RisingTransfers
AI DNA Similarity

Best Alternatives to Raoul Bellanova

Players most similar to Raoul Bellanova (Midfielder, €22.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Raoul Bellanova

  1. 1.Benja Cremaschi86% DNA match·Parma€4.5M
  2. 2.Nicolò Barella84% DNA match·Inter€60.0M
  3. 3.Kristjan Asllani85% DNA match·Beşiktaş€13.0M

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

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Intelligence Verdict

Chances MissedTop 0%
???Bottom 0%

Bellanova has carved out a quietly efficient niche at Inter as the industrious connector who keeps...

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Playing Style Analysis

Chance Creator

Bellanova has carved out a quietly efficient niche at Inter as the industrious connector who keeps possession ticking without ever demanding the spotlight. His 89.1% pass accuracy places him in the top fifth of Serie A midfielders, and a 56.3% duel win rate suggests he competes effectively at ground level—two traits that underpin his value as a reliable ball-mover in tight spaces. Here's the counterintuitive part: his key passes per 90 sit above the league average, meaning he's actually more progressive in the final moments of build-up than his modest assists tally implies—the creativity is there, the finishing touch simply isn't his job. The three most similar players to Raoul Bellanova by playing style are:

  • Benja Cremaschi(86% match)A Box-to-Box. Statistically, he stands out as a capable chance creator (1.1 key passes/90), active in the tackle (2.4 tackles/90), wins the ball cleanly (1.8 successful tackles/90), heavily involved in play (58 touches/90) and active off the ball (2.7 press score/90), contributing to defensive transitions.
  • Nicolò Barella(84% match)Barella is the engine that makes Inter's midfield breathe—a box-to-box dynamo whose footballing intelligence operates at a frequency most teammates can only follow, not match. His key pass rate sits in Serie A's top 5%, and his assist numbers land in the top 10%, meaning the creativity isn't accidental—it's systematic. He moves the ball with purpose too, ranking in the top 10% for passes per 90 and top 20% for progressive distribution.
  • Kristjan Asllani(85% match)A Ball-Winner. Statistically, he stands out as a capable chance creator (1.4 key passes/90), wins the physical battle (56% duel success), penetrates with forward passing (10.5 final-third passes/90), heavily involved in play (69 touches/90), uses long balls frequently (10.2/90) and active off the ball (2.9 press score/90), contributing to defensive transitions. Note: this profile is based on 635 minutes of playing time this season.

Transfer Intelligence

Benja Cremaschi delivers 86% of the same playing style, at 80% lower cost (€4.5M vs €22.0M), with 1.10 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 →

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Comparison Base
Raoul Bellanova
MidfielderItaly€22.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
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Benja Cremaschi
Parma · Serie A
United States21yContract 2026
KP/901.10
G/900.06
Box-to-Box
vs Bellanova: €18M cheaper · 4y younger
86% match
€4.5M
#2
N
Nicolò Barella
Inter · Serie A
Italy29yContract 2029
KP/903.44
G/900.08
MetronomeCreative
Last 5: → Stable
vs Bellanova: €38M more expensive · 4y older
84% match
€60.0M
#3
K
Kristjan Asllani
Beşiktaş · Serie A
Albania24yContract 2026
KP/900.99
G/900.22
Ball-WinnerSmall Sample
Last 5: → Stable
vs Bellanova: €9M cheaper
85% match
€13.0M
#4
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Reda Belahyane
Lazio · Serie A
France21yContract 2029
KP/900.35
G/900.00
Ball-WinnerSmall Sample
84% match
€8.5M
#5
A
Albert Grønbæk
Hamburger SV · Serie A
Denmark24yContract 2026
KP/900.86
G/900.29
CreatorCreative
84% match
€8.0M
#6
N
Niccolò Pisilli
Roma · Serie A
Italy21yContract 2029
KP/900.94
G/900.27
Chance Creator
Last 5: ↓ Dip
84% match
€12.0M
#7
M
Morten Frendrup
Genoa · Serie A
Denmark25yContract 2028
KP/900.23
G/900.06
Ball-WinnerDefensive
Last 5: ↓ Dip
83% match
€18.0M
#8
N
Nikola Moro
Bologna · Serie A
Croatia28yContract 2027
KP/902.95
G/900.00
Chance Creator
Last 5: ↓ Dip
83% match
€6.5M
#9
J
Jens Odgaard
Bologna · Serie A
Denmark27yContract 2027
KP/900.76
G/900.33
CreatorSmall Sample
Last 5: ↑ Hot
83% match
€15.0M
#10
K
Kristian Thorstvedt
Sassuolo · Serie A
Norway27yContract 2027
KP/900.67
G/900.27
Box-to-BoxSmall Sample
Last 5: → Stable
83% match
€10.0M
#11
S
Simon Sohm
Bologna · Serie A
Switzerland25yContract 2030
KP/900.64
G/900.00
Box-to-BoxSmall Sample
Last 5: ↑ Hot
83% match
€8.0M
#12
M
Máximo Perrone
Como · Serie A
Argentina23yContract 2029
KP/900.93
G/900.17
Metronome
Last 5: → Stable
83% match
€25.0M

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 Raoul Bellanova.

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Frequently Asked Questions

Who are the best alternatives to Raoul Bellanova?
The top alternatives to Raoul Bellanova based on AI DNA playing style analysis include: Benja Cremaschi, Nicolò Barella, Kristjan Asllani, Reda Belahyane, Albert Grønbæk. 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 Raoul Bellanova in 2026?
Players with a similar profile to Raoul Bellanova in 2026 include Benja Cremaschi (€4.5M), Nicolò Barella (€60.0M), Kristjan Asllani (€13.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Raoul Bellanova play and who plays similarly?
Raoul Bellanova plays as a Midfielder. Players with a comparable positional profile include Benja Cremaschi (United States, €4.5M); Nicolò Barella (Italy, €60.0M); Kristjan Asllani (Albania, €13.0M); Reda Belahyane (France, €8.5M).
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.