⬡ AI DNA · Live season

Portland Timbers· 2026 · Major League Soccer · PARTIAL

Best Alternatives to Kamal Miller

Centre BackCanada29y€570KFull profile →

Ball-Playing CBBall-PlayingAerial

0.71Tkl/90

0.00KP/90

Based on 558 min · 2026 · Major League Soccer · PARTIAL

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

Note: Top DNA style matches can come from lower leagues. We also surface Major League Soccer peers ranked by market value and league tier — scroll the full list below.

DNA matchDNA style match · see league & value below

Top 3 alternatives to Kamal Miller

Stefan de Vrij99% match
Inter · Serie A · €3.5M
Lars Bünning99% match
Dynamo Dresden · Bundesliga

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Playing Style Analysis

Ball-Playing CBBall-PlayingAerialSmall Sample

A Ball-Playing CB. Statistically, he stands out as commanding in the air (7.4 clearances/90), meticulous in distribution (92% pass accuracy), wins the physical battle (59% duel success), heavily involved in possession (70 passes/90), central to possession (84 touches/90), uses long balls frequently (6.3/90) and active off the ball (2.3 press score/90), contributing to defensive transitions. Note: this profile is based on 558 minutes of playing time this season. The three closest DNA matches to Kamal Miller:

Stefan de Vrij(99% match) — A Ball-Playing CB. Statistically, he stands out as active in the tackle (2.0 tackles/90), commanding in the air (4.6 clearances/90), meticulous in distribution (94% pass accuracy), wins the physical battle (64% duel success), heavily involved in possession (63 passes/90), central to possession (75 touches/90) and active off the ball (2.1 press score/90), contributing to defensive transitions.
Lars Bünning(99% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (6.8 clearances/90), wins the physical battle (67% duel success), penetrates with forward passing (10.3 final-third passes/90), dominant in the air (4.7 aerials won/90, 74%) and uses long balls frequently (9.6/90).
Friedrich Müller(99% match) — A Ball-Playing CB. Statistically, he stands out as commanding in the air (4.4 clearances/90), meticulous in distribution (90% pass accuracy), central to possession (71 touches/90) and active off the ball (2.4 press score/90), contributing to defensive transitions.

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

Comparison Base

Kamal Miller

DefenderCanadaMajor League Soccer€570K

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Similar Players — Ranked by DNA Similarity

Stefan de Vrij

Inter · Serie A

Netherlands34yContract 2026

Tkl/902.01

KP/900.27

Ball-Playing CBBall-PlayingSteady form

vs Miller: 5y older

99% match

€3.5M

Ask about replacements for Miller

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 Kamal Miller?▼

The top alternatives to Kamal Miller based on AI DNA playing style analysis include: Stefan de Vrij, Lars Bünning, Friedrich Müller, El Chadaille Bitshiabu, Adamo Nagalo. 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 Kamal Miller in 2026?▼

Players with a similar profile to Kamal Miller in 2026 include Stefan de Vrij (€3.5M), Lars Bünning (N/A), Friedrich Müller (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.

What position does Kamal Miller play and who plays similarly?▼

Kamal Miller plays as a Defender. Players with a comparable positional profile include Stefan de Vrij (Netherlands, €3.5M); Lars Bünning (Germany, N/A); Friedrich Müller (Germany, N/A); El Chadaille Bitshiabu (France, €15.0M).

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.

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