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Player reportLigue 1 2025/26

Thibault De Smet

Paris FC
Defensive full-back FB
12.1 defensive actions/90 · low final-third share 19%
full-backinverted full-backprogressioncrossing
1241
minutes
17 apps
83%
pass completion
672 passes
69
progressive passes
5.0/90
42
final-3rd entries
3.0/90
7
box entries
0.51/90
167
defensive actions
12.1/90
31
tackles + interceptions
48% tackle win
7
dribbles
43% won
Overview

The player

Who he is and how he compares with his peers.

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
Left Wing, Middle third — wide or inverted — mostly in the middle third (50% of his 672 passes)
83% completion · 672× in 17/17 matches
↓
PROGRESS
carry or combine up the flank
5.0 prog/90 · 69× in 15/17 matches
↓
DRIBBLE
beat his man up the line
43% won · 7× in 6/17 matches
↓
DELIVER
cross or cut-back into the box
5 key passes · 7× in 4/17 matches
↓
DEFEND
1v1 and cover on his side
167 def actions · lost 42% deep · 167× in 17/17 matches
Signature: receive wide/inverted → progress the flank → deliver into the box → recover to defend 1v1. Attack the space behind him in transition.
18

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 →
40
passes / match
12.1
def actions / 90
6–69
pass range (matches)
53
clearances
Pass range = his fewest and most passes in any single match this season (6 at the low end, 69 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.

08

How dangerous are his carries?

Real ball-carries

124 tracked carries (9.0/90, 32 progressive, 1113m 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.

1%1%1%1%5%16%37%25%12%2%
progressivelateral/short% of his 124 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 7m, longest 31m
By zone — where the carry started → where it ended
14Outside → Inside
16Inside → Inside
90Outside → Outside
4Inside → Outside
First (55)Second (44)Third (24)Fourth (1)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).

23
tackle duels
11
won
12
beaten · 52%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 35%
OUTSIDE 65%
Tackle-duel location — 8 inside · 15 outside
Right Wing
0 · 0%
Right Half-Space
1 · 4%
Central
0 · 0%
Left Half-Space
7 · 30%
Left Wing
15 · 65%
Vision AI beaten in 12 of 23 tackle duels (52% loss rate) — a real defensive leak worth flagging.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

He attempted only 7 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 build & move the ball?

How does he escape the first line?

16%
vertical passes
51×
1%
switches
4×
23%
carries
74×
59%
short circulation
187×
Answer: he escapes the press primarily through carrying — stepping out with the ball.

How he moves the ball — his 4 busiest progression routes, not where every pass starts and ends separately. Arrow width = how often, colour = xT gained, dashed = switch of play. The full breakdown is in the lane matrix below.

own goal left, attacking →
Lane transition matrix — when he receives in a lane, where does it go?
TO →RWRHSCLHSLWRW1100%1RHS520%120%160%3C1421%357%814%27%1LHS791%18%627%2135%2829%23LW4610%10%25%2541%19152%242FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the left wing in the middle third → the left half-space in the middle third — 15 progressive passes (22% of his progression) at 0.003 xT each. He moves it inside.

His progression is inward: 58% of progressive passes move the ball toward the middle versus 0% going wider — he cuts in rather than holding width.

Only 4% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 15 line-breaking passes and 42 final-third entries, 6.3 total xT added.

Origin and destination are measured on the same event row — no receiver inference. Receiver identity is not recoverable from this data source.
All passes — origin zone share
Filter: from to
0%0%0%1%1%1%1%8%23%24%23%13%5%
completedincomplete672 passes · any zone → any zone · own goal left, attacking →
672
passes
83%
completed
112
lost
Vision AIIn line with his 83% season completion rate.
05

How does he progress play?

How much he drives the ball forward. Progressive = completed pass advancing ≥15 toward goal.

69
progressive · 5.0/90
42
final-third entries · 3.0/90
7
box entries · 0.51/90
18
progression index /90
Progression index: one composite number — progressive passes + progressive carries + 2% of total distance progressed + 8× positive xT added, all per 90. Weights VOLUME and THREAT together rather than counting progressive actions alone.
10

How does he create chances?

