At the heart of Manchester City's transfer operation lies a deceptively simple question that guides every recruitment decision: "What does it take to win?"
This philosophy underpins the club's sophisticated data infrastructure, which breaks the challenge into three interconnected components: identifying potential signings, rigorously evaluating their capabilities, and determining how the club could develop them further. The ultimate goal remains constant—to enhance the statistical probability of City winning the Premier League title.
During the previous campaign, City's data department projected the club would remain competitive in the title race, though their algorithms indicated Arsenal held the edge as favourites. That projection proved accurate. This season, with five consecutive Premier League victories already secured, City's analysts have maintained discretion about their updated forecasts, though supporters and commentators increasingly view them as Arsenal's primary challengers.
The club's commitment to data-driven decision-making sits at the core of their efforts to narrow the gap with Arsenal. According to a comprehensive review of City's transfer activity, the club completed a Premier League-record summer spend of £458m while fundamentally reshaping their squad. This represents the scale of transformation underpinned by their analytical approach.
City's data philosophy extends across the Premier League and beyond, reflecting a broader industry shift toward quantitative analysis in transfer strategy and performance monitoring. At City specifically, one foundational objective is to minimise the risk inherent in any market transaction, whether acquiring or selling players.
The club's sporting director Hugo Viana outlined the framework during an interview with a national broadcaster.
Data plays a role in our decision-making, but it is just one part of the overall picture,he explained.
We know data cannot tell us everything about a player. It cannot fully show a person's character, mentality or behaviour. That is why we study data insights but focus on the expertise of our scouts and other specialists.
Despite the prominence data has assumed behind the scenes at the Etihad, traditional scouting remains the primary mechanism through which City determines whether to pursue a player. The analytical systems have grown significantly in influence, yet they operate in concert with established recruitment expertise rather than replacing it.
How City narrows 650,000 candidates to their top target
Every recruitment process at City begins with the same starting point: a database containing information on 650,000 footballers distributed across the globe. The next phase requires clarity on the specific profile the club seeks to recruit.
This initial brief extends beyond simply naming a position. City categorises full-backs, for instance, into three distinct types: those emphasising defensive solidity, those who drift infield to support midfield play, and those deployed high and wide on the flank. Once the data department receives the recruitment brief, they apply filtering criteria that assess overall player ability, systematically reducing the 650,000-name pool to between 20 and 50 candidates.
Juventus full-back Andrea Cambiaso exemplifies how this process functions in practice. City's data systems highlighted Cambiaso after identifying his particular strength in drifting inside to construct play through the midfield. His two-footedness registered as a significant positive within their evaluation framework. Following consultation between data analysts and scouting staff, the club determined not to pursue Cambiaso in the previous transfer window, though their methodology suggests he will remain under continuous observation.
The initial 20-to-50-name longlist undergoes cross-referencing with the scouting department's independent longlist. Typically, substantial overlap exists between players identified through algorithmic analysis and those already flagged by traditional scouts. Additional refined metrics are then applied to rank and prioritise candidates within this cohort.
Scouts conduct further investigative work to compress the list to approximately six players maximum. At this juncture, City initiates deeper analysis into the remaining candidates, encompassing examination of injury records, athletic performance data, and behavioural patterns. All information is subsequently consolidated into individual reports termed acquisition packs, which contain the key metrics informing the final decision on each player.
These acquisition packs incorporate a 'radar chart' that rates a spectrum of specific on-field metrics tailored to the recruitment brief. When Jeremy Doku was signed in 2023, then-manager Pep Guardiola specified he wanted a winger capable of direct running, similar to Leroy Sane, because the squad already contained Jack Grealish and Riyad Mahrez, both preferring to retain possession and cut infield. The recruitment criteria established for this position included making runs into the box, pressure regains, take-on percentage, and opposition-half pressure. Doku's overall numbers aligned with Guardiola's requirements, though his 'making the box' metric ranked among his lowest readings. Since arriving at City, Doku has improved this particular rating—a development City attributes to their data systems' capacity to identify and facilitate player improvement.
The acquisition packs also contain a 'utilisation chart' documenting how frequently the player has featured across a three-year period, alongside a scouting grade reflecting how highly traditional scouts rate the individual. Each candidate receives a 'current impact score' predicting the immediate impression they would make upon signing, and a 'potential impact score' projecting their future contribution.
