RisingTransfers
AI DNA Similarity

Best Alternatives to Lorenzo Scipioni

Players most similar to Lorenzo Scipioni (Midfielder, €3.7M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Lorenzo Scipioni

  1. 1.Niccolò Pisilli85% DNA match·Roma€12.0M
  2. 2.Morten Frendrup84% DNA match·Genoa€18.0M
  3. 3.Luca Lipani84% DNA match·Sassuolo€7.5M

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

RT

Intelligence Verdict

Chances MissedTop 0%

A Ball-Winner....

See Full Verdict + Share Card →

Playing Style Analysis

Ball-WinnerDefensiveSmall Sample

A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (5.0 tackles/90), wins the physical battle (62% duel success), penetrates with forward passing (9.2 final-third passes/90), wins the ball cleanly (3.6 successful tackles/90), heavily involved in play (67 touches/90), switches play with precision (5.8 long balls/90, 67% accuracy), a high-intensity presser (press score 3.6/90), constantly disrupting opposition build-up and top 10% tackler in the league. Note: this profile is based on 672 minutes of playing time this season. The three most similar players to Lorenzo Scipioni by playing style are:

  • Niccolò Pisilli(85% match)Pisilli is the rare midfielder who wins the ball back with his brain before his boots ever get involved. Playing for a mid-table Serie A side, he ranks in the top 5% of his position for both interceptions and press intensity—a combination that signals elite anticipatory intelligence rather than mere industry. His passing into the final third sits in the same elite bracket, meaning he doesn't just win possession; he immediately weaponises it.
  • Morten Frendrup(84% match)A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.8 tackles/90), meticulous in distribution (87% pass accuracy), wins the physical battle (59% duel success), wins the ball cleanly (2.1 successful tackles/90), heavily involved in play (51 touches/90), a high-intensity presser (press score 3.1/90), constantly disrupting opposition build-up and top 10% tackler in the league.
  • Luca Lipani(84% match)A Ball-Winner. Statistically, he stands out as an aggressive ball-winner (2.9 tackles/90), heavily involved in play (58 touches/90), active off the ball (2.7 press score/90), contributing to defensive transitions and top 10% tackler in the league. However, he prone to committing fouls (2.7/90).

Transfer Intelligence

Niccolò Pisilli delivers 85% of the same playing style, at a 227% premium over Lorenzo Scipioni, with 0.94 key passes per 90 at age 21.

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

L
Comparison Base
Lorenzo Scipioni
MidfielderArgentina€3.7M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
N
Niccolò Pisilli
Roma · Serie A
Italy21yContract 2029
KP/900.94
G/900.27
Chance Creator
Last 5: ↓ Dip
vs Scipioni: €8M more expensive
85% match
€12.0M
#2
M
Morten Frendrup
Genoa · Serie A
Denmark25yContract 2028
KP/900.23
G/900.06
Ball-WinnerDefensive
Last 5: ↓ Dip
vs Scipioni: €14M more expensive · 4y older
84% match
€18.0M
#3
L
Luca Lipani
Sassuolo · Serie A
Italy20yContract 2028
KP/901.12
G/900.00
Ball-WinnerDefensive
Last 5: ↑ Hot
84% match
€7.5M
#4
H
Hugo Magnetti
Brest · Ligue 1
France27yContract 2027
KP/900.48
G/900.10
Balanced Midfielder
Last 5: → Stable
83% match
€6.0M
#5
M
Michel Aebischer
Pisa · Serie A
Switzerland29yContract 2026
KP/901.05
G/900.00
Balanced Midfielder
Last 5: ↑ Hot
83% match
€4.0M
#6
A
Antoine Bernede
Hellas Verona · Serie A
France26yContract 2028
KP/901.26
G/900.07
CreatorDefensive
84% match
€3.5M
#7
P
Patrizio Masini
Genoa · Serie A
Italy25yContract 2028
KP/900.84
G/900.00
Ball-WinnerDefensive
Last 5: → Stable
84% match
€6.0M
#8
J
Jan Schöppner
Heidenheim · Bundesliga
Germany26yContract 2028
KP/900.63
G/900.27
Balanced MidfielderSmall Sample
84% match
€4.0M
#9
R
Robin Fellhauer
FC Augsburg · Bundesliga
Germany28yContract 2029
KP/900.68
G/900.10
Box-to-BoxSmall Sample
83% match
€3.0M
#10
N
Neil El Aynaoui
Roma · Serie A
France24yContract 2030
KP/900.76
G/900.13
Last 5: → Stable
83% match
€20.0M
#11
D
Danilo Cataldi
Lazio · Serie A
Italy31yContract 2027
KP/901.06
G/900.14
Ball-Winner
82% match
€3.5M
#12
E
Ellyes Skhiri
Eintracht Frankfurt · Bundesliga
Tunisia31yContract 2027
KP/900.38
G/900.00
Ball-WinnerSmall Sample
83% match
€6.0M

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 Lorenzo Scipioni.

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Frequently Asked Questions

Who are the best alternatives to Lorenzo Scipioni?
The top alternatives to Lorenzo Scipioni based on AI DNA playing style analysis include: Niccolò Pisilli, Morten Frendrup, Luca Lipani, Hugo Magnetti, Michel Aebischer. 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 Lorenzo Scipioni in 2026?
Players with a similar profile to Lorenzo Scipioni in 2026 include Niccolò Pisilli (€12.0M), Morten Frendrup (€18.0M), Luca Lipani (€7.5M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Lorenzo Scipioni play and who plays similarly?
Lorenzo Scipioni plays as a Midfielder. Players with a comparable positional profile include Niccolò Pisilli (Italy, €12.0M); Morten Frendrup (Denmark, €18.0M); Luca Lipani (Italy, €7.5M); Hugo Magnetti (France, €6.0M).
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.