Thin sample this season. Lorenzo Colombo has played 6 matches (365 min) so far, so sections that need a bigger sample to say anything reliable are not shown here — they are missing on purpose, not broken. See all seasons combined →
01
What Patterns Define Him?
His repeatable signature. A step only appears if its reliability score (sample size × match coverage) reaches at least Medium confidence — pattern mining, not anecdotes.
Signature: Link → Finish — the only steps proven repeatable this season (2 of 4 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: receive / move — 0× (insufficient confidence, hidden — not enough evidence yet); convert — 0× (insufficient confidence, hidden — not enough evidence yet) — omitted from the signature rather than presented as one.
In possession
In possession
What he does with the ball: build-up, progression, creation, carrying and finishing.
16 tracked carries (3.9/90, 4 progressive, 136m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). this counts every touch-carry, not just his dribble attempts below — a fuller picture of how much of his ball-carrying is control-and-move rather than beating a man.
progressivelateral/short% of his 16 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 24m
By zone — where the carry started → where it ended
First (16)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Dribbles (1v1s)
Only 7 dribbles attempted this season — too little volume to map a location pattern.
02
How does he create chances?
6 key passes (1.48/90), 0 of them assists — where his chance creation specifically comes from, 18 zones (6×3), showing his share of key passes originating there.
Chance creation — key pass origin zone share
Filter:
chance creation (6)assist (0)% of the selected group's key passes originating in each zone
Box deliveries — key passes reaching the final third, by flank
from the left (2)from the right (4)of 6 key passes landing in the final thirdattacking ↑ toward goal
04
Where does he become vulnerable?
28 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.
15
attacking third (cheap)
12
middle third
1
own third (dangerous)
Vision AI 54% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 1.53 danger-index/90 · 0.222 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
03
Tactical patterns — how his football actually looks
Three clustered sequence diagrams from his own event data — his three busiest routes: the way he progresses, the pattern behind his chances, and where a turnover turns dangerous.
own goal left, attacking →
Where do his chances come from?
Of 6 key passes, his busiest route is a delivery where he switches from the right hs to the left hs, advancing it forward in the middle third — 1 times. The receiver isn't identifiable in this data, only where the pass started and ended.
Where does he lose the ball most?
This is a RATE, not a raw count — the share of his touches in each zone that end in a turnover, so a zone he simply plays in more often doesn't automatically look riskier. His weakest zone is the left half-space in the final third: 75% of his 8 touches there are lost (6 times).
58 defensive actions across the season (14.3/90). Where he wins the ball, and how — the core question for a defender. Aerial duels are not recorded for this competition, so aerial dominance is not measured here.
click a card to isolate that action type · own goal left, attacking →
3
tackles · 33% won
2
interceptions · 0.5/90
5
recoveries · 1.2/90
3
clearances · 0.7/90
1
blocks
55
avg action height
14
won high (att 3rd)
37
middle third
7
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 10 proactive ball-wins (2.5/90), tackle success 33%. He defends high, stepping out to intercept — suits a high line.
Defensive work in the attacking half
Ball-wins in the attacking half only (own half vs. attacking half, a simple 2-way split, not the usual thirds) — the clearest single signal of how much he presses and recovers the ball high up the pitch.
35
attacking-half actions · 8.63/90
06
Against Different Pressing Intensities
Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Lorenzo Colombo keep producing when the game is tight and the press is high? Tiers of ~2-2 matches — directional evidence, not proof.
press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 4.0, 2m)
0.48
1.9
1.86
50%
Mid press (PPDA 5.8, 2m)
0.15
1.7
0.84
25%
Low press (PPDA 6.8, 2m)
0.42
1.7
1.68
0%
Team
Team context
How much of the team runs through him, and what changes without him.
Genoa's output per match with Lorenzo Colombo (6 matches) versus without him (2 matches). Insufficient evidence — the without-sample is only 2 matches; treat every Δ below as noise until more games exist. A proper on-off model needs many more minutes.