5 key passes (0.36/90), 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:
20%20%60%
chance creation (5)assist (0)% of the selected group's key passes originating in each zone
09

Where does he become vulnerable?

116 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.

28
attacking third (cheap)
39
middle third
49
own third (dangerous)
Vision AI 24% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 3.81 danger-index/90 · 0.453 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
12

What is his passing profile?

672
passes attempted
36%
mostly forward
51%
mostly short
Direction
Forward
242 · 36%
Sideways
206 · 31%
Backward
224 · 33%
Length (completed)
Short (<15m)
286 · 51%
Medium
249 · 44%
Long (>30m)
25 · 4%
11

Preferred Progression Routes — xT-weighted

His progressive passes as zone→zone routes, weighted by expected threat (xT) added — arrow width and the number are the total xT generated on each route, not just how often he plays it. This is where he actually moves the needle.

1.330.690.680.660.630.34
own goal left, attacking →
Highest-value routes (xT)
1.33
Left Wing Mid third → Left Wing Att third
12 passes
0.69
Left Wing Mid third → Left Wing Mid third
10 passes
0.68
Left Wing Mid third → Left Half-Space Att third
3 passes
0.66
Left Wing Def third → Left Wing Mid third
13 passes
0.63
Left Wing Def third → Left Half-Space Mid third
8 passes
0.34
Left Wing Att third → Left Half-Space Att third
1 passes
06

Where Does He Receive?

The zones where Thibault De Smet 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
41%
Primary
Left Wing, Middle third
28%
Secondary
Left Wing, Defensive third
15%
Third
Left Wing, Attacking third
These are the zones where he collected the ball most.
07

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Thibault De Smet 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:
531561611618732158610111
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.

0%0%0%1%1%1%1%8%23%24%23%13%5%
own goal left, attacking →
13

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.

5Key pass
12Cross
5Cutback
69Progressive
88Long ball
9Switch
By zone — where the pass started → where it landed
218Outside → Inside
72Inside → Inside
244Outside → Outside
26Inside → Outside
By direction
242Forward
224Backward
206Sideways
own goal left, attacking →
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 →
How does he progress the ball forward?
His most common route for progressing play: he plays straight through the left wing, advancing it forward in the middle third — 12 passes worth 1.33 xT.
Where do his chances come from?
Of 5 key passes, his busiest route is a delivery where he switches it out from the central 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: 25% of his 20 touches there are lost (5 times).
—0 touches · too few—0 touches · too few—3 touches · too few13%3/23 lost24%45/187 lost—1 touch · too few—4 touches · too few12%1/8 lost8%4/48 lost11%31/272 lost—0 touches · too few—1 touch · too few—6 touches · too few25%5/20 lost21%21/99 lostRWRHSCLHSLWDEFMIDATT
02

Crosses & Cutbacks

12 crosses (0.87/90, 4 completed) and 5 cutbacks (0.36/90, 1 completed) — two separate wide-delivery patterns into the box, each its own map with a completed/failed filter. Neither is a tagged event, so both are inferred from pass geometry — the intended end point of a failed attempt is still real data (an interception doesn’t erase where the ball was aimed): a cross is a pass aimed into the box starting from a wide channel; a cutback starts almost on the byline but is squared back rather than driven forward, aimed centrally around the box. The completed-cross count was checked against this platform’s own real match-level cross totals and lands within about 1 cross of the true count.

Crosses — close-up on the final third
Cutbacks — close-up on the final third
completedfailed (dashed)close-up on the box — attacking ↑ toward goal
Out of possession

Out of possession

Where and how he defends and presses.

14

How & where does he defend?

