RisingTransfers
AI DNA Similarity

Best Alternatives to James Abankwah

Players most similar to James Abankwah (Defender, €1.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to James Abankwah

  1. 1.Malick Thiaw85% DNA match·Newcastle United€45.0M
  2. 2.Kevin Danso86% DNA match·Tottenham Hotspur€22.0M
  3. 3.Dan Ballard85% DNA match·Sunderland€20.0M

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

RT

Intelligence Verdict

Chances MissedTop 0%

A Physical Stopper....

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Playing Style Analysis

Physical StopperAerial

A Physical Stopper. Statistically, he stands out as commanding in the air (5.4 clearances/90), wins the physical battle (60% duel success) and uses long balls frequently (5.9/90). The three most similar players to James Abankwah by playing style are:

  • Malick Thiaw(85% match)Thiaw has quietly become one of the Premier League's most complete defensive profiles — a towering centre-back who doesn't just win his battles, he wins them cleanly. His aerial win rate of 65.1% and duel success of 64.2% both sit in the league's top 20%, but the counterintuitive story is his attacking output: 0.16 goals per 90 and 0.98 shots per 90 place him in the top 10% among defenders, suggesting a genuine threat from set-pieces that opponents routinely underestimate. His pass accuracy of 90.6% reflects a ball-player comfortable in possession-heavy systems, and his above-average delivery into the final third adds genuine build-up value.
  • Kevin Danso(86% match)A Ball-Playing CB. Statistically, he stands out as active in the tackle (1.9 tackles/90), commanding in the air (8.3 clearances/90), meticulous in distribution (86% pass accuracy), wins the physical battle (62% duel success), central to possession (78 touches/90), dominant in the air (4.8 aerials won/90, 63%) and uses long balls frequently (6.0/90).
  • Dan Ballard(85% match)A Ball-Playing CB. Statistically, he stands out as commanding in the air (7.8 clearances/90), wins the physical battle (59% duel success), strong in aerial duels (4.4 aerials won/90) and uses long balls frequently (6.6/90).

Transfer Intelligence

Malick Thiaw delivers 85% of the same playing style, at a 2900% premium over James Abankwah, with 1.29 tackles won per 90 at age 24.

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

J
Comparison Base
James Abankwah
DefenderRepublic of Ireland€1.5M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
M
Malick Thiaw
Newcastle United · Premier League
Germany24yContract 2029
Tkl/901.29
KP/900.19
Ball-Playing CBAerial
Last 5: ↑ Hot
vs Abankwah: €44M more expensive · 2y older
85% match
€45.0M
#2
K
Kevin Danso
Tottenham Hotspur · Premier League
Austria27yContract 2030
Tkl/901.84
KP/900.20
Ball-Playing CBBall-Playing
Last 5: → Stable
vs Abankwah: €21M more expensive · 5y older
86% match
€22.0M
#3
D
Dan Ballard
Sunderland · Premier League
Northern Ireland26yContract 2028
Tkl/901.38
KP/900.67
Ball-Playing CBAerial
Last 5: → Stable
vs Abankwah: €19M more expensive · 4y older
85% match
€20.0M
#4
J
Jake O'Brien
Everton · Premier League
Republic of Ireland24yContract 2028
Tkl/901.66
KP/900.48
Aerial
Last 5: → Stable
84% match
€16.0M
#5
S
Sepp van den Berg
Brentford · Premier League
Netherlands24yContract 2029
Tkl/900.64
KP/900.20
Ball-Playing CBAerial
Last 5: → Stable
84% match
€28.0M
#6
J
Joe Worrall
Burnley · Premier League
England29yContract 2028
Tkl/900.73
KP/900.18
Physical StopperAerial
Last 5: → Stable
84% match
€4.0M
#7
K
Kojo Peprah Oppong
Nice · Ligue 1
Ghana21yContract 2029
Tkl/902.21
KP/900.23
Ball-Playing CBAerial
Last 5: → Stable
84% match
€4.0M
#8
M
Marc Guéhi
Manchester City · Premier League
England25yContract 2026
Tkl/901.55
KP/900.45
Ball-Playing CBAerial
Last 5: → Stable
84% match
€65.0M
#9
J
Josh Acheampong
Chelsea · Premier League
England20yContract 2029
Tkl/901.54
KP/900.31
Active Full-BackBall-Playing
Last 5: ↑ Hot
84% match
€20.0M
#10
S
Samson Baidoo
Lens · Ligue 1
Austria22yContract 2030
Tkl/901.98
KP/900.28
Ball-Playing CBAerial
Last 5: → Stable
83% match
€12.0M
#11
B
Bafodé Diakité
AFC Bournemouth · Premier League
France25y
Tkl/901.41
KP/900.21
Ball-Playing CBAerial
83% match
€30.0M
#12
J
James Hill
AFC Bournemouth · Premier League
England24yContract 2026
Tkl/901.77
KP/900.61
Physical StopperAerial
Last 5: → Stable
84% match
€15.0M

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 James Abankwah.

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Frequently Asked Questions

Who are the best alternatives to James Abankwah?
The top alternatives to James Abankwah based on AI DNA playing style analysis include: Malick Thiaw, Kevin Danso, Dan Ballard, Jake O'Brien, Sepp van den Berg. 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 James Abankwah in 2026?
Players with a similar profile to James Abankwah in 2026 include Malick Thiaw (€45.0M), Kevin Danso (€22.0M), Dan Ballard (€20.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does James Abankwah play and who plays similarly?
James Abankwah plays as a Defender. Players with a comparable positional profile include Malick Thiaw (Germany, €45.0M); Kevin Danso (Austria, €22.0M); Dan Ballard (Northern Ireland, €20.0M); Jake O'Brien (Republic of Ireland, €16.0M).
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.