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AI DNA Similarity

Best Alternatives to Predrag Rajković

Players most similar to Predrag Rajković (Goalkeeper, €7.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Predrag Rajković

  1. 1.Vanja Milinković-Savić 87% DNA match·Napoli€20.0M
  2. 2.Ionuț Radu87% DNA match·Celta de Vigo€5.0M
  3. 3.David Raya87% DNA match·Arsenal€35.0M

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

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Intelligence Verdict

Tackles WonTop 10%
???Bottom 0%

Rajković is the rare goalkeeper who functions less like a last line of defence and more like an...

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Playing Style Analysis

Traditional Keeper

Rajković is the rare goalkeeper who functions less like a last line of defence and more like an aggressive midfielder wearing the wrong shirt. His press intensity ranks in the league's top 10%, and his tackles won per 90 place him in the top 5%—numbers that belong to a pressing forward, not a shot-stopper. He moves the ball forward with purpose too, ranking above average in passes into the final third, suggesting a keeper comfortable initiating attacks rather than simply recycling possession. The three most similar players to Predrag Rajković by playing style are:

  • Vanja Milinković-Savić (87% match)Milinković-Savić has quietly become one of Serie A's most progressive distributors from behind—a goalkeeper who functions less like a last line of defence and more like an extra midfielder in possession. His passing volume sits in the top 5% of Serie A goalkeepers, and crucially, nearly a fifth of those passes penetrate the final third, a figure that elite pressing teams would covet. The counterintuitive detail: his 69.8% pass accuracy sounds modest, but it reflects ambition—he's attempting the difficult ball, not the safe one.
  • Ionuț Radu(87% match)A Traditional Keeper. Statistically, he stands out as dominant in aerial duels (100% success).
  • David Raya(87% match)A Reliable Keeper. Statistically, he stands out as dominant in aerial duels (96% success) and keeps goals out effectively (0.72 conceded/90).

Transfer Intelligence

Vanja Milinković-Savić  delivers 87% of the same playing style, at a 186% premium over Predrag Rajković, and is 29 years old.

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

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Comparison Base
Predrag Rajković
GoalkeeperSerbia€7.0M
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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 Predrag Rajković.

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Frequently Asked Questions

Who are the best alternatives to Predrag Rajković?
The top alternatives to Predrag Rajković based on AI DNA playing style analysis include: Vanja Milinković-Savić , Ionuț Radu, David Raya, Vasilios Barkas, Diant Ramaj. 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 Predrag Rajković in 2026?
Players with a similar profile to Predrag Rajković in 2026 include Vanja Milinković-Savić  (€20.0M), Ionuț Radu (€5.0M), David Raya (€35.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Predrag Rajković play and who plays similarly?
Predrag Rajković plays as a Goalkeeper. Players with a comparable positional profile include Vanja Milinković-Savić  (Serbia, €20.0M); Ionuț Radu (Romania, €5.0M); David Raya (Spain, €35.0M); Vasilios Barkas (Greece, €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.