AI Picks Manchester City to Win the Premier League

Liverpool and Arsenal to chase City while Luton and Nottingham Forest predicted to be relegated

Ben Wodecki, Jr. Editor

August 8, 2023

8 Min Read
AI predicts the probability of stopping Man City from lifting another Premier League titleCredit: Michael Regan/Getty Images

At a Glance

  • AI predicts Manchester City will win the Premier League with Pep Guardiola's side to win their fourth title in a row.
  • AI picks Tottenham to finish above Chelsea, Liverpool to finish second above Arsenal and new boys Luton to be relegated.

The English Premier League returns this weekend, with Manchester City looking set to win their fourth Premier League title in a row as AI predicts the 2023/24 season.

Pep Guardiola’s side won the treble last year and have eyes on their sixth title in seven seasons. AI Business partnered with to predict the 2023-24 season, with Erling Haaland, Kevin De Bruyne and company the far-off favorites to clinch the title.

City will start their title defense at Burnley who are managed by former captain Vincent Kompany. The Sky Blues have spent big on Joško Gvardiol, signing the Croatian defender from RB Leipzig in a deal worth £77.6 million ($98 million), as well as bringing in Mateo Kovacic from Chelsea for £25 million ($30 million).

However, City will be without midfield maestro İlkay Gündoğan who left the club for Barcelona, as well as winger Riyad Mahrez, who joined the growing number of stars in Saudi Arabia.'s machine learning model picked Jürgen Klopp's Liverpool to recover from their poor fifth place finish last time to return to challenging City.

Liverpool has spent the summer rebuilding their aging midfield, turfing out stalwarts Jordan Henderson, Fabinho and Naby Keita for young promising talents including Alexis Mac Alister from Brighton and Leipzig's Hungarian star Dominik Szoboszlai. The club is also circling Southampton's former City midfielder Romeo Lavia, Brighton's Moises Caicedo and Fluminense's Andre Trindade.

Despite Klopp’s midfield rebuild, the AI model calculated City were almost five times more likely to win the title than Liverpool, with the Sky Blues’ financials might likely tipping them past their title rivals.

Mikel Arteta’s Arsenal were the surprise nearly men last time out, look set to finish behind Liverpool and Man City in third. Arsenal looked all but certain to win the league last year before falling away in the Spring, allowing City to catch up.

To push the Gunners on, Arteta has signed West Ham’s Declan Rice for a club and British record transfer worth up to £105 million ($133 million). Arsenal has also brought in Chelsea attacking midfielder Kai Havertz and Ajax defender Jurrien Timber and is in talks with Brentford over £40 million ($50 million) goalkeeper David Reya.

Arsenal may have defeated City on the weekend in the Community Shield at Wembley, but the North London side will need more than penalties to challenge last season’s treble winners.

Rounding out the Champions League spots is Erik Ten Hag's Manchester United. The Red Devil's title hopes look slim, however, with the machine learning model calculating a title probability of just 3% compared to the neighbor's city with 61%.

Ten Hag’s United will be joined by Rasmus Højlund. The 20-year-old striker joined from Atalanta in a £72 million ($91 million) deal to lead the line for a United side desperate for goals. Marcus Rashford was the club’s leading Premier League scorer with 17 goals, but no other player scored over 10 goals last season. Højlund scored 10 goals for Atalanta last season and is largely seen as a long-term attacking option for the club.

Saudi-owned Newcastle was the highest of the non-Champions League clubs, pipping a potentially Harry Kane-less Tottenham and topsy-turvey Chelsea, who finished lowly eighth and 12th last season, respectively.

Brighton, Aston Villa and Brentford look set to continue their fine forms last season, but the machine learning model places them below the bigger boys this season. West Ham, who won their first trophy in 43 years after clinching the Europa Conference League last year, are just behind the trio, though a lack of transfer activity due to issues in the club’s hierarchy could see them fall behind.

Facing the drop according to AI is new boys Luton Town. The club is set to play in the Premier League for the first time in its history. Just five years ago, the Hatters won promotion from League Two, the fourth tier of English football, and now find themselves against some of the biggest names in the game.

Also predicted to be relegated is Nottingham Forrest. Forrest famously brought in an entirely new squad when they came up from the Championship last season. Steve Cooper brought in 30 total players throughout the season to help them save the drop, including former Man Utd midfielder Jesse Lingard and Morgan Gibbs-White from Wolves for a whopping £42.5 million ($54 million).

