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Can AI predicts the tournament winner and golden booth for the FIFA World Cup Football Soccer 2022 in Qatar?
#FIFAWORLDCUP2022 #WORLDCUP2022 #QATARWORLDCUP #WORLDCUP
With the FIFA World Cup looming soon, fans around the world are wondering who will take home the coveted trophy. While many people have their own opinion on who the favorite is, one thing is for sure: no one knows for sure. However, that hasn’t stopped people from trying to predict the outcome using various methods, including artificial intelligence (AI). So, can AI accurately predict the winner of the 2022 FIFA World Cup? Let’s take a look.
How AI is Used to Predict the Outcome of Sporting Events
There are a few different ways that AI can be used to predict the outcome of sporting events. One method is known as predictive modeling. This method uses data from past events to try and identify patterns that can be used to predict future outcomes. For example, if a team has won every time they’ve scored first in their last 10 games, predictive modeling would suggest that there’s a good chance they’ll win again if they score first in their next game.
Another method that can be used is known as Monte Carlo simulations. This approach involves using a computer to simulate a large number of potential outcomes for an event. For example, a computer might simulate a football match 10,000 times and keep track of how often each team wins. Based on these results, it could then generate probabilities for each team winning.
Artificial intelligence (AI) can be used to predict the outcome of sporting events in a variety of ways, depending on the specific sport and the data available. Some common approaches include:
Analyzing past performance data: By analyzing past performance data for teams or individual players, it is possible to build statistical models that can predict the likelihood of certain outcomes in future games. This can involve analyzing data such as scoring patterns, win/loss records, and individual player stats.
Analyzing team dynamics: In team sports, it is also important to consider the dynamics of the team as a whole. AI can be used to analyze things like team cohesion, leadership, and communication to predict how well a team is likely to perform in a given game.
Analyzing external factors: External factors such as weather, home field advantage, and the relative strength of opponents can also be taken into account when predicting the outcome of a sporting event. AI can be used to analyze these factors and incorporate them into predictions.
Analyzing live data: In some cases, AI can also be used to analyze live data during a sporting event in order to make more accurate predictions. This could involve analyzing things like player movements, possession patterns, and scoring opportunities in real-time.
Overall, the use of AI in predicting the outcome of sporting events can be a powerful tool, but it is important to note that no prediction is ever 100% accurate, and there will always be some element of uncertainty involved.
Get the All Subjects Quiz App to play the World Cup Soccer Quiz at: Web – iOS – Android – Windows Amazon
How AI Can Help Us Predict The Winner Of The FIFA World Cup?
AI can help us to make predictions about who will win the FIFA World Cup by looking at past data and patterns. For example, if we look at the data from the last few World Cups, we can see that there are certain teams that have a higher chance of winning. By using AI, we can identify these teams and make a prediction about who will win the tournament.
We can also use AI to predict who will get the golden boot. The golden boot is awarded to the player who scores the most goals in the tournament. Again, by looking at past data, we can identify patterns and make predictions about who is most likely to score the most goals in this year’s tournament.
So, How Accurate is AI?
While AI can be quite accurate when it comes to predicting sporting event outcomes, there are always going to be some factors that are impossible to account for. For example, injuries or last-minute changes to a team’s lineup can completely change the outcome of a match. As such, even the best AI predictions should always be taken with a grain of salt.
As we get closer and closer to the 2022 FIFA World Cup, more and more people will be trying to predict who will take home the trophy. While many of these predictions will be based on gut feeling or personal biases, some will be based on artificial intelligence (AI). While AI can be quite accurate when it comes to predicting sporting event outcomes, there are always going to be some factors that are impossible to account for. As such, even the best AI predictions should always be taken with a grain of salt.
AI can be very helpful in making predictions about who will win the FIFA World Cup and who will get the golden boot. However, it is important to remember that these are just predictions. We cannot be 100% sure about anything until the tournament is over. So, enjoy the games and root for your favorite team.
#FIFAWORLDCUP2022 #WORLDCUP2022 #QATARWORLDCUP #WORLD
10 specific Predictions for the 2022 FIFA World Cup
- France will AVOID the World Cup winner’s curse, coming 2nd in Group D behind Denmark.
- Belgium and Uruguay crash out in the Group Stages.
- Morocco advances to the quarter final for the first time ever.
- Tunisia gets agonizingly close to the Round of 16 but falls short.
- Netherlands vs Argentina and Croatia vs Brazil are the two most thrilling Matches of the Tournament.
- Croatia and Morocco make the Quarter finals.
- England doesn’t capitulate. They have a standard 2000s England showing. Quarter Final exit.
- The World almost gets an Argentina vs Portugal Final, but Messi and Ronaldo meet in the Third Place match.
World Cup 2022: Opta predicts each country’s chances of winning
FiveThirtyEight’s 2022 World Cup Predictions
Soccer Power Index (SPI) ratings and chances of advancing for every team, updating live.
Results of 50,000 World Cup Knockout Simulations
BCA Research’s Supercomputer has predicted Argentina will win the 2022 World Cup
Who won the Golden Boots?
