RisingTransfers
⬡ AI DNA · Live season
Nottingham Forest

Best Alternatives to Zach Abbott

Centre BackEngland20y€300KFull profile →
Solid DefenderSmall Sample
1.07Tkl/90
0.36KP/90

Based on 505 min · 2025/2026 · Premier League · PARTIAL

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

DNA matchPrioritizes Premier League & top-tier peers

Top 3 alternatives to Zach Abbott

  1. William Saliba80% match

    Arsenal · Premier League · €90.0M

  2. Gabriel Magalhães80% match

    Arsenal · Premier League · €75.0M

  3. Josko Gvardiol 80% match

    Manchester City · Premier League · €70.0M

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

Solid DefenderSmall Sample

A Solid Defender. Statistically, he stands out as uses long balls frequently (5.2/90). Note: this profile is based on 505 minutes of playing time this season. The three closest DNA matches to Zach Abbott:

  • William Saliba(80% match) Saliba has quietly become the most complete ball-playing centre-back in the Premier League—a defender who makes the game look administrative. His 92.7% pass accuracy and 76 passes per 90 place him in the top 5% of defenders in the division, yet the more revealing figure is his 6.81 passes into the final third per 90, putting him in the top 20%—this isn't a man simply recycling possession, he's actively driving attacks from deep.
  • Gabriel Magalhães(80% match) A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (5.9 clearances/90), meticulous in distribution (88% pass accuracy), wins the physical battle (65% duel success), central to possession (71 touches/90), strong in aerial duels (3.2 aerials won/90) and uses long balls frequently (5.8/90).
  • Josko Gvardiol (80% match) A Ball-Playing CB. Statistically, he stands out as naturally left-footed, commanding in the air (4.0 clearances/90), meticulous in distribution (90% pass accuracy), wins the physical battle (56% duel success), heavily involved in possession (68 passes/90), penetrates with forward passing (9.2 final-third passes/90), central to possession (82 touches/90) and uses long balls frequently (5.0/90).

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

Comparison Base
Zach Abbott
DefenderEnglandPremier League€300K

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 Zach Abbott vs William Saliba, Gabriel Magalhães, and Josko Gvardiol . Post to X or WhatsApp — DNA + season totals from RT.

Zach Abbott RT player card

Source · Zach Abbott

William Saliba RT player card

Alt · William Saliba

Gabriel Magalhães RT player card

Alt · Gabriel Magalhães

Josko Gvardiol  RT player card

Alt · Josko Gvardiol 

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

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Frequently Asked Questions

Who are the best alternatives to Zach Abbott?
The top alternatives to Zach Abbott based on AI DNA playing style analysis include: William Saliba, Gabriel Magalhães, Josko Gvardiol , Marc Guéhi, Micky van de Ven. 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 Zach Abbott in 2026?
Players with a similar profile to Zach Abbott in 2026 include William Saliba (€90.0M), Gabriel Magalhães (€75.0M), Josko Gvardiol  (€70.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Zach Abbott play and who plays similarly?
Zach Abbott plays as a Defender. Players with a comparable positional profile include William Saliba (France, €90.0M); Gabriel Magalhães (Brazil, €75.0M); Josko Gvardiol  (Croatia, €70.0M); Marc Guéhi (England, €65.0M).
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.