Futures
Access hundreds of perpetual contracts
CFD
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
CFD
U.S. stock CFD derivatives
US Stocks
Access real US stocks and ETFs
HK Stocks
Trade quality Hong Kong-listed stocks
Korean Stocks
SK Hynix
Real Korean stocks and top assets
Stock Futures
High leverage, 24/7 trading
Tokenized Stocks
Backed by real stock assets
IPO Access
Unlock full access to global stock IPOs
GUSD
Mint GUSD for Treasury RWA yields
Stocks Activities
Trade Popular Stocks and Unlock Generous Airdrops
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
IPO Access
Unlock full access to global stock IPOs
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
Promotions
AI
Gate AI
Your all-in-one conversational AI partner
Gate AI Bot
Use Gate AI directly in your social App
GateClaw
Gate Blue Lobster, ready to go
Gate for AI Agent
AI infrastructure, Gate MCP, Skills, and CLI
Gate Skills Hub
10K+ Skills
From office tasks to trading, the all-in-one skill hub makes AI even more useful.
#广场预测世界杯赢40000U Why are there more and more upsets in the World Cup? Math has already told you...
There is a line in Goal!: In the world of football, impossible things happen every day.
You think it's just motivational talk. It's actually math.
1. First, a number that silences everyone
In the 2018 World Cup, Germany lost 2-0 to South Korea in the group stage, finishing dead last in the group. The world was shocked. But the odds from BC company at the time were 1:17. Converted to probability: South Korea winning had only a 5.6% chance.
Theoretically, such an event would happen once every 18 times on average. But that World Cup group stage had only 48 matches—and it happened exactly that way.
Some say: luck. Some say: complacency. Mathematicians say: this is not an accident; this is the Poisson distribution.
2. What is the Poisson distribution? In plain English
A football match lasts 90 minutes, with few goals. The average number of goals per match is around 2 to 3. This kind of "rare random event per unit time" can be precisely modeled with the Poisson distribution.
The formula looks scary, but the principle is simple:
If a team averages 2 goals per match (λ=2), then: Probability of 0 goals: 13.5%
Probability of 1 goal: 27.1%
Probability of 2 goals: 27.1%
Probability of 3 goals: 18.0%
Probability of 4+ goals: about 14.3%
A weak team scoring 3 goals and causing an upset? Mathematically, it's not impossible—just low probability. Low probability does not mean it won't happen.
3. In 2026, why will there be more upsets?
The 2018 World Cup: 32 teams, 48 group stage matches. The 2026 World Cup: 48 teams, 72 group stage matches. That's a full **50%** increase in matches. Each additional match is another "opportunity" for a low-probability event to occur.
We did a rough estimate: assume each match has about a 5% chance of a major upset (strong team losing).
With 48 matches: expected about 2.4 major upsets.
With 72 matches: expected about 3.6 major upsets.
That's a full **50%** increase.
In other words: it's not that you're more likely to see upsets; there are simply more upsets happening. This is not a feeling; this is math talking.
4. So, is AI prediction useful? This is the core question.
Since football is so random, what's the point of prediction? The answer is: partially useful, but you need to understand the boundaries of "usefulness."
5. Backtesting data speaks
We ran offline verification on 192 matches from the 2014, 2018, and 2022 World Cups. The conclusion is clear: In group stage matches, where there is a clear disparity in strength, the model has reference value. In knockout rounds, where one match decides everything, randomness spikes, and the model's performance weakens significantly. High-confidence matches are the most worth referencing—but only about 20 matches per World Cup. The essence of upsets is the normal occurrence of low-probability events.
It's not a bug, not a referee scandal, not luck. It's the Poisson distribution saying: You plan for every possibility, but football keeps that 5% just to make the world remember it.
6. In 2026, which types of matches should you focus on most?
Our advice: Group stage third round: tight standings, some strong teams already qualified and resting key players, high upset rate.
Asia/Africa vs. Europe: biggest ELO gap, but the Poisson distribution tells you: the bigger the gap, the more "shocking" the occasional upset feels. Matches with confidence ≥60%: system will highlight them separately; historically the most worth watching.
There's a line in *Goal! The Dream Begins*: In the world of football, the impossible happens every day.
You might think this is inspirational. But it's actually math.
First, let's talk about a number that stunned everyone.
At the 2018 World Cup, Germany lost 0-2 to South Korea in the group stage and finished last in their group. The world was shocked. But at the time, the odds from BC company were 1:17. Converted to probability: South Korea winning had only a 5.6% chance.
Theoretically, such an event happens once every 18 matches. But there were only 48 group-stage matches in that World Cup—and it just happened to occur.
Some say: luck. Some say: complacency. Mathematicians say: This isn't an accident; it's the Poisson distribution.
Second, what is the Poisson distribution? In simple terms.
A football match lasts 90 minutes, with few goals scored. The average number of goals per match is around 2 to 3. This kind of "rare random event within a unit of time" can be precisely modeled using the Poisson distribution.
The formula looks scary, but the principle is simple:
If a team averages 2 goals per match (λ=2), then:
Probability of scoring 0 goals: 13.5%
Probability of scoring 1 goal: 27.1%
Probability of scoring 2 goals: 27.1%
Probability of scoring 3 goals: 18.0%
Probability of scoring 4 or more: about 14.3%
A weak team scoring 3 goals in an upset? Mathematically, it's possible, just with low probability. Low probability does not mean it won't happen.
Third, why will there be more upsets in 2026?
2018 World Cup: 32 teams, 48 group-stage matches. 2026 World Cup: 48 teams, 72 group-stage matches. That's a full **50%** increase in matches. Every additional match is another "launch opportunity" for a low-probability event.
We did a rough estimate: Assume that in each match, the probability of a major upset (strong team being beaten) is about 5%.
With 48 matches: Expected about 2.4 major upsets.
With 72 matches: Expected about 3.6 major upsets.
That's a full 50% increase.
In other words: You're not just seeing more upsets—there are simply more upsets. This isn't a feeling; it's math speaking.
Fourth, so is AI prediction useful? That's the core question.
Since football is so random, what's the point of predictions? The answer is: partially useful, but you need to understand the boundaries of "usefulness."
Fifth, backtesting data speaks.
We conducted offline validation on 192 matches from the 2014, 2018, and 2022 World Cups. The conclusion is clear:
In group stages, where strength differences are obvious, the model has reference value.
In knockout stages, where it's one match to decide, randomness surges, and the model significantly weakens.
High-confidence matches are the most worth referencing—but each World Cup has only about 20 such matches.
The essence of upsets is the normal occurrence of low-probability events.
It's not a bug, not match-fixing, not luck. It's the Poisson distribution saying: You planned for every possibility, but football keeps that 5% just to make the world remember it.
Sixth, for 2026, which matches should you pay most attention to?
Our suggestion:
Third round of group stage: With tight standings, some strong teams already qualified, reduced motivation for starters, high upset probability.
Asia/Africa vs. Europe: Biggest ELO gap, but the Poisson distribution tells you: the larger the gap, the stronger the "shock value" when an upset occasionally happens.
Matches with confidence ≥ 60%: System-specific marking, historically the most worth paying attention to.