1- Kylian Mbappé (8 goals, 2 assists)
2- Lionel Messi (7 goals, 3 assists)
Who won the Golden Ball?
1- Lionel Messi
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Who won the Golden Gloves?
1- Emiliano Martínez (Argentina)
2- Livakovic (Croatia)
World Cup 2022 Key Stats
Winner: Argentina (1st World Cup win for Lionel Messi)
After 64 games and a record 172 goals, Argentina were crowned World champions for a third time with their dramatic penalty shoot-out victory over France.
Data analysts Nielsen’s Gracenote examined the trends from the 2022 competition after the conclusion of the first World Cup to be held in the winter, and in the Middle East.https://www.bbc.com/sport/football/64027504
1. Most upsets for 64 years
Number of upsets | Year | Percentage of matches ending in upset |
---|---|---|
15 | 2022 | 24% |
14 | 2002 | 22% |
12 | 2010 | 19% |
12 | 2018 | 19% |
11 | 1990 | 17% |
11 | 1994 | 17% |
10 | 1986 | 16% |
9 | 1958 | 26% |
8 | 1982 | 16% |
8 | 2006 | 13% |
2. Fewer shots…more goals
There were ‘only’ 1,458 shots at this year’s tournament, which was the lowest amount since Nielsen’s Gracenote started recording data on the statistic in 2002, down from a high of 1661 in 2014.
Indeed, the average number of shots taken during a match in Qatar was 22.8.
But that did not stop the goals raining in, with a record 172 goals scored – the highest since the tournament was expanded to 32 teams in 1998, with 171 scored at both France 1998 and Brazil 2014.
3. ‘Cleanest’ World Cup this century and more stoppage time
Referees handed out 227 yellow cards – the most since 2010, which Nielsen’s Gracenote say is down to stricter refereeing, while only four red cards were shown – the same as in Russia.
But the number of fouls declined for the fourth successive tournament to its lowest level this century at 1,599 – perhaps a reflection of referees being encouraged to let play flow.
A total of 23 penalties were awarded at an average of 0.36 per match – including three in the final – but that was actually down on the 2018 World Cup in Russia, the first with Video Assistant Referee (VAR) technology.
4. Young guns
The 2022 competition saw the most teenagers starting than at any other World Cup.
10 teenagers made 20 starts including 19-year-old England midfielder Jude Bellingham, 19-year-old Germany midfielder Jamal Musiala and 18-year-old Spain midfielder Gavi.
France forward Kylian Mbappe, now 23, still holds the record for most starts as a teenager with six to his name at the 2018 edition.
5. Ageing stars
It was not just a year for the young players as it also saw the most veteran players, competitors aged 35 and over, starting World Cup matches.
A combined 27 veteran players made 83 starts at the 2022 tournament, 32 more starts than the previous record set at the 2002 World Cup.
Messi, 35, and Croatia’s Luka Modric, 37, made the most starts of any veteran player in Qatar with seven each.
In recent years, AI has made great strides in pattern recognition and predictive analytics, leading many to believe that the technology could one day be used to accurately predict the outcomes of sporting events. However, there are a number of factors that make correctly predicting the FIFA World Cup winner a near impossible task for even the most advanced AI system. Let’s take a look at some of those factors.
The first factor is the sheer number of variables that need to be taken into account when trying to predict the outcome of a football match. Things like weather conditions, player fitness levels, team morale, and home-field advantage can all have a significant impact on the outcome of a game but are very difficult to quantify. Even something as seemingly simple as the quality of the pitch can have a major impact on how a game plays out.
Another factor that makes correctly predicting the FIFA World Cup winner difficult is the fact that there is no one “right” way to play football. Some teams prefer to play a possession-based style while others look to hit their opponents on the counter-attack. This variety makes it hard for AI systems to identify patterns and trends that could be used to predict results.
Finally, there is the element of luck that can often play a role in deciding football matches. A well-struck shot may take a fortuitous bounce and end up in the back of the net or a referee may make a controversial decision that changes the course of a game. While luck is not something that can be accounted for in predictive models, it can still have a major impact on results.
Conclusion:
As you can see, there are many factors that make correctly predicting the FIFA World Cup winner a daunting task for even the most advanced AI system. That being said, with continued advances in pattern recognition and predictive analytics, it’s not out of the realm of possibility that AI will one day be able to correctly predict the outcome of this prestigious event.
Make your picks: Printable World Cup 2022 Bracket
Football/Soccer World Cup Quiz
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FIFA World Cup 2022 Unofficial Guide Book – World Cup 2022 Bible and Quran
Access it here or via the video below:
How the World Cup Works?
The FIFA World Cup is the biggest tournament in world football. Every four years, 32 teams from across the world travel to a host nation to compete.
These 32 teams are selected through each confederation’s qualification round;
– 13 from Europe,
– 5 from Africa,
– 3 or 4* from North, Central America and the Caribbean,
– 4 or 5* from Asia,
– 4 or 5* from South America,
– 0 or 1* from Oceania
– and one spot for the hosts.
