RisingTransfers
AI DNA Similarity

Best Alternatives to Gianluca Mancini

Players most similar to Gianluca Mancini (Defender, €15.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Gianluca Mancini

  1. 1.Alessio Romagnoli86% DNA match·Lazio€7.0M
  2. 2.Amir Rrahmani 86% DNA match·Napoli€12.0M
  3. 3.Jacobo Ramón85% DNA match·Como€18.0M

Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.

RT

Intelligence Verdict

Chances MissedTop 0%

Mancini has quietly built one of the most complete defensive profiles in Serie A...

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Playing Style Analysis

Ball-Playing CB

Mancini has quietly built one of the most complete defensive profiles in Serie A — a centre-back whose football intelligence does the heavy lifting before his legs ever need to. His interception rate lands in the top 10% of the league, which tells the real story: this isn't a defender who relies on last-ditch tackles — average by league standards — but one who simply isn't there when danger arrives because he read it two seconds earlier. His progressive passing output places him in the top 20%, and with 6.68 passes into the final third per 90, he's functioning closer to a deep-lying playmaker than a pure stopper. The three most similar players to Gianluca Mancini by playing style are:

  • Alessio Romagnoli(86% match)A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (4.8 clearances/90), meticulous in distribution (92% pass accuracy), wins the physical battle (57% duel success), heavily involved in possession (66 passes/90) and central to possession (76 touches/90).
  • Amir Rrahmani (86% match)A Ball-Playing CB. Statistically, he stands out as meticulous in distribution (91% pass accuracy), wins the physical battle (66% duel success), heavily involved in possession (79 passes/90), central to possession (89 touches/90), dominant in the air (3.4 aerials won/90, 63%), uses long balls frequently (5.0/90) and active off the ball (2.0 press score/90), contributing to defensive transitions.
  • Jacobo Ramón(85% match)A Ball-Playing CB. Statistically, he stands out as active in the tackle (1.9 tackles/90), meticulous in distribution (91% pass accuracy), wins the physical battle (63% duel success), heavily involved in possession (73 passes/90), central to possession (87 touches/90), dominant in the air (3.7 aerials won/90, 70%) and active off the ball (2.4 press score/90), contributing to defensive transitions.

Transfer Intelligence

Alessio Romagnoli delivers 86% of the same playing style, at 53% lower cost (€7.0M vs €15.0M), with 0.77 tackles won per 90 at age 31.

Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →

G
Comparison Base
Gianluca Mancini
DefenderItaly€15.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
A
Alessio Romagnoli
Lazio · Serie A
Italy31yContract 2027
Tkl/900.77
KP/900.18
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Mancini: €8M cheaper
86% match
€7.0M
#2
A
Amir Rrahmani 
Napoli · Serie A
Kosovo32yContract 2027
Tkl/901.14
KP/900.07
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Mancini: 2y older
86% match
€12.0M
#3
J
Jacobo Ramón
Como · Serie A
Spain21yContract 2030
Tkl/901.95
KP/900.43
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
vs Mancini: 9y younger
85% match
€18.0M
#4
M
Manuel Akanji
Inter · Serie A
Switzerland30yContract 2026
Tkl/901.47
KP/900.20
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
85% match
€22.0M
#5
O
Oumar Solet
Udinese · Serie A
France26yContract 2027
Tkl/902.13
KP/900.67
Ball-Playing CBBall-Playing
Last 5: ↑ Hot
85% match
€20.0M
#6
L
Luca Ranieri
Fiorentina · Serie A
Italy27yContract 2028
Tkl/901.36
KP/900.40
Ball-Playing CBAerial
Last 5: ↓ Dip
85% match
€7.0M
#7
L
Lloyd Kelly
Juventus · Serie A
England27yContract 2029
Tkl/901.77
KP/900.11
Ball-Playing CBBall-Playing
Last 5: → Stable
85% match
€20.0M
#8
P
Pierre Kalulu
Juventus · Serie A
France25yContract 2029
Tkl/902.17
KP/901.25
Ball-Playing CBBall-Playing
Last 5: → Stable
85% match
€32.0M
#9
Y
Yann Bisseck
Inter · Serie A
Germany25yContract 2029
Tkl/900.98
KP/900.20
Last 5: ↓ Dip
85% match
€35.0M
#10
A
Alessandro Buongiorno
Napoli · Serie A
Italy26yContract 2029
Tkl/900.98
KP/900.00
Reading Defender
Last 5: ↑ Hot
85% match
€45.0M
#11
A
Alessandro Bastoni
Inter · Serie A
Italy27yContract 2028
Tkl/902.31
KP/901.16
Ball-Playing CBBall-Playing
Last 5: ↓ Dip
84% match
€80.0M
#12
T
Thomas Kristensen
Udinese · Serie A
Denmark24yContract 2028
Tkl/901.08
KP/900.08
Physical StopperAerial
Last 5: ↓ Dip
85% match
€12.0M

Ask AI: Why are these players similar?

Our 768-dimension Player DNA model matches playing style, physical profile, pressing intensity, and tactical fit. Ask the AI to explain exactly what makes these players statistically similar to Gianluca Mancini.

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Frequently Asked Questions

Who are the best alternatives to Gianluca Mancini?
The top alternatives to Gianluca Mancini based on AI DNA playing style analysis include: Alessio Romagnoli, Amir Rrahmani , Jacobo Ramón, Manuel Akanji, Oumar Solet. These players were matched using Rising Transfers' 768-dimension DNA model across playing style, pressing intensity, and tactical fit — not just position or market value.
Which players are similar to Gianluca Mancini in 2026?
Players with a similar profile to Gianluca Mancini in 2026 include Alessio Romagnoli (€7.0M), Amir Rrahmani  (€12.0M), Jacobo Ramón (€18.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Gianluca Mancini play and who plays similarly?
Gianluca Mancini plays as a Defender. Players with a comparable positional profile include Alessio Romagnoli (Italy, €7.0M); Amir Rrahmani  (Kosovo, €12.0M); Jacobo Ramón (Spain, €18.0M); Manuel Akanji (Switzerland, €22.0M).
How does Rising Transfers find similar players?
Rising Transfers uses a proprietary 768-dimension Player DNA model trained on 3.2 million match events. Each player is represented as a vector across 35+ per-90 metrics including pressing intensity, passing footprint, dribbling profile, and defensive contribution. Similarity is measured using cosine distance — the same technique used in state-of-the-art AI systems — making it the most precise player comparison tool available publicly.