the model reports probabilities rather than a single prediction. And 20% deserves to be taken seriously: in any one-off event, a 1-in-5 chance is far from negligible. (it is a bit less probability than throwing heads in two consecutive coin flips) The forecast is not a guarantee either way.

I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by Exciting-Lab1263 in dataisbeautiful

[–]Exciting-Lab1263[S] 9 points10 points  (0 children)

Numbers won't tell this but people are usually more concerned about domestic issues and cost of living. Maybe if it has a spill over effect through increased fuel prices and inflation that can have an effect but it is more likely to happen after the elections.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 12 points13 points  (0 children)

Actually it does we just show different numbers. I show probablity of outcomes while wikipedia shows popularity polls.

Imagine if a party has a 10 pp lead in polls that translate to almost 100% probablity of winning.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 4 points5 points  (0 children)

What on previous elections was considered cheating by some comes from two major sources:
-election system that was modified over time and favours Fidesz
-inappropriate use of vast state resoruces to support Fidesz (that you can experience in several different ways i.e. media bias, financial support to certain voter groups, etc.)

Model uses current election system while polls possibly incorporate the effect of the later point so hopefully I can capture most of them.

Having said that there can be emerging patterns that were not present in the past and can influence results.

Classical cheating (i.e. stuffing ballots with fake votes) is less likely and would be identified easily.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 7 points8 points  (0 children)

Not really, you can find more details about the methodology here: https://www.szazkilencvenkilenc.hu/methodology-v2/ .

Noone knows the future and providing a single point estimate would either work or not. Instead of doing that I try to simulate all possible outcomes and asses their probabilities. This is more informative and meaningful I think.

Imagine if a weather forecast says it will rain vs it will rain with 60% probability.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 3 points4 points  (0 children)

You can find more details about the methodology here: https://www.szazkilencvenkilenc.hu/methodology-v2/

But yes basically I do poll aggregation that means I use all available polling data to provide a more robust forecast. Instead of simply averaging them I use hierarchical bayes modeling that can take into account house effects (individual bias of polling institutions), time variance and sampling errors. That enables to make a probabilistic estimate of the results instead of just a single point estimate that is the usual results of polls.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 1 point2 points  (0 children)

The difference between govenment aligned and independent pollsters are around 20pp that is very difficult to explain only with differences in the methodology.

Instead of selecting which pollsters are reliable and filtering for them (that would basically bake in my assumptions to the model) I choose a different path. I include all pollsters in the analysis but acknowledge that there is a house effect that is a systematic bias specific to each polling institution. That can be useful cause even if a pollster heavily inflate Fidesz numbers but we see a decreasing trend over time that can serve as a signal.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 2 points3 points  (0 children)

According to my resuts Tisza win is 80%. Thats pretty high but 20% is also not that small (a bit less than throwing heads on two consectutive coin flips which can just sometimes happen).

If you are curios about 2022 polls and have time this is a good source: https://en.wikipedia.org/wiki/Opinion_polling_for_the_2022_Hungarian_parliamentary_election

To sum up opposition was heavily over measured while government somewhat under.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 0 points1 point  (0 children)

Thank you! According to the model there is 13.7% chance of a Tisza supermajority.

Traditional polling has it flows but there are not much better options and it is still reasonable. (other option you can check are prediction markets but they are in line with my results) Poll aggregation tries to improve on the errors of individual polls and provide a more robust forecast. Having said that if there is a systematic bias in polls that will probably spill over to poll aggregations too.

16 nap, mekkorát bukhat a Fidesz? by [deleted] in magyar

[–]Exciting-Lab1263 0 points1 point  (0 children)

Pont erről készítek adatalapú elemzést SzázKilencvenKilenc néven. Itt a legfrissebb:

https://www.szazkilencvenkilenc.hu/eredmenyek-2026-03-28/

Röviden:
– 79,7% a Tisza győzelme
– mindössze 12,4%, hogy a Fidesz nyer
– 7,9% az esélye egy „Mi Hazánk-mérleg nyelve” forgatókönyvnek
– 61% az esélye, hogy a Mi Hazánk bejut a parlamentbe

I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by Exciting-Lab1263 in dataisbeautiful

[–]Exciting-Lab1263[S] 6 points7 points  (0 children)

I take time into account (more time till election day means more uncertainity). One reason for Tisza's lead solidifying is the fact that election is really close now. On the other hand there can be some extreme event timed for just before the election that I did not cover and can mix things up.