*(there is an intercontinental playoff for these spots)
For the tournament, the 32 teams are split into 8 groups made up of 4 teams each.
These 4 teams play each other once. Points are awarded per result;
3 for a win, 1 for a draw and 0 for a loss.
The top 2 teams in terms of points advance to the knockout rounds*.
*(in case of a tie, there are tie breaking statistics, the most common being goal differential which is the number of goals scored minus the number of goals conceded. In a tie the team with the higher GA goes through)
The 16 teams that make it out enter a single elimination knockout round, with extra time then penalty shootouts to decide a winner, if needed.
The round of 16 is followed by Quarter Finals, Semi Finals, a third place match, and then the Final; the winner of which is crowned champion.
Which teams have been drawn into the Group of Death for Qatar 2022?
Group A: Qatar, Ecuador, Senegal, Netherlands
This group is headlined by two traditional powerhouses in Netherlands and Senegal. Senegal is led by striker Sadio Mane, who is always a threat to score. Netherland, meanwhile, will be looking to rebound after missing the 2018 World Cup. They will be led by striker Memphis Depay, midfielders Denzel Dumphries and Frenkie De Jong, who will be looking to establish themselves on the world stage. Qatar and Ecuador round out the group and will be fighting for a spot in the knockout stage.
Coach: Aliou Cissé
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Édouard Mendy | 1 March 1992 (aged 30) | 25 | 0 | Chelsea | |
GK | Alfred Gomis | 5 September 1993 (aged 29) | 14 | 0 | Rennes | |
GK | Seny Dieng | 23 November 1994 (aged 27) | 3 | 0 | Queens Park Rangers | |
DF | Kalidou Koulibaly (captain) | 20 June 1991 (aged 31) | 63 | 0 | Chelsea | |
DF | Youssouf Sabaly | 5 March 1993 (aged 29) | 24 | 0 | Real Betis | |
DF | Abdou Diallo | 4 May 1996 (aged 26) | 18 | 2 | RB Leipzig | |
DF | Fodé Ballo-Touré | 3 January 1997 (aged 25) | 14 | 0 | Milan | |
DF | Pape Abou Cissé | 14 September 1995 (aged 27) | 12 | 1 | Olympiacos | |
DF | Ismail Jakobs | 17 August 1999 (aged 23) | 1 | 0 | Monaco | |
DF | Formose Mendy | 2 January 2001 (aged 21) | 1 | 0 | Amiens | |
MF | Idrissa Gueye | 26 September 1989 (aged 33) | 95 | 7 | Everton | |
MF | Cheikhou Kouyaté | 21 December 1989 (aged 32) | 82 | 4 | Nottingham Forest | |
MF | Krépin Diatta | 25 February 1999 (aged 23) | 25 | 2 | Monaco | |
MF | Nampalys Mendy | 23 June 1992 (aged 30) | 18 | 0 | Leicester City | |
MF | Pape Gueye | 24 January 1999 (aged 23) | 11 | 0 | Marseille | |
MF | Pape Matar Sarr | 14 September 2002 (aged 20) | 8 | 0 | Tottenham Hotspur | |
MF | Moustapha Name | 5 May 1995 (aged 27) | 6 | 0 | Pafos | |
MF | Mamadou Loum | 30 December 1996 (aged 25) | 3 | 0 | Reading | |
MF | Pathé Ciss | 16 March 1994 (aged 28) | 1 | 0 | Rayo Vallecano | |
FW | Sadio Mané | 10 April 1992 (aged 30) | 92 | 34 | Bayern Munich | |
FW | Ismaïla Sarr | 25 February 1998 (aged 24) | 47 | 10 | Watford | |
FW | Famara Diédhiou | 15 December 1992 (aged 29) | 24 | 10 | Alanyaspor | |
FW | Boulaye Dia | 16 November 1996 (aged 26) | 18 | 3 | Salernitana | |
FW | Bamba Dieng | 23 March 2000 (aged 22) | 12 | 2 | Marseille | |
FW | Iliman Ndiaye | 6 March 2000 (aged 22) | 1 | 0 | Sheffield United | |
FW | Nicolas Jackson | 20 June 2001 (aged 21) | 0 | 0 | Villarreal |
Coach: Gustavo Alfaro
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
1 | GK | Hernán Galíndez | 30 March 1987 (aged 35) | 12 | 0 | Aucas |
