AI DNA Similarity
Best Alternatives to Michael Laffey
Players most similar to Michael Laffey (Midfielder, N/A) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.
Top 3 Alternatives to Michael Laffey
- 1.M. Rasmussen98% DNA match·HB Køge
- 2.Ivan Franjic98% DNA match·Wehen Wiesbaden
- 3.Frederik Brinch Møller96% DNA match·Kolding IF
Ranked by AI DNA similarity — 768 dimensions across playing style, pressing intensity, and tactical fit.
RT
Intelligence Verdict
???Bottom 0%
“A Midfielder....”
See Full Verdict + Share Card →Playing Style Analysis
Small Sample
A Midfielder. Note: this profile is based on 562 minutes of playing time this season. The three most similar players to Michael Laffey by playing style are:
- M. Rasmussen(98% match) — A Midfielder. Note: this profile is based on 882 minutes of playing time this season.
- Ivan Franjic(98% match) — A Midfielder. Note: this profile is based on 540 minutes of playing time this season.
- Frederik Brinch Møller(96% match) — A Balanced Midfielder. Note: this profile is based on 629 minutes of playing time this season.
Similarity is calculated using per-90 performance data across multiple playing style dimensions. How Player DNA matching works →
Similar Players — Ranked by DNA Similarity
#1
M
M. Rasmussen
HB Køge · Superliga
Denmark20y
KP/900.71
G/900.00
Small Sample
98% match
N/A
#2
I
Ivan Franjic
Wehen Wiesbaden · Bundesliga
Germany28y
KP/900.00
G/900.00
Small Sample
vs Laffey: 8y older
98% match
N/A
#3
F
Frederik Brinch Møller
Kolding IF · Superliga
Denmark20y
KP/900.64
G/900.14
Balanced MidfielderSmall Sample
Last 5: → Stable96% match
N/A
#4
L
Loret Sadiku
Kasımpaşa · Super Lig
34y
KP/900.39
G/900.00
Balanced MidfielderSmall Sample
95% match
N/A
#5
G
George Lawrence Hemmings
Aston Villa · Premier League
England19y
KP/900.80
G/900.00
Balanced MidfielderSmall Sample
95% match
N/A
#6
H
Hjalte Toftegaard
Hillerød · Superliga
Denmark19y
KP/903.52
G/900.00
Small Sample
95% match
N/A
#7
M
Marcel Wenig
Ulm · Bundesliga
Germany22yContract 2027
KP/900.00
G/900.17
Small Sample
95% match
N/A
#8
M
Mitchel Van Rosmalen
Blauw Geel '38 · Eredivisie
Netherlands24y
KP/900.72
G/900.00
Small Sample
94% match
N/A
#9
D
Diogo Ferreira Prioste
Benfica · Liga Portugal
Portugal22y
KP/901.18
G/900.00
Small Sample
94% match
N/A
#10
T
Tiago Freitas
Benfica · Liga Portugal
Portugal19y
KP/900.00
G/900.38
Small Sample
93% match
N/A
#11
B
B. Kücükylidiz
Hillerød · Superliga
Denmark25y
KP/900.00
G/900.00
Small Sample
93% match
N/A
#12
Y
Yassin Oukili
Fortuna Sittard · Liga Portugal
Morocco25y
KP/900.20
G/900.00
Balanced MidfielderSmall Sample
Last 5: ↓ Dip93% match
N/A
⬡
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 Michael Laffey.
Ask AI about Michael Laffey →Frequently Asked Questions
Who are the best alternatives to Michael Laffey?▼
The top alternatives to Michael Laffey based on AI DNA playing style analysis include: M. Rasmussen, Ivan Franjic, Frederik Brinch Møller, Loret Sadiku, George Lawrence Hemmings. 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 Michael Laffey in 2026?▼
Players with a similar profile to Michael Laffey in 2026 include M. Rasmussen (N/A), Ivan Franjic (N/A), Frederik Brinch Møller (N/A). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Michael Laffey play and who plays similarly?▼
Michael Laffey plays as a Midfielder. Players with a comparable positional profile include M. Rasmussen (Denmark, N/A); Ivan Franjic (Germany, N/A); Frederik Brinch Møller (Denmark, N/A); Loret Sadiku (, N/A).
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.