العربيةVision AI ← BACK TO SEARCH
Player reportLigue 1 2026

Thomas Jørgensen

Toulouse
Half-space creator AM
39% of actions in the half-spaces
Capability Analysis
Chance Creation25%vs 11 attacking mids
"Does he create real chances for others?"
Expected assists /900.14xA64%
Through balls /900.00%
Threat added by passing /900.74xT18%
Box entries (pass) /901.3618%
Box Threat42%vs 11 attacking mids
"Is he a genuine goal threat by shot volume and quality?"
xG /900.19xG45%
Shots /901.8545%
xGOT /900.2xGOT36%
Ball-Carrying50%vs 11 attacking mids
"Does he advance the ball himself when the pass isn't on?"
Progressive carries /904.8155%
Carry distance /90141.75m64%
Successful take-ons /900.7418%
Take-on success42.86%64%
attacking midadvanced playmaker (8)creationbetween the lines
729
minutes
8 apps
11
key passes
1.36/90
20
progressive passes
2.5/90
6
box entries
0.74/90
19
final-3rd entries
2.3/90
2
goals
1.58 xG
14
dribbles
43% won
75%
pass completion
287 passes
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
Central, Middle third — between the lines — mostly in the middle third (46% of his 287 passes)
75% completion · 287× in 8/8 matches
↓
TURN / BEAT MAN
face forward in the pocket
43% won · 14× in 7/8 matches
↓
CREATE
through-ball, cut-back, key pass
1.36/90 · 11× in 5/8 matches
↓
FINISH
arrive and shoot from central zones
2 goals · 1.58 xG · 15× in 8/8 matches
Signature: receive between the lines → turn → create or finish.
21

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 →
36
passes / match
2.0
dribbles / match
29–43
pass range (matches)
1–3
dribble range (matches)
Pass range = his fewest and most passes in any single match this season (29 at the low end, 43 at the high) — a measure of match-to-match involvement, not pass distance. Dribble range works the same way, for dribbles/carries per match.
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

90 tracked carries (11.1/90, 28 progressive, 1148m 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.

2%12%14%12%6%16%11%3%3%3%6%8%3%
progressivelateral/short% of his 90 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 9m, longest 37m
By zone — where the carry started → where it ended
16Outside → Inside
54Inside → Inside
14Outside → Outside
6Inside → Outside
First (28)Second (26)Third (21)Fourth (15)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →

Dribbles (1v1s)

Does he carry to create or drift wide? Dribbles by channel. Season rate: 1.73 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 57%
OUTSIDE 43%
Dribble location — 8 inside · 6 outside
Right Wing
4 · 29%
Right Half-Space
2 · 14%
Central
4 · 29%
Left Half-Space
2 · 14%
Left Wing
2 · 14%
Vision AI His carries cluster centrally — a central creator.
16

How does he build & move 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 →RWRHSCLHSLWRW5139%2053%274%24%2RHS5828%1647%2721%123%22%1C5914%815%941%2420%1210%6LHS248%221%529%742%10LW2214%314%373%16FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the right wing in the middle third → the right half-space in the middle third — 4 progressive passes (14% of his progression) at 0.015 xT each. He moves it inside.

His progression is inward: 46% of progressive passes move the ball toward the middle versus 7% going wider — he cuts in rather than holding width.

9% of his passes are cross-field switches — he changes the point of attack often.

Quality behind the volume: 13 line-breaking passes and 19 final-third entries, 1.8 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
1%4%9%12%11%5%3%10%10%14%1%1%2%3%2%5%6%
completedincomplete287 passes · any zone → any zone · own goal left, attacking →
287
passes
75%
completed
73
lost
Vision AIIn line with his 75% season completion rate.
11

How does he progress play?

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

20
progressive · 2.5/90
19
final-third entries · 2.3/90
6
box entries · 0.74/90
16
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.
02

How does he create chances?

11 key passes (1.36/90), 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:
11%22%11%33%22%
chance creation (9)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 (3)from the right (6)of 9 key passes landing in the final thirdattacking ↑ toward goal
13

Can he finish?