2 | DF | Félix Torres | 11 January 1997 (aged 25) | 17 | 2 | Santos Laguna |
3 | DF | Piero Hincapié | 9 January 2002 (aged 20) | 21 | 1 | Bayer Leverkusen |
4 | DF | Robert Arboleda | 22 October 1991 (aged 31) | 33 | 2 | São Paulo |
5 | MF | José Cifuentes | 12 March 1999 (aged 23) | 11 | 0 | Los Angeles FC |
6 | DF | William Pacho | 16 October 2001 (aged 21) | 0 | 0 | Antwerp |
7 | DF | Pervis Estupiñán | 21 January 1998 (aged 24) | 28 | 3 | Brighton & Hove Albion |
8 | MF | Carlos Gruezo | 19 April 1995 (aged 27) | 45 | 1 | FC Augsburg |
9 | MF | Ayrton Preciado | 17 July 1994 (aged 28) | 25 | 3 | Santos Laguna |
10 | MF | Romario Ibarra | 24 September 1994 (aged 28) | 25 | 3 | Pachuca |
11 | FW | Michael Estrada | 7 April 1996 (aged 26) | 35 | 8 | Cruz Azul |
12 | GK | Moisés Ramírez | 9 September 2000 (aged 22) | 2 | 0 | Independiente del Valle |
13 | FW | Enner Valencia (captain) | 4 November 1989 (aged 33) | 74 | 35 | Fenerbahçe |
14 | DF | Xavier Arreaga | 28 September 1994 (aged 28) | 18 | 1 | Seattle Sounders FC |
15 | MF | Ángel Mena | 21 January 1988 (aged 34) | 46 | 7 | León |
16 | MF | Jeremy Sarmiento | 16 June 2002 (aged 20) | 9 | 0 | Brighton & Hove Albion |
17 | DF | Ángelo Preciado | 18 February 1998 (aged 24) | 25 | 0 | Genk |
18 | DF | Diego Palacios | 12 July 1999 (aged 23) | 12 | 0 | Los Angeles FC |
19 | MF | Gonzalo Plata | 1 November 2000 (aged 22) | 30 | 5 | Valladolid |
20 | MF | Sebas Méndez | 26 April 1997 (aged 25) | 32 | 0 | Los Angeles FC |
21 | MF | Alan Franco | 21 August 1998 (aged 24) | 25 | 1 | Talleres |
22 | GK | Alexander Domínguez | 5 June 1987 (aged 35) | 68 | 0 | LDU Quito |
23 | MF | Moisés Caicedo | 2 November 2001 (aged 21) | 25 | 2 | Brighton & Hove Albion |
24 | FW | Djorkaeff Reasco | 18 January 1999 (aged 23) | 4 | 0 | Newell’s Old Boys |
25 | DF | Jackson Porozo | 4 August 2000 (aged 22) | 5 | 0 | Troyes |
26 | FW | Kevin Rodríguez | 4 March 2000 (aged 22) | 1 | 0 | Imbabura |
World Cup 2022 – GROUP A Scores and Ranking Predictions with AI
1. Netherlands – 7 pts.
2. Senegal – 6 pts.
3. Ecuador – 4 pts.
4. Qatar – 0 pt.
Qatar 0-2 Ecuador [Ener Valencia Brace: 2 goals]
Senegal 0-2 Netherlands [Cody Gakpo(1) and Klassen(1)]
Qatar 1-3 Senegal [Muntari(1), B Dia(1), B Dieng(1)]
Netherlands 1-1 Ecuador [Gakpo(1), E. Valencia(1)]
Ecuador 1-2 Senegal [Caidedo(1), Sarr(1), Koulibaly(1)]
Netherlands 2-0 Qatar [Gakpo(1), De Jong(1)]
Group B: England, Iran, USA, Wales
This group features another traditional powerhouse in England. Harry Kane and Raheem Sterling will be looking to lead their country to glory for the first time since 1966. USA and Iran are both strong sides that will provide stiff competition. Wales rounds out the group and is led by Gareth Bale and will likely be fighting for second place.
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Jordan Pickford | 7 March 1994 (aged 28) | 45 | 0 | Everton | |
GK | Nick Pope | 19 April 1992 (aged 30) | 10 | 0 | Newcastle United | |
GK | Aaron Ramsdale | 14 May 1998 (aged 24) | 3 | 0 | Arsenal | |
DF | Kyle Walker | 28 May 1990 (aged 32) | 70 | 0 | Manchester City | |
DF | John Stones | 28 May 1994 (aged 28) | 59 | 3 | Manchester City | |
DF | Harry Maguire | 5 March 1993 (aged 29) | 48 | 7 | Manchester United | |
DF | Eric Dier | 15 January 1994 (aged 28) | 47 | 3 | Tottenham Hotspur | |
DF | Kieran Trippier | 19 September 1990 (aged 32) | 37 | 1 | Newcastle United | |
DF | Luke Shaw | 12 July 1995 (aged 27) | 23 | 3 | Manchester United | |
