RisingTransfers
AI DNA Similarity

Best Alternatives to Patrick Bamford

Players most similar to Patrick Bamford (Attacker, €1.2M) — ranked by AI DNA similarity score across playing style, pressing intensity, and tactical fit.

Top 3 Alternatives to Patrick Bamford

  1. 1.Chris Wood 85% DNA match·Nottingham Forest€8.0M
  2. 2.Erling Haaland82% DNA match·Manchester City€200.0M
  3. 3.Raúl Jiménez82% DNA match·Fulham€4.0M

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

RT

Intelligence Verdict

GoalsTop 5%
???Bottom 17%

Bamford remains the Championship’s most sophisticated enigma...

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Playing Style Analysis

Complete ForwardProlificSmall Sample

Bamford remains the Championship’s most sophisticated enigma, a striker who functions less like a traditional target man and more like a predatory ghost haunting the penalty area. His output is undeniable: a staggering 0.73 goals per 90 puts him in the top 5% of the league, fueled by a relentless volume of 3.18 shots per 90. While his 65.2% pass accuracy suggests technical mediocrity, the counterintuitive reality is that Bamford isn't a link-man; he is a defensive disruptor. The three most similar players to Patrick Bamford by playing style are:

  • Chris Wood (85% match)A Target Man. Statistically, he stands out as a regular goalscorer (0.35 goals/90). Note: this profile is based on 775 minutes of playing time this season.
  • Erling Haaland(82% match)Haaland exists in a category so singular that comparing him to other forwards almost feels like a category error. His 0.82 goals per 90 places him firmly in the top 5% of Premier League attackers—not through accumulation, but through ruthless, repeatable execution. The counterintuitive read on his passing numbers tells the real story: rock-bottom passing volume and below-average accuracy aren't symptoms of a limited footballer, they're evidence of extreme positional discipline—he conserves touches precisely because he's always positioning for the kill.
  • Raúl Jiménez(82% match)A Target Man. Statistically, he stands out as a capable chance creator (1.0 key passes/90), a constant goal threat (3.0 shots/90), a regular goalscorer (0.38 goals/90) and strong in aerial duels (3.5 aerials won/90).

Transfer Intelligence

Chris Wood  delivers 85% of the same playing style, at a 567% premium over Patrick Bamford, with 0.35 goals per 90 at age 34. That's 59% of Patrick Bamford's output in goals per 90 — a credible like-for-like option.

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

P
Comparison Base
Patrick Bamford
AttackerEngland€1.2M
Full profile →

Similar Players — Ranked by DNA Similarity

#1
C
Chris Wood 
Nottingham Forest · Premier League
New Zealand34yContract 2027
G/900.35
A/900.00
Target ManSmall Sample
Last 5: ↑ Hot
vs Bamford: €7M more expensive · 2y older · -0.24 G/90
85% match
€8.0M
#2
E
Erling Haaland
Manchester City · Premier League
Norway25yContract 2034
G/900.81
A/900.25
PoacherProlific
Last 5: → Stable
vs Bamford: €199M more expensive · 7y younger · +0.22 G/90
82% match
€200.0M
#3
R
Raúl Jiménez
Fulham · Premier League
Mexico35yContract 2026
G/900.38
A/900.13
Target Man
Last 5: ↓ Dip
vs Bamford: 3y older · -0.22 G/90
82% match
€4.0M
#4
V
Viktor Gyökeres
Arsenal · Premier League
Sweden27yContract 2030
G/900.57
A/900.04
PoacherProlific
Last 5: → Stable
83% match
€65.0M
#5
E
Enes Ünal
AFC Bournemouth · Premier League
Turkey29yContract 2028
G/900.46
A/900.00
Target ManProlific
Last 5: ↓ Dip
83% match
€8.0M
#6
P
Pablo
West Ham United · Premier League
Portugal22yContract 2030
G/900.94
A/900.09
Complete ForwardProlific
Last 5: ↓ Dip
82% match
€5.0M
#7
J
Jean-Philippe Mateta
Crystal Palace · Premier League
France28yContract 2027
G/900.47
A/900.00
Target ManProlific
Last 5: → Stable
82% match
€40.0M
#8
Y
Youssef Chermiti
Rangers · Premier League
Portugal21yContract 2029
G/900.67
A/900.22
Complete ForwardProlific
Last 5: → Stable
82% match
€9.0M
#9
D
Dominic Calvert-Lewin
Leeds United · Premier League
England29yContract 2028
G/900.46
A/900.04
Target ManProlific
Last 5: ↑ Hot
81% match
€22.0M
#10
G
Georginio Rutter
Brighton & Hove Albion · Premier League
France24yContract 2028
G/900.15
A/900.21
Complete Forward
Last 5: ↑ Hot
81% match
€32.0M
#11
Z
Zian Flemming
Burnley · Premier League
Netherlands27yContract 2029
G/900.56
A/900.06
Target ManProlific
Last 5: → Stable
82% match
€12.0M
#12
L
Lukas Nmecha
Leeds United · Premier League
Germany27yContract 2027
G/900.57
A/900.09
Target ManProlific
Last 5: ↓ Dip
82% match
€10.0M

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 Patrick Bamford.

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Frequently Asked Questions

Who are the best alternatives to Patrick Bamford?
The top alternatives to Patrick Bamford based on AI DNA playing style analysis include: Chris Wood , Erling Haaland, Raúl Jiménez, Viktor Gyökeres, Enes Ünal. 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 Patrick Bamford in 2026?
Players with a similar profile to Patrick Bamford in 2026 include Chris Wood  (€8.0M), Erling Haaland (€200.0M), Raúl Jiménez (€4.0M). For a deeper DNA-level comparison including playing style, physical attributes, and tactical fit, ask Rising Transfers' AI directly.
What position does Patrick Bamford play and who plays similarly?
Patrick Bamford plays as a Attacker. Players with a comparable positional profile include Chris Wood  (New Zealand, €8.0M); Erling Haaland (Norway, €200.0M); Raúl Jiménez (Mexico, €4.0M); Viktor Gyökeres (Sweden, €65.0M).
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.