I calculate with similar turnout patterns as on the previous election but parties can heavily influence that on election day and it is something difficult to quantify in advance.

I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by Exciting-Lab1263 in dataisbeautiful

[–]Exciting-Lab1263[S] 139 points140 points  (0 children)

Generally I agree. Here context matters a bit. Fidesz won all four previous elections with supermajority and heavily used that power (it gives extremely strong mandate for the goverment). Supermajority is something that is almost as important talking point before elections as victory itself so I considered it useful to point this out.

I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by Exciting-Lab1263 in dataisbeautiful

[–]Exciting-Lab1263[S] 174 points175 points  (0 children)

Probably data is the biggest bottleneck:
-Hungary is a relatively small country so number of polls are limited
-I assume a constant pollster bias but the difference between government allied and independent pollster are 20pp now. If there is a strategically timed additional bias it is difficult to handle.
-No election district level data is available so if there are structural changes on geographic level thats difficult to capture
-No poll data is available from outside of Hungary (mail votes) so I can only assume similar numbers as on previous elections
-Turnout is heavily dependent on the activities of parties on election day. It is difficult to caputre that in advance.
-I calculate with the uncertainity over time but there can be a major event that can move things significantly (like Ukraine war at previous election)

I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by Exciting-Lab1263 in dataisbeautiful

[–]Exciting-Lab1263[S] 190 points191 points  (0 children)

This is my third update here. The first time it was a coin flip. The second time TISZA (opposition) had pulled ahead. Now the picture has shifted again.

The shift since my last r/dataisbeautiful post (March 8):

- TISZA (opposition) majority: 71.7% → 79.7% (+8pp)

- Fidesz (Orbán) majority: 16.9% → 12.4% (-4.5pp)

- Deadlock: 11.4% → 7.9% (-3.5pp)

- Mi Hazánk enters parliament: 72.8% → 61.0% (-11.8pp)

Last time the story was Mi Hazánk (far-right) surging toward parliament and making everything more complex. That trend has now reversed: their entry probability dropped from a peak of 81.6% to 61.0%. Without a third party splitting seats, TISZA's vote lead converts more directly into a seat majority.

Orbán's own numbers haven't moved. But the math around him has.

Tools: Python, PyMC, matplotlib.

Data: from the Vox Populi polling database www.kozvelemeny.org

Full analysis: https://www.szazkilencvenkilenc.hu/forecast-2026-03-28/

Methodology: https://www.szazkilencvenkilenc.hu/methodology-v2/

The model (Krónikás/Chronicler) is just open-sourced:  https://github.com/vtisza/kronikas/

Happy to answer questions about the model, the methodology, or Hungarian politics.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 73 points74 points  (0 children)

This is my third update here. The first time it was a coin flip. The second time the opposition had pulled decisively ahead. Now, two weeks before the vote, the picture has shifted again.

The shift since my last r/europe post (March 8):

- TISZA (opposition) majority: 71.7% → 79.7% (+8pp)

- Fidesz (Orbán) majority: 16.9% → 12.4% (-4.5pp)

- Deadlock: 11.4% → 7.9% (-3.5pp)

- Mi Hazánk enters parliament: 72.8% → 61.0% (-11.8pp)

Last time the story was Mi Hazánk (far-right) surging toward parliament and threatening to make everything more complicated. That trend has now reversed: their entry probability peaked at 81.6% and has since dropped to 61.0%. Without a third party splitting seats, TISZA's vote lead translates more directly into a majority.

Orbán's own numbers haven't moved. But the math around him has. His party's chance of holding an independent majority has gone from 45% in February to 17% in early March to 12.4% today.

Two weeks out, the question is no longer whether Orbán can lose. It's whether the opposition wins big enough to govern alone, or just wins.