DF | Trent Alexander-Arnold | 7 October 1998 (aged 24) | 17 | 1 | Liverpool | |
DF | Conor Coady | 25 February 1993 (aged 29) | 10 | 1 | Everton | |
DF | Ben White | 8 October 1997 (aged 25) | 4 | 0 | Arsenal | |
MF | Jordan Henderson | 17 June 1990 (aged 32) | 70 | 2 | Liverpool | |
MF | Declan Rice | 14 January 1999 (aged 23) | 34 | 2 | West Ham United | |
MF | Mason Mount | 10 January 1999 (aged 23) | 32 | 5 | Chelsea | |
MF | Kalvin Phillips | 2 December 1995 (aged 26) | 23 | 0 | Manchester City | |
MF | Phil Foden | 28 May 2000 (aged 22) | 18 | 2 | Manchester City | |
MF | Jude Bellingham | 29 June 2003 (aged 19) | 17 | 0 | Borussia Dortmund | |
MF | Conor Gallagher | 6 February 2000 (aged 22) | 4 | 0 | Chelsea | |
MF | James Maddison | 13 November 1996 (aged 26) | 1 | 0 | Leicester City | |
FW | Raheem Sterling | 8 December 1994 (aged 27) | 79 | 19 | Chelsea | |
FW | Harry Kane (captain) | 28 July 1993 (aged 29) | 75 | 51 | Tottenham Hotspur | |
FW | Marcus Rashford | 31 October 1997 (aged 25) | 46 | 12 | Manchester United | |
FW | Jack Grealish | 10 September 1995 (aged 27) | 24 | 1 | Manchester City | |
FW | Bukayo Saka | 5 September 2001 (aged 21) | 20 | 4 | Arsenal | |
FW | Callum Wilson | 27 February 1992 (aged 30) | 4 | 1 | Newcastle United |
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Matt Turner | 24 June 1994 (aged 28) | 20 | 0 | Arsenal | |
GK | Sean Johnson | 31 May 1989 (aged 33) | 10 | 0 | New York City FC | |
GK | Ethan Horvath | 9 June 1995 (aged 27) | 8 | 0 | Luton Town | |
DF | DeAndre Yedlin | 9 July 1993 (aged 29) | 75 | 0 | Inter Miami | |
DF | Tim Ream | 5 October 1987 (aged 35) | 46 | 1 | Fulham | |
DF | Walker Zimmerman | 19 May 1993 (aged 29) | 33 | 3 | Nashville SC | |
DF | Aaron Long | 12 October 1992 (aged 30) | 29 | 3 | New York Red Bulls | |
DF | Antonee Robinson | 8 August 1997 (aged 25) | 29 | 2 | Fulham | |
DF | Sergiño Dest | 3 November 2000 (aged 22) | 19 | 2 | Milan | |
DF | Shaq Moore | 2 November 1996 (aged 26) | 15 | 1 | Nashville SC | |
DF | Cameron Carter-Vickers | 31 December 1997 (aged 24) | 11 | 0 | Celtic | |
DF | Joe Scally | 31 December 2002 (aged 19) | 3 | 0 | Borussia Mönchengladbach | |
MF | Kellyn Acosta | 24 July 1995 (aged 27) | 53 | 2 | Los Angeles FC | |
MF | Weston McKennie | 28 August 1998 (aged 24) | 37 | 9 | Juventus | |
MF | Tyler Adams | 14 February 1999 (aged 23) | 32 | 1 | Leeds United | |
MF | Cristian Roldan | 3 June 1995 (aged 27) | 32 | 0 | Seattle Sounders | |
MF | Brenden Aaronson | 22 October 2000 (aged 22) | 24 | 6 | Leeds United | |
MF | Yunus Musah | 29 November 2002 (aged 19) | 19 | 0 | Valencia | |
MF | Luca de la Torre | 23 May 1998 (aged 24) | 12 | 0 | Celta Vigo | |
FW | Christian Pulisic | 18 September 1998 (aged 24) | 52 | 21 | Chelsea | |
FW | Jordan Morris | 26 October 1994 (aged 28) | 49 | 11 | Seattle Sounders | |
FW | Timothy Weah | 22 February 2000 (aged 22) | 25 | 3 | Lille | |
FW | Josh Sargent | 20 February 2000 (aged 22) | 20 | 5 | Norwich City | |
FW | Jesús Ferreira | 24 December 2000 (aged 21) | 15 | 7 | FC Dallas | |
FW | Giovanni Reyna | 13 November 2002 (aged 20) | 14 | 4 | Borussia Dortmund | |
FW | Haji Wright | 27 March 1998 (aged 24) | 3 | 1 | Antalyaspor |
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Wayne Hennessey | 24 January 1987 (aged 35) | 106 | 0 | Nottingham Forest | |
GK | Danny Ward | 22 June 1993 (aged 29) | 26 | 0 | Leicester City | |
GK | Adam Davies | 17 July 1992 (aged 30) | 3 | 0 | Sheffield United | |