Perhaps the most revealing metric on the acquisition packs is the 'action value score', which positions players within a comparative league table encompassing both City players and rivals operating in similar roles. Once acquisition reports have been evaluated, the list narrows further to 2-3 players after City's valuation assessment is factored in. Data contributes substantially to determining the price range City believes a player occupies, and valuations are never expressed as single figures.
A decision then follows regarding which player becomes the priority, though all shortlisted candidates are worked on simultaneously to accommodate changing circumstances—such as a player becoming unavailable. City's data team emphasises their growing adeptness at responding flexibly to market developments. When Yan Diomande emerged as a prospect last season, City completed preliminary checks before he joined Real Madrid from RB Leipzig. The club similarly monitored Eduardo Camavinga's metrics in case Real Madrid considered selling a midfielder.
Why Elliot Anderson proved data's limitations and strengths
On the surface, Elliot Anderson represented an obvious signing for a top Premier League club. The 23-year-old had developed into a key player for Nottingham Forest, with the additional appeal of being English and having established himself in the national team. City prevailed over other elite clubs, including Manchester United, to secure his services. The decision appeared straightforward.
Yet the manner in which City analysed Anderson's profile illuminates their forensic approach even when, superficially, such comprehensive evaluation might seem unnecessary given his evident quality. Their continued application of algorithmic analysis and adherence to standard procedures underscores the demands of elite football in the contemporary era—and simultaneously reveals data's inherent limitations.
Surprisingly, Anderson's metrics did not immediately capture attention. At the start of the previous season, despite emerging uncertainty surrounding Guardiola's future, City recognised they would require at least one central midfielder during the summer window. They anticipated Bernardo Silva's departure while doubts persisted regarding Rodri and Nico Gonzales' futures. The club acknowledged that replacing Silva and Rodri on a like-for-like basis would prove virtually impossible, so they sought a player equally capable of constructing play from deep or advanced central midfield positions.
As the season progressed, uncertainty also emerged regarding Tijjani Reijnders' future—though Enzo Fernandez was regarded as the favoured replacement for the Dutch midfielder. Anderson advanced from the initial 650,000-player database to the longlist, but did not rank highly within that group. His metric readings did not immediately signal the obvious choice he ultimately became.
Upon closer examination, Anderson's case highlighted certain data limitations. He did not accumulate substantial goal tallies for Forest or consistently register assists. Because Forest generally operate without the possession dominance City maintain, his algorithmic metrics failed to generate immediate attention. City's data analysts recognised that, since Anderson typically played closer to his own goal than he would at City, he lacked opportunities to demonstrate capability in the final third.
Consequently, they examined closely what Anderson accomplished at Forest and modelled his prospective role within a City team that typically dominates possession, plays closer to the opposition goal, and features more elite-level players. Criteria graded on Anderson's 'radar chart' encompassed defensive regains, duel success, line-breaking passes, aerial-duel success, and defensive errors. Regarding his defensive-error reading, analysts acknowledged that, because Forest operated as a transitional side, certain errors resulted from the pitch areas where he was deployed. He might regain possession deep within his own half but lose the ball attempting a longer, riskier pass after being instructed to play forward quickly. In City's system, Anderson would likely possess options to execute shorter passes with superior success rates.
Just because a player doesn't have the opportunity to perform a particular action on a regular basis because of the team he is playing doesn't mean he can't do it,explained a source within City's data operation.
Anderson's data readings improved markedly as the season advanced, prompting City's scouts to monitor him consistently. He compared favourably against City's existing midfielders and against a roster of rival players the club had identified as potential signings in that position. The comprehensive diligence completed by City's data team, scouts, and other specialists meant that despite Anderson's price escalating beyond City's initial valuation assessment, the club perceived the risk as manageable.
Viana reflected on the signing's significance to the club's methodology.
Elliot Anderson is a great example of how the process works. The data was positive for Elliot and gave us real confidence in his profile, but it was the insight from our scouts and wider performance team that helped us understand the player and his attributes and this proved our belief that he was the right fit for the club.
According to a detailed squad audit, City spent more than £500m and recouped close to £300m across the two-window rebuild. One analysis indicated City spent £326m specifically revamping the centre of the pitch, with the midfield reconstruction representing the most significant component of the overall transformation.
How data identified Alvarez and Khusanov before they became stars
City's data operation provided fascinating insight into how algorithmic analysis facilitated the signing of Julian Alvarez from River Plate for £14m in 2022. The initial recommendation originated from scouts, and given Alvarez was not a player originally identified through data metrics, the analytical team conducted deeper investigation.
