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Player reportPremier League 2026

Roméo Lavia

Chelsea
Ball-winning 6 (destroyer) DM
17.1 defensive actions/90
defensive midtempo controllerpress resistancescreening
295
minutes
6 apps
122
passes
87% completed
87%
pass completion
122 passes
7
progressive passes
2.1/90
56
defensive actions
17.1/90
16
tackles + interceptions
50% tackle win
18
recoveries
5.5/90
4
line-breaking passes
1.2/90
Overview

The player

Who he is and how he compares with his peers.

Thin sample this season. Roméo Lavia has played 6 matches (295 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.

RECEIVE
drop between the centre-backs — mostly in the middle third (71% of his 122 passes)
87% completion · 122× in 6/6 matches
↓
ESCAPE PRESSURE
turn out of a tight central area
50% won · 4× in 4/6 matches
↓
PROGRESS CENTRAL
break a line through the middle
2.1 prog/90 · 4× in 4/6 matches
↓
SCREEN / WIN BALL
protect the back four
10.4 ball-wins/90 · 34× in 6/6 matches
↓
RECYCLE / PROGRESS
keep it ticking, feed the final third
2.1 f3-entries/90 · 7× in 4/6 matches
Signature: drop to receive → escape the press on the turn → progress centrally or recycle → screen the counter. Block the central lane and press his first touch to force him backwards.
13

Where is he influential — vs where is he merely present?

Red fill = raw touch territory. Gold rings = zones where his influence (xT added, progression, line-breaks, key passes) outweighs how often he's actually there — one combined map instead of two separate maps to compare by eye. Red with no ring: present but not dangerous. A ring on faint red: rare touches, outsized impact.

own goal left, attacking →
20
passes / match
17.1
def actions / 90
4–43
pass range (matches)
4
clearances
Pass range = his fewest and most passes in any single match this season (4 at the low end, 43 at the high) — a measure of match-to-match involvement, not pass distance.
In possession

In possession

What he does with the ball: build-up, progression, creation, carrying and finishing.

07

How dangerous are his carries?

Real ball-carries

25 tracked carries (7.6/90, 3 progressive, 216m total) — the ball moving with his touches, a different signal from dribbles below (beating an opponent 1v1). even a player who rarely dribbles past a man can still carry the ball forward constantly in build-up; this is that.

4%8%8%16%24%12%8%16%4%
progressivelateral/short% of his 25 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 6m, longest 38m
By zone — where the carry started → where it ended
1Outside → Inside
23Inside → Inside
1Outside → Outside
First (20)Second (5)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Beaten in the tackle

How often an attacker gets past him in a 1v1 defensive duel — the closest signal the data has to "dribbled past" (no attacker-beat-defender field exists directly, so this counts tackles he attempted and lost).

8
tackle duels
4
won
4
beaten · 50%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 88%
OUTSIDE 12%
Tackle-duel location — 7 inside · 1 outside
Right Wing
0 · 0%
Right Half-Space
1 · 12%
Central
3 · 38%
Left Half-Space
3 · 38%
Left Wing
1 · 12%
Vision AI beaten in 4 of 8 tackle duels (50% loss rate) — a real defensive leak worth flagging.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

He attempted only 4 dribbles of his own all season — dribbling is not part of this role; his ball-carrying is covered above, his defending against the dribble below.

04

How does he create chances?

2 key passes (0.61/90), 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:
50%50%
chance creation (2)assist (0)% of the selected group's key passes originating in each zone
03

Where does he become vulnerable?

18 times he gave the ball away. For a defender the danger is where — a loss in his own third can turn into a chance against; higher up it costs little.

1
attacking third (cheap)
15
middle third
2
own third (dangerous)
Vision AI 6% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 1.99 danger-index/90 · 0.362 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
05

Where Does He Receive?

The zones where Roméo Lavia gets on the ball — his top three ball-collection areas highlighted (gold = primary). Reception is proxied by where his on-ball actions begin (no explicit receiver is recorded).

123
1 = primary, 2 = secondary, 3 = third · own goal left, attacking →
His collection zones
42%
Primary
Central, Middle third
13%
Secondary
Right Half-Space, Middle third
11%
Third
Left Half-Space, Middle third
These are the zones where he collected the ball most.
06

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Roméo Lavia actually gets on the ball. Hover any zone for its breakdown by action type, its share of all touches, and the exact coordinate range it covers.

Filter:
27751532318213492
own goal left, attacking → · brighter + higher number = more touches

Passes only — completed vs incomplete, by zone

Same zone grid, restricted to passes so completed/incomplete and match filters actually mean something — a shot or a dribble has no "completed" in the pass sense.

1%2%3%7%2%12%25%24%7%1%6%6%4%
own goal left, attacking →
08

Every Pass This Season — completed vs incomplete

Every pass this season, plotted individually — green = completed, grey (dashed) = incomplete, gold = key pass. Filter by outcome or isolate one match below.