WITH (6)
WITHOUT (2)
Δ
goals for /match
0.67
1.00
-0.33
xG for /match
0.85
0.00
+0.85
goals against /match
1.67
1.50
+0.17
points /match
0.67
1.50
-0.83
09
His Share of the Team
Of everything Genoa produced this season, the categories where the biggest share ran through Lorenzo Colombo specifically — his share of the team total, not a per-90 rate.
category
share
him / team
expected goals (xG)
22%
9.2 / 40.9
shots
16%
72 / 440
successful take-ons
8%
21 / 252
Recruitment
Style and verdict
Style profile, closest comparables, and the summary.
Not raw event counts — football style scores: weighted models scored 0–100 against the 299 strikers in the pool (min 450 min). This is what separates players who post similar numbers but play differently. Proxy dimensions are inferred from on-ball data; true off-ball running / under-pressure context is not measured.
Why Pressing forward 65%: a weighted blend of defensive aggression 67 (weight 45%) + ball-winning 52 (weight 30%) + transition 55 (weight 25%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
aerial ability, marking, off-ball running — not in event data
Territory (wide vs central)
75
Defensive aggression
67
Carrying
64
Line-breaking
63
Through-balls ~proxy
63
Progression
61
Passing directness
59
Transition ~proxy
55
Build-up
54
Box threat
54
Ball-winning
52
Final-third threat
48
Dribbling
47
Receiving zones
42
Creativity
40
Press resistance ~proxy
40
Crossing
34
Retention
27
11
Similar Players — in style space
Closest comparables measured on the style scores above, within the same position family — so it separates how players are alike, not just how much they touch the ball. Each line explains the shared strength and the divergent mechanism. A light physical-profile term (height / weight; this player: 186 cm / 74 kg) is included at a quarter of one style axis's weight — enough to break ties between stylistic twins, not to override style.Scope: pooled across the Serie A, Bundesliga, La Liga, Ligue 1 and Premier League, percentiled within each player's own league before comparing — a match from another league is marked with its league name.
Style, not quality:a high match here means two players tend to produce the ball in similar ways — it is not a ranking, a scouting recommendation, or a claim that they are equally good.
Adrián Liso Getafe · La Liga 25/26 · 182 cm / 70 kg
66%
Driven by: retention (20%), defensive aggression (17%), territory (wide vs central) (17%). Different mechanism — Colombo more via box threat, build-up; Liso more via territory (wide vs central), ball-winning.
Toni Martínez Alaves · La Liga · 187 cm / 83 kg
62%
Driven by: retention (27%), defensive aggression (23%), territory (wide vs central) (19%). Different mechanism — Colombo more via carrying, through-balls; Martínez more via passing directness.
Patrick Cutrone Monza · 183 cm / 75 kg
60%
Driven by: territory (wide vs central) (23%), retention (23%), through-balls (8%). Different mechanism — Colombo more via build-up, defensive aggression; Cutrone more via transition, passing directness.
Lukas Nmecha Leeds · Premier League · 185 cm / 80 kg
57%
Driven by: retention (24%), defensive aggression (19%), crossing (15%). Different mechanism — Colombo more via line-breaking, build-up; Nmecha more via box threat, creativity.
Christantus Uche Crystal Palace · La Liga 25/26 · 190 cm / 84 kg
57%
Driven by: retention (23%), crossing (17%), territory (wide vs central) (16%). Different mechanism — Colombo more via through-balls, build-up; Uche more via passing directness.
Isaac Romero Sevilla · La Liga · 184 cm / 70 kg
56%
Driven by: territory (wide vs central) (19%), press resistance (13%), retention (11%). Different mechanism — Colombo more via box threat; Romero more via ball-winning, creativity.
12
Summary
Lorenzo Colombo is a pressing forward / transition runner: 0 goals from 1.06 xG (-1.06 vs expected), 6 shots, 0 box entries. Under-performing his chances. [Off-ball runs, aerials and hold-up under contact need tracking/aerial data.]
Based on 6 matches (365 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a pressing forward / transition runner — best used in a system built around that identity.
His biggest room for growth is ball-winning — even a modest improvement there would meaningfully lift his overall pressing forward profile.
✨ This report is interactive
Click any stat card to filter its map, hover a dot for the exact match, and use the dropdowns to slice passes zone-to-zone. Nothing here is static.