15 shots · 1.58 xG · 2 goals (+0.42 vs xG). Mostly left-footed. Circle size = xG.

shots  15
on target  9
goals  2
xG  1.58
xG on target  1.60
xG / shot  0.105
Where he shoots from — click an area of the box
09

Where does he become vulnerable?

81 possessions lost. Directness has a cost — the question is where. Attacking-third losses are cheap; deep ones are dangerous.

45
attacking third (cheap)
26
middle third
10
own third (dangerous)
Vision AI 56% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 2.42 danger-index/90 · 0.242 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
14

What is his passing profile?

287
passes attempted
39%
mostly forward
52%
mostly short
Direction
Forward
113 · 39%
Sideways
92 · 32%
Backward
82 · 29%
Length (completed)
Short (<15m)
111 · 52%
Medium
85 · 40%
Long (>30m)
18 · 8%
12

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.

0.530.230.190.130.110.10
own goal left, attacking →
Highest-value routes (xT)
0.53
Central Att third → Left Half-Space Att third
2 passes
0.23
Left Half-Space Att third → Left Half-Space Att third
1 passes · 1 to a shot
0.19
Central Mid third → Right Wing Att third
2 passes
0.13
Right Half-Space Mid third → Right Half-Space Att third
1 passes
0.11
Right Half-Space Def third → Right Half-Space Mid third
1 passes
0.10
Central Mid third → Left Half-Space Att third
1 passes
06

Where Does He Receive?

The zones where Thomas Jørgensen 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
15%
Primary
Central, Middle third
12%
Secondary
Right Wing, Middle third
11%
Third
Right Half-Space, Middle 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 Thomas Jørgensen 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:
26981519112929421641325363616
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%4%9%12%11%5%3%10%10%14%1%1%2%3%2%5%6%
own goal left, attacking →
15

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.

11Key pass
2Cross
5Cutback
20Progressive
31Long ball
14Switch
By zone — where the pass started → where it landed
37Outside → Inside
100Inside → Inside
36Outside → Outside
41Inside → Outside
By direction
113Forward
82Backward
92Sideways
own goal left, attacking →
05

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 switches it out from the central to the left hs in the final third — 2 passes worth 0.53 xT.
Where do his chances come from?
Of 11 key passes, his busiest route is a delivery where he switches it out from the central to the right hs in the final third — 2 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: 41% of his 17 touches there are lost (7 times).
—6 touches · too few18%2/11 lost25%2/8 lost—3 touches · too few—6 touches · too few18%6/34 lost15%5/34 lost19%8/43 lost20%3/15 lost—6 touches · too few25%6/24 lost35%11/31 lost36%10/28 lost41%7/17 lost33%7/21 lostRWRHSCLHSLWDEFMIDATT
03

Does he carry inside or outside — his ball-carries across the pitch

Four arrows, one per movement class of his ball-carries: outside→inside (cutting in with the ball), inside→outside (carrying wide), outside→outside (down the touchline) and inside→inside (through the middle). Each count is measured from the carry's real start and end coordinates.

own goal left, attacking →
Across 90 ball-carries, his dominant tendency is that he carries through central areas (60%). He carries from outside into the middle 16 times and out toward the touchline 6 — a genuine inside forward who cuts in with the ball.
04

What happens right after he carries the ball

Every carry's end point matched against his own very next pass or shot in the same match, when one starts almost exactly there — the direct continuation of that touch, not a separate stat. “No clean link” means no pass or shot of his own started close enough to count (often the carry ended in a tackle or a loss); it isn't a claim about exactly what happened, only that nothing traceable followed.

Shot
4 · 4%
Progressive / key pass
6 · 7%
Simple pass
54 · 60%
No clean link
26 · 29%
Of 90 carries, 4% flow straight into a shot of his own, 7% into a key or progressive pass — a genuine end product to the carry, not just ball retention. 29% have no clean link to a next touch of his own close to where the carry ended.
10

Crosses & Cutbacks

2 crosses (0.25/90, 0 completed) and 5 cutbacks (0.62/90, 2 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.

18

How & where does he defend?

98 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 →
14
tackles · 57% won
7
interceptions · 0.9/90
36
recoveries · 4.4/90
2
clearances · 0.2/90
5
blocks
45
avg action height
16
won high (att 3rd)
50
middle third
32
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 57 proactive ball-wins (7.0/90), tackle success 57%. 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.