2Key pass
7Progressive
4Long ball
1Switch
By zone — where the pass started → where it landed
5Outside → Inside
80Inside → Inside
2Outside → Outside
19Inside → Outside
By direction
51Forward
18Backward
53Sideways
own goal left, attacking →
02

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 →
How does he progress the ball forward?
His most common route for progressing play: he plays straight through the central in the final third — 1 passes worth 0.22 xT.
Where do his chances come from?
Of 2 key passes, his busiest route is a delivery where he switches from the left hs to the right hs 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 middle third: 29% of his 14 touches there are lost (4 times).
—0 touches · too few—5 touches · too few10%1/10 lost—5 touches · too few—0 touches · too few—0 touches · too few12%2/17 lost12%6/50 lost29%4/14 lost—6 touches · too few—0 touches · too few—3 touches · too few—7 touches · too few—3 touches · too few—2 touches · too fewRWRHSCLHSLWDEFMIDATT
Out of possession

Out of possession

Where and how he defends and presses.

10

How & where does he defend?

56 defensive actions across the season (17.1/90). 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 →
8
tackles · 50% won
8
interceptions · 2.4/90
18
recoveries · 5.5/90
4
clearances · 1.2/90
4
blocks
37
avg action height
4
won high (att 3rd)
30
middle third
22
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 34 proactive ball-wins (10.4/90), tackle success 50%. He defends mostly around the middle third.
09

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Roméo Lavia still play out when the opponent presses high? His build-up quality split by press intensity — the key question for a ball-playing defender. Tiers of ~2-2 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 3.5, 2m)
91%
0.7
0.7
0.33
Mid press (PPDA 4.7, 2m)
87%
3.6
2.4
0.76
Low press (PPDA 5.4, 2m)
83%
2.9
1.0
0.88
Team

Team context

How much of the team runs through him, and what changes without him.

11

Impact on the Team

Chelsea's output per match with Roméo Lavia (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. What his own defending should move — goals conceded and results — leads; attacking output (largely out of a defender's hands) is shown after, for context. A proper on-off model needs many more minutes.

WITH (6)
WITHOUT (2)
Δ
goals against /match
1.67
2.50
-0.83
points /match
2.17
0.00
+2.17
goals for /match
2.83
0.00
+2.83
xG for /match
1.35
0.65
+0.70
12

His Share of the Team

Of everything Chelsea produced this season, the categories where the biggest share ran through Roméo Lavia specifically — his share of the team total, not a per-90 rate.

category
share
him / team
goals
6%
1 / 17
interceptions
3%
13 / 481
expected assists (xA)
2%
0.8 / 38.6
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

14

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 258 defensive mids 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.

Tempo controller77%Deep-lying playmaker68%Ball-winning 644%
Why Tempo controller 77%: a weighted blend of retention 87 (weight 35%) + build-up 71 (weight 30%) + press resistance 73 (weight 20%) + progression 31 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
retention
Strong
press resistance, build-up, creativity
Average
box threat, dribbling, passing directness, receiving zones, crossing, ball-winning, carrying, transition, final-third threat
Weak
progression, defensive aggression, through-balls, line-breaking, territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Retention
87
Press resistance ~proxy
73
Build-up
71
Creativity
71
Box threat
65
Dribbling
65
Passing directness
63
Receiving zones
61
Crossing
54
Ball-winning
52
Carrying
51
Transition ~proxy
47
Final-third threat
46
Progression
31
Defensive aggression
31
Through-balls ~proxy
18
Line-breaking
16
Territory (wide vs central)
4
15

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: 181 cm / 76 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 Premier League, Bundesliga, La Liga, Ligue 1 and Serie A, 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.

Axel Witsel Nice · Ligue 1 · 186 cm / 82 kg
70%
Driven by: retention (26%), through-balls (13%), build-up (13%). Different mechanism — Lavia more via dribbling, creativity; Witsel more via territory (wide vs central), transition.
Harry Winks Cagliari · Serie A · 178 cm / 65 kg
66%
Driven by: territory (wide vs central) (18%), retention (18%), build-up (13%). Different mechanism — Lavia more via creativity, box threat; Winks more via build-up.
Alberto Grassi Cremonese · Serie A 25/26 · 183 cm / 75 kg
64%
Driven by: territory (wide vs central) (20%), defensive aggression (18%), press resistance (11%). Different mechanism — Lavia more via creativity, box threat.
Nicolas Seiwald RBL · Bundesliga · 180 cm / 80 kg
64%
Driven by: retention (24%), territory (wide vs central) (23%), press resistance (17%). Different mechanism — Lavia more via crossing, box threat; Seiwald more via through-balls, defensive aggression.
Thomas Partey Villarreal · La Liga 25/26 · 185 cm / 77 kg
61%
Driven by: territory (wide vs central) (30%), press resistance (17%), creativity (13%). Different mechanism — Lavia more via passing directness, retention; Partey more via carrying, through-balls.
Shea Charles Fulham · 189 cm / 87 kg
60%
Driven by: retention (21%), territory (wide vs central) (19%), build-up (18%). Different mechanism — Lavia more via passing directness; Charles more via defensive aggression, through-balls.
16

Summary

Roméo Lavia is a tempo controller / deep-lying playmaker: 87% completion, 4 line-breaks and 2.1 progressive passes /90, resisting pressure with 50% dribble success. A central controller. [Off-ball screening position and scanning need tracking data.]

Based on 6 matches (295 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a tempo controller / deep-lying playmaker — best used in a system built around that identity. His biggest room for growth is progression — even a modest improvement there would meaningfully lift his overall tempo controller 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.

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