RisingTransfers
AI DNA Similarity

Best Alternatives to Ishaq Abdulrazak

Players most similar to Ishaq Abdulrazak (Midfielder, €3.0M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Ishaq Abdulrazak

  1. 1.Magnus Mattsson83% DNA match·FC København€4.3M
  2. 2.Leon Avdullahu81% DNA match·TSG Hoffenheim€17.0M
  3. 3.Dani Silva82% DNA match·FC Midtjylland€3.5M

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

RT

Intelligence Verdict

???Bottom 0%

A Box-to-Box....

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Playing Style Analysis

Box-to-BoxSmall Sample

A Box-to-Box. Statistically, he stands out as active in the tackle (2.2 tackles/90) and meticulous in distribution (88% pass accuracy). Note: this profile is based on 457 minutes of playing time this season. The three most similar players to Ishaq Abdulrazak by playing style are:

  • Magnus Mattsson(83% match)A Creator. Statistically, he stands out as an elite creator (2.6 key passes/90), a regular goalscorer (0.39 goals/90), a reliable supplier (0.20 assists/90), meticulous in distribution (89% pass accuracy), creates high-quality scoring opportunities (0.59 big chances/90), heavily involved in play (65 touches/90), active off the ball (2.1 press score/90), contributing to defensive transitions and top 10% creator in the league. However, he loses possession under pressure (1.6 dispossessed/90).
  • Leon Avdullahu(81% match)A Metronome. Statistically, he stands out as active in the tackle (2.0 tackles/90), reads the game exceptionally (1.5 interceptions/90), meticulous in distribution (88% pass accuracy), heavily involved in possession (66 passes/90), wins the ball cleanly (1.9 successful tackles/90), central to possession (77 touches/90), uses long balls frequently (5.4/90) and a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up. Note: this profile is based on 529 minutes of playing time this season.
  • Dani Silva(82% match)Silva is a metronomic safety valve operating within a Tier C environment, maintaining a staggering 100% pass completion rate that places him in the elite 5th percentile of Superliga midfielders. While his 48.2 passes per 90 suggest a high-volume facilitator, the data reveals a player who prioritizes ball retention over risk, evidenced by a pedestrian 0.64 key passes per 90. The counterintuitive insight lies in his defensive profile: despite being flagged for poor aerial duel success rates, his 1.49 aerials won per 90 ranks in the top 20%, suggesting he possesses an uncanny knack for positioning and timing even if he lacks raw physical dominance.

Transfer Intelligence

Magnus Mattsson delivers 83% of the same playing style, at a 42% premium over Ishaq Abdulrazak, with 2.56 key passes per 90 at age 27.

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

I
Comparison Base
Ishaq Abdulrazak
MidfielderNigeria€3.0M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
M
Magnus Mattsson
FC København · Superliga
Denmark27yContract 2028
KP/902.56
G/900.39
CreatorCreative
vs Abdulrazak: 3y older
83% match
€4.3M
#2
L
Leon Avdullahu
TSG Hoffenheim · Bundesliga
Switzerland22yContract 2029
KP/901.02
G/900.00
MetronomeSmall Sample
Last 5: ↑ Hot
vs Abdulrazak: €14M more expensive · 2y younger
81% match
€17.0M
#3
D
Dani Silva
FC Midtjylland · Superliga
Portugal26yContract 2029
KP/901.19
G/900.00
Balanced MidfielderSmall Sample
vs Abdulrazak: 2y older
82% match
€3.5M
#4
J
Jesper Karlström
Udinese · Serie A
Sweden30yContract 2026
KP/900.45
G/900.06
Box-to-Box
81% match
€4.0M
#5
N
Noah Sadiki
Sunderland · Premier League
Belgium21yContract 2030
KP/900.56
G/900.00
Balanced Midfielder
Last 5: ↑ Hot
81% match
€30.0M
#6
R
Ramiz Zerrouki
FC Twente · Eredivisie
Algeria27y
KP/901.56
G/900.11
MetronomeCreative
Last 5: ↑ Hot
81% match
€7.2M
#7
M
Mikael Egill Ellertsson
Genoa · Serie A
Iceland24yContract 2029
KP/900.40
G/900.00
Balanced Midfielder
Last 5: ↓ Dip
81% match
€3.5M
#8
L
Love Arrhov
Eintracht Frankfurt · Bundesliga
Sweden17yContract 2028
KP/901.50
G/900.07
Creator
81% match
€5.0M
#9
O
Oussama Targhalline
Feyenoord · Eredivisie
Morocco23yContract 2028
KP/900.94
G/900.10
Ball-WinnerDefensive
Last 5: ↑ Hot
80% match
€8.0M
#10
S
Sam Larsson
Fatih Karagümrük · Super Lig
Sweden33y
KP/902.11
G/900.06
CreatorCreative
Last 5: → Stable
81% match
€5.0M
#11
A
Antoni Milambo
Brentford · Premier League
Netherlands21yContract 2030
KP/901.22
G/900.14
Creator
80% match
€20.0M
#12
D
Denis Huseinbasic
FC Köln · Bundesliga
Germany24yContract 2027
KP/900.79
G/900.00
Balanced MidfielderSmall Sample
81% match
€3.0M

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 Ishaq Abdulrazak.

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Frequently Asked Questions

Who are the best alternatives to Ishaq Abdulrazak?
The top alternatives to Ishaq Abdulrazak based on AI DNA playing style analysis include: Magnus Mattsson, Leon Avdullahu, Dani Silva, Jesper Karlström, Noah Sadiki. 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 Ishaq Abdulrazak in 2026?
Players with a similar profile to Ishaq Abdulrazak in 2026 include Magnus Mattsson (€4.3M), Leon Avdullahu (€17.0M), Dani Silva (€3.5M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Ishaq Abdulrazak play and who plays similarly?
Ishaq Abdulrazak plays as a Midfielder. Players with a comparable positional profile include Magnus Mattsson (Denmark, €4.3M); Leon Avdullahu (Switzerland, €17.0M); Dani Silva (Portugal, €3.5M); Jesper Karlström (Sweden, €4.0M).
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.