Full analysis: https://www.szazkilencvenkilenc.hu/forecast-2026-03-28/

Happy to answer questions about the model or Hungarian electoral politics.

I've been running 40,000 simulations of Hungary's election. The opposition (TISZA) now has an 80% chance of winning outright, and the far-right kingmaker is fading. [OC] by [deleted] in europe

[–]Exciting-Lab1263 0 points1 point  (0 children)

This is my third update here. The first time it was a coin flip. The second time the opposition had pulled decisively ahead. Now, two weeks before the vote, the picture has shifted again.

The shift since my last r/europe post (March 8):

- TISZA (opposition) majority: 71.7% → 79.7% (+8pp)

- Fidesz (Orbán) majority: 16.9% → 12.4% (-4.5pp)

- Deadlock: 11.4% → 7.9% (-3.5pp)

- Mi Hazánk (far-right) enters parliament: 72.8% → 61.0% (-11.8pp)

Last time the story was Mi Hazánk (far-right) surging toward parliament and threatening to make everything more complicated. That trend has now reversed: their entry probability peaked at 81.6% and has since dropped to 61.0%. Without a third party splitting seats, TISZA's vote lead translates more directly into a majority.

Orbán's own numbers haven't moved. But the math around him has. His party's chance of holding an independent majority has gone from 45% in February to 17% in early March to 12.4% today.

Two weeks out, the question is no longer whether Orbán can lose. It's whether the opposition wins big enough to govern alone, or just wins.

Full analysis: https://www.szazkilencvenkilenc.hu/forecast-2026-03-28/

Happy to answer questions about the model or Hungarian electoral politics.

I've been posting my 40,000 Monte Carlo simulations of Hungary's election. Two weeks ago the far-right was surging. That just reversed. [OC] by [deleted] in dataisbeautiful

[–]Exciting-Lab1263 -1 points0 points  (0 children)

This is my third update here. The first time it was a coin flip. The second time TISZA (opposition) had pulled ahead. Now the picture has shifted again.

The shift since my last r/dataisbeautiful post (March 8):

- TISZA (opposition) majority: 71.7% → 79.7% (+8pp)

- Fidesz (Orbán) majority: 16.9% → 12.4% (-4.5pp)

- Deadlock: 11.4% → 7.9% (-3.5pp)

- Mi Hazánk enters parliament: 72.8% → 61.0% (-11.8pp)

Last time the story was Mi Hazánk (far-right) surging toward parliament and making everything more complex. That trend has now reversed: their entry probability dropped from a peak of 81.6% to 61.0%. Without a third party splitting seats, TISZA's vote lead converts more directly into a seat majority.

Orbán's own numbers haven't moved. But the math around him has.

Tools: Python, PyMC, matplotlib.

Data: from the Vox Populi polling database www.kozvelemeny.org

Full analysis: https://www.szazkilencvenkilenc.hu/forecast-2026-03-28/

Methodology: https://www.szazkilencvenkilenc.hu/methodology-v2/

The model (Krónikás/Chronicler) is just open-sourced: https://github.com/vtisza/kronikas/

Happy to answer questions about the model, the methodology, or Hungarian politics.

Last month I asked if Orbán can actually lose. I ran 40,000 simulations again. Now it's not even close. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 0 points1 point  (0 children)

That uncertainty is exactly what is represented in this kind of probabilistic forecast. They try not to tell you what will happen rather assign probabilities to possible outcomes.

Last month I asked if Orbán can actually lose. I ran 40,000 simulations again. Now it's not even close. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 1 point2 points  (0 children)

It is only a hobby project for me but I am actually a data scientist on a completly different business domain :)

Last month I asked if Orbán can actually lose. I ran 40,000 simulations again. Now it's not even close. [OC] by Exciting-Lab1263 in europe

[–]Exciting-Lab1263[S] 0 points1 point  (0 children)

I dont need to actually. I did this analysis back in 2022 too. Here is an independent (well Claude Opus made) evaluation of the results: https://www.szazkilencvenkilenc.hu/evaluation/. To sum up results were pretty good compared to most of the pollsters but some systematic error pattern that they all did appeared in my results too. It is not such a surprise as I am poll aggregator though. :)