167 defensive actions across the season (12.1/90). 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 →
23
tackles · 48% won
8
interceptions · 0.6/90
46
recoveries · 3.3/90
53
clearances · 3.8/90
5
blocks
27
avg action height
11
won high (att 3rd)
40
middle third
116
own third
Vision AI A deep-defending defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 77 proactive ball-wins (5.6/90), tackle success 48%. He defends deep, protecting his box — a last-line stopper.
15

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Thibault De Smet 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 ~5-7 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 5.1, 5m)
83%
6.3
5.8
0.93
Mid press (PPDA 7.6, 5m)
82%
6.0
7.8
1.08
Low press (PPDA 10.7, 7m)
84%
3.2
5.6
0.93
Team

Team context

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

16

Impact on the Team

Paris FC's output per match with Thibault De Smet (17 matches) versus without him (17 matches). 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 (17)
WITHOUT (17)
Δ
goals against /match
1.59
1.35
+0.24
points /match
1.18
1.41
-0.24
goals for /match
1.41
1.35
+0.06
xG for /match
1.35
0.41
+0.94
17

His Share of the Team

Of everything Paris FC produced this season, the categories where the biggest share ran through Thibault De Smet specifically — his share of the team total, not a per-90 rate.

category
share
him / team
clearances
5%
53 / 1174
progressive passes
4%
71 / 1722
tackles
3%
24 / 700
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

19

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 231 full-backs 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.

Inverted full-back62%Overlapping full-back18%
Why Inverted full-back 62%: a weighted blend of build-up 73 (weight 35%) + retention 68 (weight 30%) + progression 28 (weight 25%) + press resistance 56 (weight 10%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
—
Strong
territory (wide vs central), build-up
Average
retention, press resistance
Weak
receiving zones, dribbling, defensive aggression, creativity, through-balls, line-breaking, carrying, final-third threat, progression, ball-winning, transition, box threat, crossing, passing directness
Unknown
aerial ability, marking, off-ball running — not in event data
Territory (wide vs central)
82
Build-up
73
Retention
68
Press resistance ~proxy
56
Receiving zones
39
Dribbling
36
Defensive aggression
35
Creativity
35
Through-balls ~proxy
35
Line-breaking
33
Carrying
30
Final-third threat
29
Progression
28
Ball-winning
24
Transition ~proxy
23
Box threat
22
Crossing
17
Passing directness
10
20

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: 183 cm / 65 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 Ligue 1, Bundesliga, La Liga, Premier League 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.

Adam Marusic Lazio · Serie A · 185 cm / 76 kg
81%
Driven by: build-up (12%), territory (wide vs central) (12%), transition (11%). Different mechanism — Marusic more via crossing, passing directness.
Nhoa Sangui Paris FC 25/26 · 178 cm / 67 kg
76%
Driven by: box threat (14%), defensive aggression (13%), passing directness (13%). Different mechanism — Smet more via territory (wide vs central), defensive aggression; Sangui more via crossing, carrying.
Milos Kerkez Liverpool · Premier League · 180 cm / 71 kg
76%
Driven by: crossing (25%), ball-winning (13%), passing directness (11%). Different mechanism — Smet more via build-up, retention; Kerkez more via carrying, box threat.
Ximo Navarro Deportivo · La Liga · 176 cm / 75 kg
76%
Driven by: transition (18%), crossing (18%), passing directness (12%). Different mechanism — Smet more via dribbling, press resistance; Navarro more via ball-winning, box threat.
Genesis Antwi Strasbourg · 189 cm
72%
Driven by: crossing (12%), box threat (11%), passing directness (9%). Different mechanism — Smet more via territory (wide vs central), line-breaking; Antwi more via dribbling, ball-winning.
Buba Sangaré Elche · La Liga · 183 cm / 75 kg
70%
Driven by: transition (16%), box threat (13%), final-third threat (11%). Different mechanism — Smet more via territory (wide vs central), line-breaking; Sangaré more via ball-winning.
21

Summary

Thibault De Smet is an inverted full-back: 5.0 progressive passes and 7 box entries, delivering 5 key passes. Overlap-first full-back. [1v1 recovery pace and off-ball overlap timing need tracking.]

Based on 17 matches (1241 minutes) — a reasonable read, still building toward a full-season sample. He profiles as an inverted full-back — 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 inverted full-back 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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