DF | Chris Gunter | 21 July 1989 (aged 33) | 109 | 0 | Wimbledon | |
DF | Ben Davies | 24 April 1993 (aged 29) | 74 | 1 | Tottenham Hotspur | |
DF | Connor Roberts | 23 September 1995 (aged 27) | 41 | 3 | Burnley | |
DF | Ethan Ampadu | 14 September 2000 (aged 22) | 37 | 0 | Spezia | |
DF | Chris Mepham | 5 November 1997 (aged 25) | 33 | 0 | Bournemouth | |
DF | Joe Rodon | 22 October 1997 (aged 25) | 30 | 0 | Rennes | |
DF | Neco Williams | 13 April 2001 (aged 21) | 23 | 2 | Nottingham Forest | |
DF | Tom Lockyer | 3 December 1994 (aged 27) | 14 | 0 | Luton Town | |
DF | Ben Cabango | 30 May 2000 (aged 22) | 5 | 0 | Swansea City | |
MF | Aaron Ramsey (vice captain) | 26 December 1990 (aged 31) | 75 | 20 | Nice | |
MF | Joe Allen | 14 March 1990 (aged 32) | 72 | 2 | Swansea City | |
MF | Harry Wilson | 22 March 1997 (aged 25) | 39 | 5 | Fulham | |
MF | Jonny Williams | 9 October 1993 (aged 29) | 33 | 2 | Swindon Town | |
MF | Joe Morrell | 3 January 1997 (aged 25) | 30 | 0 | Portsmouth | |
MF | Matthew Smith | 22 November 1999 (aged 22) | 19 | 0 | Milton Keynes Dons | |
MF | Dylan Levitt | 17 November 2000 (aged 22) | 13 | 0 | Dundee United | |
MF | Rubin Colwill | 27 April 2002 (aged 20) | 7 | 1 | Cardiff City | |
MF | Sorba Thomas | 25 January 1999 (aged 23) | 6 | 0 | Huddersfield Town | |
FW | Gareth Bale (captain) | 16 July 1989 (aged 33) | 108 | 40 | Los Angeles FC | |
FW | Daniel James | 10 November 1997 (aged 25) | 38 | 5 | Fulham | |
FW | Kieffer Moore | 8 August 1992 (aged 30) | 28 | 9 | Bournemouth | |
FW | Brennan Johnson | 23 May 2001 (aged 21) | 15 | 2 | Nottingham Forest | |
FW | Mark Harris | 29 December 1998 (aged 23) | 5 | 0 | Cardiff City |
World Cup 2022 – GROUP B Scores and Ranking Predictions with AI:
1. England – 7 pts.
2. Usa – 5 pts.
3. Iran – 3 pts.
4. Wales- 3 pts.
England 6-2 Iran [Saka(2), Bellingham(1), Sterling(1), Grealish(1)]
United States 1-1 Wales [Weah(1), Bale(1)]
England 0-0 United States
Wales 0-2 Iran [Cheschmi(1), Rezaeian(1)]
Iran 2-3 United States [C. Pulisic (1)]
Wales 0-3 England [M Rashford(2), P. Foden(1)]
Group C: Argentina, Mexico, Saudi Arabia, Poland
This group features another traditional powerhouse in Argentina. Lionel Messi will be looking to lead his country to glory one last time before he retires from international football. Mexico is always a tough team to beat and will be looking to go far in Qatar. Poland is a solid European side led by prolific striker Robert Lewandowski that could give Argentina a run for their money. Saudi Arabia rounds out the group and will likely finish in last place.
World Cup 2022 – GROUP C Predictions based AI
1. Argentina – 6 pts.
2. Poland – 4 pts. [Goal Difference)
3. Mexico – 4 pts.
4. Saudi Arabia – 3 pt.
Argentina 1-2 Saudi Arabia [Messi (1), Al Shehri(1), Al Dawsari(1)]
Mexico 0-0 Poland
Argentina 2-0 Mexico [L. Messi(1), E. Fernandez(1)]
Poland 2-0 Saudi Arabia [Lewandowski(1), P. Zielinski(1)]
Saudi Arabia 1-2 Mexico [S. Al Dawsari(1), H. Martin(1), Luis Chavez(1)]
Poland 0-2 Argentina [A. Mac Allister(1), J. Alvarez(1)]
Group D: France, Australia, Denmark, Tunisia
France is always one of the favorites to win the World Cup, and they headline this group. They are led by superstars Kylian Mbappe and Karim Benzema, the current Ballon d’Or, who will be looking to carry their beloved country national team (Les Bleus) to back to back World Cup glory. Denmark and Tunisia are both solid sides that could give France a challenge. Australia rounds out the group and will likely finish in last place.
