RisingTransfers
AI DNA Similarity

Best Alternatives to Henrikh Mkhitaryan

Players most similar to Henrikh Mkhitaryan (Midfielder, €3.5M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Henrikh Mkhitaryan

  1. 1.Manuel Locatelli82% DNA match·Juventus€25.0M
  2. 2.Bryan Cristante82% DNA match·Roma€7.0M
  3. 3.Mario Götze83% DNA match·Eintracht Frankfurt€3.5M

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

RT

Intelligence Verdict

Press IntensityTop 2%
???Bottom 0%

A Metronome....

See Full Verdict + Share Card →

Playing Style Analysis

MetronomeSmall Sample

A Metronome. Statistically, he stands out as comfortable with both feet, a constant goal threat (3.2 shots/90), a regular goalscorer (0.24 goals/90), active in the tackle (2.1 tackles/90), central to possession (77 touches/90) and a high-intensity presser (press score 3.5/90), constantly disrupting opposition build-up. Note: this profile is based on 737 minutes of playing time this season. The three most similar players to Henrikh Mkhitaryan by playing style are:

  • Manuel Locatelli(82% match)Locatelli has spent years being the midfielder that makes everything work without ever making the highlight reel—and the numbers finally prove why that matters. Operating in Serie A's congested midfield battles, he ranks in the top 5% for passes per 90, tackles won, press intensity, and passes into the final third simultaneously; finding a player who dominates all four categories at once is genuinely rare. The counterintuitive read here is his goal contribution figures, which look pedestrian until you understand he's essentially the engine redistributing possession upward—those 15-plus progressive passes per 90 are what create the chances others finish.
  • Bryan Cristante(82% match)Cristante has quietly become one of Serie A's most underrated distribution engines — a midfielder who doesn't dazzle but consistently moves teams forward with purpose. His passes into the final third rank in the top 5% of the league, which tells the real story: this isn't a recycler, it's a progressor. The counterintuitive read on his average key pass numbers is that Cristante is threading balls *into* dangerous areas, not completing the final action himself — he's the architect before the architect.
  • Mario Götze(83% match)A Creator. Statistically, he stands out as a capable chance creator (1.1 key passes/90), heavily involved in play (68 touches/90) and active off the ball (2.6 press score/90), contributing to defensive transitions. However, he loses possession under pressure (1.9 dispossessed/90).

Transfer Intelligence

Manuel Locatelli delivers 82% of the same playing style, at a 614% premium over Henrikh Mkhitaryan, with 1.88 key passes per 90 at age 28.

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

H
Comparison Base
Henrikh Mkhitaryan
MidfielderArmenia€3.5M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
M
Manuel Locatelli
Juventus · Serie A
Italy28yContract 2028
KP/901.88
G/900.00
MetronomeDefensive
Last 5: ↓ Dip
vs Mkhitaryan: €22M more expensive · 9y younger
82% match
€25.0M
#2
B
Bryan Cristante
Roma · Serie A
Italy31yContract 2027
KP/900.88
G/900.05
Metronome
Last 5: ↓ Dip
vs Mkhitaryan: 6y younger
82% match
€7.0M
#3
M
Mario Götze
Eintracht Frankfurt · Bundesliga
Germany33yContract 2026
KP/900.43
G/900.00
CreatorSmall Sample
vs Mkhitaryan: 4y younger
83% match
€3.5M
#4
L
Luka Modrić
AC Milan · Serie A
Croatia40yContract 2026
KP/901.48
G/900.00
MetronomeSmall Sample
Last 5: → Stable
81% match
€4.0M
#5
G
Granit Xhaka
Sunderland · Premier League
Switzerland33yContract 2028
KP/901.13
G/900.03
Metronome
Last 5: → Stable
81% match
€10.0M
#6
P
Paul Pogba
Monaco · Ligue 1
France33yContract 2027
KP/901.60
G/900.07
CreatorCreative
81% match
€5.0M
#7
W
Weston McKennie
Juventus · Serie A
United States27yContract 2026
KP/901.59
G/900.28
Creator
Last 5: → Stable
81% match
€22.0M
#8
S
Stanislav Lobotka
Napoli · Serie A
Slovakia31yContract 2027
KP/900.54
G/900.06
Last 5: ↓ Dip
81% match
€18.0M
#9
Y
Yegor Yarmolyuk
Brentford · Premier League
Ukraine22yContract 2031
KP/900.56
G/900.04
Box-to-Box
Last 5: ↓ Dip
80% match
€25.0M
#10
N
Nikola Vlašić
Torino · Serie A
Croatia28yContract 2027
KP/901.59
G/900.20
CreatorCreative
Last 5: → Stable
80% match
€9.0M
#11
M
Marten de Roon
Atalanta · Serie A
Netherlands35yContract 2026
KP/900.81
G/900.05
Chance Creator
Last 5: ↓ Dip
81% match
€3.5M
#12
D
Danilo Cataldi
Lazio · Serie A
Italy31yContract 2027
KP/901.06
G/900.14
Ball-Winner
80% match
€3.5M

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 Henrikh Mkhitaryan.

Ask AI about Henrikh Mkhitaryan

Frequently Asked Questions

Who are the best alternatives to Henrikh Mkhitaryan?
The top alternatives to Henrikh Mkhitaryan based on AI DNA playing style analysis include: Manuel Locatelli, Bryan Cristante, Mario Götze, Luka Modrić, Granit Xhaka. 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 Henrikh Mkhitaryan in 2026?
Players with a similar profile to Henrikh Mkhitaryan in 2026 include Manuel Locatelli (€25.0M), Bryan Cristante (€7.0M), Mario Götze (€3.5M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Henrikh Mkhitaryan play and who plays similarly?
Henrikh Mkhitaryan plays as a Midfielder. Players with a comparable positional profile include Manuel Locatelli (Italy, €25.0M); Bryan Cristante (Italy, €7.0M); Mario Götze (Germany, €3.5M); Luka Modrić (Croatia, €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.