RisingTransfers
⬡ AI DNA · Live season
Cagliari

Best Alternatives to Leonardo Pavoletti

Centre ForwardItaly37y€700KFull profile →
Target ManProlificSmall Sample
0.42G/90
0.42A/90

Based on 434 min · 2024/2025 · Serie A · PARTIAL

Ranked by AI DNA similarity — playing style, pressing, and tactical fit. Below: the closest replacements with per-90 stats and form.

DNA matchPrioritizes Serie A & top-tier peers

Top 3 alternatives to Leonardo Pavoletti

  1. Lautaro Martínez80% match

    Inter · Serie A · €85.0M

  2. Marcus Thuram80% match

    Inter · Serie A · €60.0M

  3. Rasmus Højlund80% match

    Napoli · Serie A · €50.0M

Ranked by RT Player DNA + league/value credibility. Scroll for full list, per-90 stats, and share cards.

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Playing Style Analysis

Target ManProlificSmall Sample

Leonardo Pavoletti is a Target Man. Physical presence who wins duels and holds up play. Statistically, he stands out as an elite creator (1.9 key passes/90), a constant goal threat (3.7 shots/90), a proven goalscorer (0.41 goals/90), creates high-quality scoring opportunities (0.62 big chances/90), strong in aerial duels (11.4 aerials won/90) and top 20% scorer in the league. The three closest DNA matches to Leonardo Pavoletti:

  • Lautaro Martínez(80% match) Lautaro Martínez is the rare striker who makes Inter's system look inevitable—a physical, relentless finisher who bends games to his will rather than waiting for them to open up. His aerial win rate sits in the top 5% of Serie A attackers, a number that reframes him entirely: this isn't a small, slippery forward—he's a bulldozer with technique.
  • Marcus Thuram(80% match) Marcus Thuram is a Poacher. Clinical finisher who lives for goals inside the box.
  • Rasmus Højlund(80% match) Højlund arrived in Serie A carrying the blueprint of a modern target forward — raw, physical, and still being written. His goal return of 0.43 per 90 places him comfortably in the top 30% of Serie A attackers, a figure that flatters a player whose broader offensive contribution remains frustratingly thin.

Similarity uses per-90 performance across playing-style dimensions. How Player DNA matching works →

Comparison Base
Leonardo Pavoletti
AttackerItalySerie A€700K

Similar Players — Ranked by DNA Similarity

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Top 8 shown first · 16 total ranked by DNA + league fit.

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Download RT stat cards for Leonardo Pavoletti vs Lautaro Martínez, Marcus Thuram, and Rasmus Højlund. Post to X or WhatsApp — DNA + season totals from RT.

Leonardo Pavoletti RT player card

Source · Leonardo Pavoletti

Lautaro Martínez RT player card

Alt · Lautaro Martínez

Marcus Thuram RT player card

Alt · Marcus Thuram

Rasmus Højlund RT player card

Alt · Rasmus Højlund

Want a deeper take? Scroll to Ask RT below — same shortlist, multi-turn chat.

Ask about replacements for Pavoletti

Same DNA shortlist as above — budget fit, who to avoid, or why the top match works.

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Frequently Asked Questions

Who are the best alternatives to Leonardo Pavoletti?
The top alternatives to Leonardo Pavoletti based on AI DNA playing style analysis include: Lautaro Martínez, Marcus Thuram, Rasmus Højlund, Moise Kean, Loïs Openda. 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 Leonardo Pavoletti in 2026?
Players with a similar profile to Leonardo Pavoletti in 2026 include Lautaro Martínez (€85.0M), Marcus Thuram (€60.0M), Rasmus Højlund (€50.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Leonardo Pavoletti play and who plays similarly?
Leonardo Pavoletti plays as a Attacker. Players with a comparable positional profile include Lautaro Martínez (Argentina, €85.0M); Marcus Thuram (France, €60.0M); Rasmus Højlund (Denmark, €50.0M); Moise Kean (Italy, €45.0M).
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.