RisingTransfers
AI DNA Similarity

Best Alternatives to Francesco Camarda

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

Top 3 Alternatives to Francesco Camarda

  1. 1.Kamaldeen Sulemana86% DNA match·Atalanta€18.0M
  2. 2.Nicolò Cambiaghi85% DNA match·Bologna€18.0M
  3. 3.Samuele Mulattieri85% DNA match·Sassuolo€6.0M

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

RT

Intelligence Verdict

Aerials WonTop 7%
???Bottom 0%

A Forward....

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Playing Style Analysis

Small Sample

A Forward. Note: this profile is based on 663 minutes of playing time this season. The three most similar players to Francesco Camarda by playing style are:

  • Kamaldeen Sulemana(86% match)A Dynamic Forward. Statistically, he stands out as a regular goalscorer (0.22 goals/90), a reliable supplier (0.22 assists/90) and a dynamic dribbler (2.1/90). Note: this profile is based on 808 minutes of playing time this season.
  • Nicolò Cambiaghi(85% match)Cambiaghi is the rare forward who earns his place through relentless service rather than spectacular finishing—a creator wearing a striker's shirt. His 0.27 assists per 90 ranks in Serie A's top 10%, yet his goals return sits stubbornly average, which tells you exactly where his value lives: in the final pass, not the final touch. What the assist numbers don't immediately reveal is his defensive engine—tackles won in the top 10% league-wide is extraordinary for an attacker, suggesting a pressing machine who genuinely disrupts rather than just gestures at it.
  • Samuele Mulattieri(85% match)Mulattieri is the kind of striker who wins headers in Serie A but struggles to win the ball at his feet—a physical presence in the box who remains curiously invisible in open play. His aerial win rate sits above the league average for attackers, a legitimate weapon in the right system, and his dribble volume places him in the top 20%—suggesting more directness than his overall profile implies. The counterintuitive read here: his low pass volume isn't laziness, it's positioning; he operates in tight spaces where recycling the ball simply isn't his job.

Transfer Intelligence

Kamaldeen Sulemana delivers 86% of the same playing style, at a 20% premium over Francesco Camarda, with 0.21 goals per 90 at age 24. That's 105% of Francesco Camarda's output in goals per 90 — a credible like-for-like option.

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

F
Comparison Base
Francesco Camarda
AttackerItaly€15.0M
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Similar Players — Ranked by DNA Similarity

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 Francesco Camarda.

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Frequently Asked Questions

Who are the best alternatives to Francesco Camarda?
The top alternatives to Francesco Camarda based on AI DNA playing style analysis include: Kamaldeen Sulemana, Nicolò Cambiaghi, Samuele Mulattieri, Patrick Cutrone, Andrea Pinamonti. 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 Francesco Camarda in 2026?
Players with a similar profile to Francesco Camarda in 2026 include Kamaldeen Sulemana (€18.0M), Nicolò Cambiaghi (€18.0M), Samuele Mulattieri (€6.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Francesco Camarda play and who plays similarly?
Francesco Camarda plays as a Attacker. Players with a comparable positional profile include Kamaldeen Sulemana (Ghana, €18.0M); Nicolò Cambiaghi (Italy, €18.0M); Samuele Mulattieri (Italy, €6.0M); Patrick Cutrone (Italy, €5.0M).
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.