44
attacking-half actions · 5.43/90
17

Against Different Pressing Intensities

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Thomas Jørgensen keep producing when the game is tight and the press is high? Tiers of ~2-4 matches — directional evidence, not proof.

press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 4.1, 2m)
0.49
0.5
2.60
50%
Mid press (PPDA 5.5, 2m)
0.64
1.9
1.42
60%
Low press (PPDA 6.7, 4m)
0.92
3.7
0.74
29%
Team

Team context

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

19

Impact on the Team

Insufficient sample: Thomas Jørgensen played nearly every Toulouse match in the loaded data, so there is no meaningful "without him" comparison yet. This section fills in as more matches (and the rest of the season) are scraped.

20

His Share of the Team

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

category
share
him / team
goals
17%
2 / 12
expected goals (xG)
5%
1.6 / 33.6
zone-14 entries
5%
9 / 192
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

22

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 247 attacking 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.

Advanced playmaker (8)64%Half-space creator62%
Why Advanced playmaker (8) 64%: a weighted blend of creativity 76 (weight 35%) + progression 58 (weight 25%) + final-third threat 50 (weight 25%) + box threat 51 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
passing directness
Strong
ball-winning, transition, creativity, receiving zones
Average
build-up, carrying, defensive aggression, progression, line-breaking, box threat, press resistance, final-third threat, retention, dribbling
Weak
crossing, through-balls, territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Passing directness
95
Ball-winning
81
Transition ~proxy
78
Creativity
76
Receiving zones
71
Build-up
65
Carrying
65
Defensive aggression
59
Progression
58
Line-breaking
56
Box threat
51
Press resistance ~proxy
50
Final-third threat
50
Retention
48
Dribbling
41
Crossing
15
Through-balls ~proxy
14
Territory (wide vs central)
7
23

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: 184 cm / 70 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.

Javi Hernández Espanyol · La Liga · 182 cm / 72 kg
76%
Driven by: passing directness (20%), transition (20%), territory (wide vs central) (19%). Different mechanism — Jørgensen more via ball-winning, receiving zones; Hernández more via through-balls, dribbling.
Carney Chukwuemeka Borussia Dortmund · Bundesliga · 187 cm / 77 kg
74%
Driven by: crossing (20%), territory (wide vs central) (17%), ball-winning (14%). Different mechanism — Jørgensen more via passing directness; Chukwuemeka more via retention, dribbling.
Kiernan Dewsbury-Hall Everton · Premier League · 178 cm / 80 kg
68%
Driven by: passing directness (19%), territory (wide vs central) (17%), ball-winning (16%). Different mechanism — Jørgensen more via carrying, box threat; Dewsbury-Hall more via through-balls, final-third threat.
Matheus Cunha Man Utd · Premier League · 183 cm / 76 kg
66%
Driven by: ball-winning (19%), transition (17%), territory (wide vs central) (15%). Different mechanism — Jørgensen more via passing directness, creativity; Cunha more via dribbling, box threat.
Joe Willock Newcastle · Premier League · 179 cm / 71 kg
62%
Driven by: ball-winning (19%), through-balls (19%), territory (wide vs central) (15%). Different mechanism — Jørgensen more via passing directness, creativity; Willock more via retention, crossing.
Ethan Nwaneri Borussia Dortmund · Bundesliga · 176 cm / 70 kg
61%
Driven by: territory (wide vs central) (24%), transition (14%), build-up (13%). Different mechanism — Jørgensen more via ball-winning, passing directness; Nwaneri more via retention, build-up.
24

Summary

Thomas Jørgensen is an advanced playmaker (8) / half-space creator: 1.36 key passes /90, 2.5 progressive passes, 2 goals from 1.58 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]

Based on 8 matches (729 minutes) — an early read, treat with caution until more minutes are logged. He profiles as an advanced playmaker (8) / half-space creator — best used in a system built around that identity. His biggest room for growth is final-third threat — even a modest improvement there would meaningfully lift his overall advanced playmaker (8) 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.

Vision AI · building report