A Mathematician's Guide to the World Cup

In 2010 Paul the Octopus 'correctly' predicted results in the 2010 World Cup. However, these days the experts are the analysts who trawl through the reams of data about players and teams. And where there is data there is mathematics. And, particularly, mathematical models.

Joshua Bull is a mathematical modeller. He was also the winner of the 2020 Fantasy Football competition from over eight million entrants. So when it came to the Oxford Mathematics 2022 World Cup predictor, Josh fitted the bill perfectly. Honing in on the data, applying his modelling skills, and adding a pinch of the assumptions that inform modelling (disclaimer: he is an Ipswich Town fan), Josh has come up with the answers - or rather, likely outcomes. See what you think.

[leonardogoes]

I think the most efficient way to test this is using the exact model for last world cups and see if it works

[mohamedelhady]

There is a HUGE mistake
Each group should provide 2 teams to the round of 16
In your model Argentina group only one team
Brazil group 3 teams
This means you have to redo the round of 16th and beyond
But really
Great work

[pswire]

Great video, my highly scientific analysis is similar- it's called "The Gabriel Martinelli factor". It works like this- you analyze the team and figure out whether it has Gabriel Martinelli on the squad roster. If it does, it means you're going to win the World Cup.

[davidclark]

First of all xG-(xG allowed) would have been more useful than straight xG in capturing defensive capabilities of teams. But frankly, international team xG is just not a large or uniform enough (given significant split between friendlies and competitive matches) data set for this to work as discussed. The overvaluing of Belgium and undervaluing of England are two examples of this

using current player market value would almost definitely be more predictive than weighting straight xG

That said, it’s a fun video and teaches the iterative process of this kind of modeling very well, so A+ for maths communication

but if anyone is here looking for a betting edge, lol I guarantee the odds makers have thought about this more and modeled it more thoroughly, so maybe don’t

[mr.d]

The next step is finding teams with best betting payoff to prediction and layer several bets to maximize expected payout. Cool stuff. Thanks for posting.

[PedroHenrique-mbhh]

Thats why i love youtube. Just random videos like this make my day. Great work by the way, fantastic analysis

[juancruzcomes]

1:32 "We can predict, basically, every game that's gonna be on the WC"

Enter:
ARG-KSA
JPN-GER

[jorgeherrera]

Considering Saudi Arabia beat Argentina, all predictions have been thrown out the window XD

[EB_]

(20:13) You have three teams coming out of Group G (Brazil, Switzerland, and Serbia) and only one coming out of Group C (Argentina).

[erick.tokuda]

Mathematical modelling in a clear and fun way! Very good

[tonywilde]

As a long-suffering Wolveerhampton Wanderers fan, the first few slides of your excellent presentation got me thinking about our recent 4-0 capitulation at home to Leicester City. According to the statistics I found online, the xG for that game was Wolves 1.62 - 0.99 Leicester, despite the real scoreline!

So judging by the distribution model given @ 5:36 there appears to have been a 1-2% chance of Leicester scoring four goals that day, and indeed around 0.7% [35% x 2%] chance of the game ending 4-0. When your luck's out...!

[fajarwp]

I really appreciate the way you built assumptions and improved them when something unlikely showed up.
The model i believe can be more deterministic

[ger]

This is a really insightful and entertaining video -- a rare combination when it comes to explaining probabilistic models!

[mbogitechconpts]

Everyone and everything may now be working against this model including VAR Decisions and officiating officials. Injuries, red cards, weather and so many other unforseen factors may play big part too in who will eventually win the world Cup. I wonder of biases or noise was introduced to account for all these but we are keen to see the model performance. Great effort 👌 Joshua and team University of Oxford .

[gfr]

I appreciate your effort in adjusting parameters but this simulation is still biased as it didn't consider many other parameters such as the team combinations for the knock out stage up to the final, the dates of those matches, and many other parameters. From my prediction Portugal should get to the final and face one of Brazil, Netherlands or Argentina. My last pick for the final would still be Portugal given the fact they would have one more day to rest and considering they would have faced weaker opponents up to the final compared to those other 3 teams I mentioned above.

[britishdini]

i can now say that your major is not math, its art

[daianaflor]

Joshua Bull sabe mucho de investigaciones matemáticas pero cero conocimiento de fútbol.Saludos desde ARGENTINA

[Youtubegebruiker]

‘Ill remain unbiased here’ While wearing an Ipswich shirt 😂😂

[xblinketx]

19:31 there are 3 teams from the group G in round of 16 and only 1 from the group C.

[jarurotetippayachai]

This prediction cannot resist the curse of cats. 😂 Cats win.