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Kasper Schmeichel | 5 November 1986 | 86 | 0 | Nice | |
GK | Oliver Christensen | 22 March 1999 | 1 | 0 | Hertha BSC | |
DF | Simon Kjær (captain) | 26 March 1989 | 121 | 5 | Milan | |
DF | Andreas Christensen | 10 April 1996 | 58 | 2 | Barcelona | |
DF | Jens Stryger Larsen | 21 February 1991 | 49 | 3 | Trabzonspor | |
DF | Daniel Wass | 31 May 1989 | 44 | 1 | Brøndby | |
DF | Joakim Mæhle | 20 May 1997 | 31 | 9 | Atalanta | |
DF | Joachim Andersen | 31 May 1996 | 19 | 0 | Crystal Palace | |
DF | Rasmus Kristensen | 11 July 1997 | 10 | 0 | Leeds United | |
DF | Victor Nelsson | 14 October 1998 | 7 | 0 | Galatasaray | |
MF | Christian Eriksen | 14 February 1992 | 117 | 39 | Manchester United | |
MF | Thomas Delaney | 3 September 1991 | 71 | 7 | Sevilla | |
MF | Pierre-Emile Højbjerg | 5 August 1995 | 60 | 5 | Tottenham Hotspur | |
MF | Mathias Jensen | 1 January 1996 | 20 | 1 | Brentford | |
FW | Martin Braithwaite | 5 June 1991 | 62 | 10 | Espanyol | |
FW | Andreas Cornelius | 16 March 1993 | 41 | 9 | FC Copenhagen | |
FW | Kasper Dolberg | 6 October 1997 | 37 | 11 | Sevilla | |
FW | Andreas Skov Olsen | 29 December 1999 | 23 | 8 | Club Brugge | |
FW | Mikkel Damsgaard | 3 July 2000 | 18 | 4 | Brentford | |
FW | Jonas Wind | 7 February 1999 | 15 | 5 | VfL Wolfsburg | |
FW | Jesper Lindstrøm | 29 February 2000 | 6 | 1 | Eintracht Frankfurt |
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
1 | GK | Aymen Mathlouthi | 14 September 1984 (aged 38) | 73 | 0 | Étoile du Sahel |
2 | DF | Bilel Ifa | 9 March 1990 (aged 32) | 36 | 0 | Kuwait SC |
3 | DF | Montassar Talbi | 26 May 1998 (aged 24) | 22 | 1 | Lorient |
4 | DF | Yassine Meriah | 2 July 1993 (aged 29) | 60 | 3 | Espérance de Tunis |
5 | DF | Nader Ghandri | 18 February 1995 (aged 27) | 7 | 0 | Club Africain |
6 | DF | Dylan Bronn | 19 June 1995 (aged 27) | 36 | 2 | Salernitana |
7 | FW | Youssef Msakni (captain) | 28 October 1990 (aged 32) | 87 | 17 | Al-Arabi |
8 | MF | Hannibal Mejbri | 21 January 2003 (aged 19) | 18 | 0 | Birmingham City |
9 | FW | Issam Jebali | 25 December 1991 (aged 30) | 9 | 2 | OB |
10 | FW | Wahbi Khazri | 8 February 1991 (aged 31) | 71 | 24 | Montpellier |
11 | FW | Taha Yassine Khenissi | 6 January 1992 (aged 30) | 48 | 9 | Kuwait SC |
12 | DF | Ali Maâloul | 1 January 1990 (aged 32) | 82 | 2 | Al Ahly |
13 | MF | Ferjani Sassi | 18 March 1992 (aged 30) | 77 | 6 | Al-Duhail |
14 | MF | Aïssa Laïdouni | 13 December 1996 (aged 25) | 24 | 1 | Ferencváros |
15 | MF | Mohamed Ali Ben Romdhane | 6 September 1999 (aged 23) | 22 | 1 | Espérance de Tunis |
16 | GK | Aymen Dahmen | 28 January 1997 (aged 25) | 4 | 0 | CS Sfaxien |
17 | MF | Ellyes Skhiri | 10 May 1995 (aged 27) | 48 | 3 | 1. FC Köln |
18 | MF | Ghailene Chaalali | 28 February 1994 (aged 28) | 30 | 1 | Espérance de Tunis |
19 | FW | Seifeddine Jaziri | 12 February 1993 (aged 29) | 29 | 10 | Zamalek |
20 | DF | Mohamed Dräger | 25 June 1996 (aged 26) | 33 | 3 | Luzern |
21 | DF | Wajdi Kechrida | 5 November 1995 (aged 27) | 18 | 0 | Atromitos |
22 | GK | Bechir Ben Saïd | 29 November 1994 (aged 27) | 10 | 0 | US Monastir |
23 | FW | Naïm Sliti | 27 July 1992 (aged 30) | 68 | 13 | Al-Ettifaq |
24 | DF | Ali Abdi | 20 December 1993 (aged 28) | 9 | 1 | Caen |
25 | MF | Anis Ben Slimane | 16 March 2001 (aged 21) | 24 | 4 | Brøndby |
26 | GK | Mouez Hassen | 5 March 1995 (aged 27) | 20 | 0 | Club Africain |
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Mathew Ryan (captain) | 8 April 1992 | 75 | 0 | Copenhagen | |
GK | Danny Vukovic | 27 March 1985 | 4 | 0 | Central Coast Mariners | |
GK | Andrew Redmayne | 13 January 1989 | 4 | 0 | Sydney FC | |
DF | Aziz Behich | 16 October 1990 | 53 | 2 | Dundee United | |
DF | Miloš Degenek | 28 April 1994 | 38 | 1 | Columbus Crew | |