Sharing Forest’s probability of being relegated is Bournemouth, who fired Gary O’Neill despite saving them from the drop last time out. O’Neill was shown the door by owner Bill Foley in favor of Rayo Vallenco manager Andoni Iraola.

The next likely team to get relegated is Wolves, who saw manager Julien Lopetegui depart by mutual consent. The former Spain coach was unhappy with the lack of funds to expand his squad, having only brought in former Wolves full-back Matt Doherty on a free transfer. Newly promoted Sheffield United, back in the big time since 2021, are also predicted to go down.

AI predicts the Premier League: How does it work?

For the 2023/24 Premier League season, the team at used machine learning to predict the probability of the season's results.

The minds behind the system are Lucas Maystre and Victor Kristof. The pair met at EPFL (École polytechnique fédérale de Lausanne) in Switzerland. Alongside, Kristof is the founder and CEO of DemoSquare, an online platform for automating the monitoring and analysis of legal and political data, and Maystre is a research scientist at Spotify.

The pair employ a statistical model of football matches. Taking data on previous season performances, the team modeled the outcome of matches to figure out where teams would end up. The model currently ignores the squad, so it won’t take into account transfers that have been made over the summer.

They employ a method dubbed ‘Kickscore’ – a rough measure of a team's performance over time. Kickscore encodes how a model "sees" a team based on the data it has. The website explains: “As it is dynamic, it is possible to interpret how a team's strength evolved over the past decades.”

Kristof and Maystre began the project in 2016, working on statistical models to predict the results of the 2016 Euros in France.

The pair perfected their model, applying it to the 2018 World Cup in Russia and have been running their prediction engine for Europe’s top five football leagues ever since.’s platform is mainly used by sports fans looking for a “hot tip,” the pair said, but added it could be used to detect possible match-fixing, with the model able to identify potentially suspicious results. TV broadcasters have also shown an interest, to provide context to viewers.

Data is already making huge strides in football. Teams like Brighton and Brentford have improved on the pitch by utilizing huge data projects off it to improve player monitoring and scouting, which is something the Kickoff team is exploring using a machine learning model focused on individual players – analyzing particular skills or strengths – to further augment scouting.

Results analysis: Can anyone stop Man City?

Up until the Newcastle takeover, Man City have immense financial clout. The Abu Dhabi-backed outfit is at the top of the Deloitte Money League as the richest football club in the world and routinely brings in some of the best talent in the world.

Reacting to the AI predictions, Lucas admitted surprise at the “magnitude” of the probability that Man City would win the 23/24 title, saying: "I wasn't surprised they would come out on top but being five times more likely than Arsenal sounded like a lot.”

The pair noted that the model may have some difficulty predicting teams that came up from the Championship, like Burney. Kompany's Clarets raked up 101 points last season, routinely blowing opposition sides away.’s model picked up potential regressions for historically larger teams, like Chelsea and Tottenham, who have underwhelmed of late.

After winning the Champions League the season before last, Chelsea sacked coach Thomas Tuchel mere weeks into the season and brought in Graham Potter from Brighton, only to later sack him, all while spending £585.5 million ($745 million) on player transfers.

Maystre said, “It’s hard, it feels like this is not going to be the season where Chelsea does something great. It’s interesting what the model is telling us as it’s maybe not what I would have instinctively said myself.”

Tottenham meanwhile has been in decline since reaching the 2019 Champions League final. Despite England's all-time leading goal scorer Harry Kane leading the line, high-pedigree coaches including Jose Mourinho, Antonio Conte and Nuno Espirito Santo all failed to push the team onto glory.

“It could be interesting to run this simulation again after five, 10 and 20 weeks, just to see how things change compared to the initial predictions,” Kristof added.

Predicting the Premier League is no easy feat. No one could have envisioned lowly Leicester City taking home the trophy with odds of 5000-to-1 in 2016, but it happened. AI could improve on the predictions, but the unpredictability of the Premier League is what makes it the best football league in the world.

About the Author(s)

Ben Wodecki

Jr. Editor

Ben Wodecki is the Jr. Editor of AI Business, covering a wide range of AI content. Ben joined the team in March 2021 as assistant editor and was promoted to Jr. Editor. He has written for The New Statesman, Intellectual Property Magazine, and The Telegraph India, among others. He holds an MSc in Digital Journalism from Middlesex University.

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