FRESH

Hacker News

Show HN: For 10 World Cups, my model's 2 favorites had the champion every time

36 points by fabioricardo7

by bArray

1 subcomments

I've updated the magic weights, and I too can get the result I want:

    WEIGHTS = {
      'w_xg': 0.09,
      'w_goals': -0.07,
      'w_star': 0.018,
      'w_value': 0.18,
      'w_rank': 0.4,
      'w_def': -0.12,
      'xga_share': 0.85,
      'w_gk': 0.0042
    }

    $ python3 worldcup_model.py --sims 100000

    2026 FIFA World Cup -- championship probabilities (100,000 simulations, from Round of 32)

     1. England                 11.7% *
     2. France                  10.0% *
     3. Spain                    9.3% *
     4. Argentina                8.4%
     5. Germany                  8.1%

It's coming home!

by immighelper

0 subcomment

Probably the human pseudonym of Paul the Octopus (https://en.wikipedia.org/wiki/Paul_the_Octopus).

by walthamstow

0 subcomment

It's worth noting that there has only been 24 world cups

by bArray

1 subcomments

I've been messing with the magic value weights, and it doesn't take too much to push them in any given direction. The TEAMS_2026 should really be taken with a pinch of salt.

by xiaodai

1 subcomments

but does the model predict the right match up along way? if not it's just wrong wrong make a right

by derdi

2 subcomments

> Applied prospectively to the in-progress 2026 World Cup from the Round of 32, the model identifies Argentina (28.0%) and Spain (21.1%) as the leading championship candidates.
Seems weird to wait to run the "prospective" simulation until the World Cup is already in progress. Although it seems that the model also needs to use "the actual bracket and group-stage performance". So it's not prospective?

by artur_makly

1 subcomments

There is no MODEL for pure Argentine magic. vamos carajos! vamooooooooo con todo!!! Our time has come again.

by glenpierce

0 subcomment

Survivor bias

by mikelward

0 subcomment

> the model identifies Argentina (28.0%) and Spain (21.1%) as the leading championship candidates

by mcphage

1 subcomments

How does this paper not even mention the word "overfitting"?

by amazingamazing

2 subcomments

Why is the world cup so infrequent anyway? I assume to match olympics?
Good models need a lot of data. Can you really be accurate with what, 30 data points, in which the team composition is basically reset each time?

by dwedge

0 subcomment

!remindme tomorrow

by dwedge

1 subcomments

A good AI would calculate refereeing decisions and put Argentina at 100% unless England can pull off a miracle against FIFA today.

by yardie

2 subcomments

Does the model account for the blatant favouritism in the refs? We used to laugh about it before but as the cameras have gotten better it has become a lot more visible. And in this case, is turning the tournament into a bit of a joke.
-- Egypt was robbed.

by xiaodai

0 subcomment

how statistic significant is it.

by pessimizer

0 subcomment

Make sure your email is on file with every horrible news outlet in the world so they can write over 9000 stories about you before the next World Cup.
Get a few nice glamorshots and make sure you have something else in the queue before then to plug during the interviews.

by pestatije

0 subcomment

and how many models did you model?

by malthaus

0 subcomment

now back your claim with money and bet accordingly on betting sites to see if you uncovered some actual alpha here

by killingtime74

1 subcomments

"They've done studies, you know. 60% of the time, it works every time." - Brian Fantana, Anchorman