DF | Bailey Wright | 28 July 1992 | 27 | 2 | Sunderland | |
DF | Fran Karačić | 12 May 1996 | 10 | 1 | Brescia | |
DF | Harry Souttar | 22 October 1998 | 10 | 6 | Stoke City | |
DF | Nathaniel Atkinson | 13 June 1999 | 5 | 0 | Heart of Midlothian | |
DF | Joel King | 30 October 2000 | 4 | 0 | OB | |
DF | Kye Rowles | 24 June 1998 | 3 | 0 | Heart of Midlothian | |
DF | Thomas Deng | 20 March 1997 | 2 | 0 | Albirex Niigata | |
MF | Aaron Mooy | 15 September 1990 | 53 | 7 | Celtic | |
MF | Jackson Irvine | 7 March 1993 | 49 | 7 | St. Pauli | |
MF | Ajdin Hrustic | 5 July 1996 | 20 | 3 | Hellas Verona | |
MF | Riley McGree | 2 November 1998 | 11 | 1 | Middlesbrough | |
MF | Keanu Baccus | 7 June 1998 | 1 | 0 | St Mirren | |
MF | Cameron Devlin | 7 June 1998 | 1 | 0 | Heart of Midlothian | |
FW | Mathew Leckie | 4 February 1991 | 73 | 13 | Melbourne City | |
FW | Awer Mabil | 15 September 1995 | 29 | 8 | Cádiz | |
FW | Jamie Maclaren | 29 July 1993 | 26 | 8 | Melbourne City | |
FW | Mitchell Duke | 18 January 1991 | 21 | 8 | Fagiano Okayama | |
FW | Martin Boyle | 25 April 1993 | 19 | 5 | Hibernian | |
FW | Craig Goodwin | 16 December 1991 | 10 | 1 | Adelaide United | |
FW | Jason Cummings | 1 August 1995 | 1 | 1 | Central Coast Mariners | |
FW | Garang Kuol | 15 September 2004 | 1 | 0 | Central Coast Mariners |
World Cup 2022 – GROUP D Score and Rankings Predictions with AI:
1. France – 6 pts.
2. Australia – 6 pts.
3. Tunisia – 4 pts.
4. Denmark – 1 pt.
France 4-1 Australia [Giroud(2), Mbappe(1), Rabiot(1)]
Denmark 0-0 Tunisia
France 2-1 Denmark [Mbappe(2)]
Tunisia 0-1 Australia [M Duke(1)]
Australia 1-0 Denmark [M. Leckie(1)]
Tunisia 1-0 France [W. Khazri(1)]
Group E: Spain, Costa Rica, Germany, Japan
There’s no doubting the most immediately attractive tie of the group stage: the clash of the 2010 and 2014 champions as Spain face Germany. After two dismal World Cup performances in a row, there is a sense that Spain are building again under Luis Enrique as he has introduced a more direct style.
For Germany, the last World Cup was a major embarrassment, defeat to South Korea resulting in a first round exit for the first time in 80 years. Germany is led by their word cup winning goalkeeper Manual Neuer and coach Hansi Flick.
Japan, who have a wealth of European experience in their squad, can feel a little unfortunate at yet another tough draw in their seventh successive World Cup appearance.
The group is rounded off by the winner of the Costa Rica v New Zealand playoff.
No. | Pos. | Player | Date of birth (age) | Caps | Goals | Club |
---|---|---|---|---|---|---|
GK | Manuel Neuer (captain) | 27 March 1986 (aged 36) | 113 | 0 | Bayern Munich | |
GK | Marc-André ter Stegen | 30 April 1992 (aged 30) | 30 | 0 | Barcelona | |
GK | Kevin Trapp | 8 July 1990 (aged 32) | 6 | 0 | Eintracht Frankfurt | |
DF | Antonio Rüdiger | 3 March 1993 (aged 29) | 54 | 2 | Real Madrid | |
DF | Matthias Ginter | 19 January 1994 (aged 28) | 46 | 2 | SC Freiburg | |
DF | Niklas Süle | 3 September 1995 (aged 27) | 42 | 1 | Borussia Dortmund | |
DF | Thilo Kehrer | 21 September 1996 (aged 26) | 22 | 0 | West Ham United | |
DF | Lukas Klostermann | 3 June 1996 (aged 26) | 18 | 0 | RB Leipzig | |
DF | David Raum | 22 April 1998 (aged 24) | 11 | 0 | RB Leipzig | |
DF | Christian Günter | 28 February 1993 (aged 29) | 6 | 0 | SC Freiburg | |
DF | Nico Schlotterbeck | 1 December 1999 (aged 22) | 5 | 0 | Borussia Dortmund | |
DF | Armel Bella-Kotchap | 11 December 2001 (aged 20) | 1 | 0 | Southampton | |
MF | Joshua Kimmich | 8 February 1995 (aged 27) | 70 | 5 | Bayern Munich | |
MF | Mario Götze | 3 June 1992 (aged 30) | 63 | 17 | Eintracht Frankfurt | |
MF | İlkay Gündoğan | 24 October 1990 (aged 32) | 62 | 16 | Manchester City | |
MF | Leon Goretzka | 6 February 1995 (aged 27) | 44 | 14 | Bayern Munich | |
MF | Julian Brandt | 2 May 1996 (aged 26) | 38 | 3 |