Because the Argentine league is not recognised among the world's strongest competitions, City's standard data parameters mean players from that division reach a natural ceiling in their readings compared to those competing in Europe's top five leagues. City therefore examined Alvarez's statistics more thoroughly, focusing on his impact both with and without the ball and his influence on River's match outcomes. The analysis revealed Alvarez as by far the strongest performer in Argentine football's top division, providing sufficient evidence for City to project he would develop into a starter for a top-half club in one of Europe's elite leagues within two-and-a-half years.
City's data model valued Alvarez between £26m and £40m. The club signed him for £14m, believing they had acquired an undervalued asset. Alvarez's projected value after three years stood at £70m. City eventually sold him to Atletico Madrid in 2024 for £81m, validating the initial assessment.
The acquisition of Abdukodir Khusanov from Lens provides equally intriguing evidence of City's reliance on data-driven recruitment. The 22-year-old did not initially appear on City's 50-name longlist, but closer inspection revealed that while his output on the ball required development, his physical data—particularly covering runs behind the defensive line—registered exceptionally highly. Since signing in January 2025, Khusanov's on-the-ball metrics have improved substantially, according to City's assessment.
How managerial change affects City's data-driven approach
Guardiola's departure and Enzo Maresca's arrival are not anticipated to alter City's fundamental methodology significantly. The key metrics Maresca prioritises in player evaluation are understood to closely resemble Guardiola's approach, with the notable distinction that the Italian prefers full-backs operating with greater directness.
City's coaching recruitment process is anchored in a specific team philosophy and playing style, with any incoming manager expected to construct a side characterised by possession dominance, high pressing, elevated possession regains, quality chance creation, and entertaining football. This philosophy was established before Guardiola's appointment, and the Spanish manager embodied the purest expression of City's footballing ideology. Consequently, the managerial transition has not fundamentally reshaped how City's data department conducts its work.
Maresca will continue collaborating closely with the analytical team as he endeavours to establish his own dynasty, though much foundational squad-building work remains complete. Before City's Treble-winning campaign, internal data indicators signalled the club would soon require comprehensive squad overhaul, as the existing group had reached its performance peak.
Selling established players including Kevin de Bruyne, Kyle Walker, Riyad Mahrez, and Ilkay Gundogan proved difficult given their distinguished service and continued elite-level performances. Data, however, enables City to identify declining performance trajectories well in advance—frequently two or three years before a player is eventually sold. These particular metrics help City determine optimal selling moments, sometimes before rival clubs have detected performance deterioration.
When such trends are identified, the club can plan extensively ahead. The organisation then determines whether to integrate an academy player or enter the transfer market for a replacement. Ayyoub Bouaddi's arrival from Lille this summer exemplifies this approach. At 18 years old, City recognise he will not necessarily deliver profound impact this season—but the club projects the Moroccan will make substantially greater contributions within two years.
Following the Treble season, City's recruitment mandate centred on reducing the squad's average age while assembling players capable of delivering sustained success. However, accomplishing this objective at City carries a significant complication. Because City consistently face expectations to compete for trophies, lowering squad age while maintaining title-winning performance presents far greater complexity than age reduction alone.
In previous years, City's data systems identified the former Brighton trio of Moises Caicedo, Marc Cucurella, and Carlos Baleba, who have been lauded as data successes. However, City perceived that developing such signings would require excessive time before they could meaningfully impact a team mandated to win titles, or alternatively, they could be developed and sold for profit.
City have successfully reduced their squad's average age to the point where they now possess the third-youngest player group in the Premier League, behind Newcastle and Chelsea. However, through signings of goalkeeper Gianluigi Donnarumma, defender Marc Guehi, and midfielders Fernandez and Anderson, they have added players capable of not only maturing alongside the emerging generation but also bringing substantial top-level experience. According to City's sporting director, the club completed eight arrivals during the 2026 summer window: Elliot Anderson, Geronimo Rulli, Ayyoub Bouaddi, Jeremy Monga, Pierce Charles, Allan Elias, Iliman Ndiaye, and Enzo Fernandez.
City's data projections indicate their current squad will not reach peak performance for another two to three years, though algorithms simultaneously project the club will likely rank among title challengers this season. Whether these projections prove accurate will become evident as the campaign unfolds.
