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Player reportPremier League 2026

Jan Paul van Hecke

Tottenham
Ball-playing centre-back CB
10.1 progressive passes/90 · 2.6 line-breaking/90
Capability Analysis
Aerial & Box Defending22%vs 50 centre-backs
"Can he win the individual defensive battle in his own box?"
Aerial duels won /900.00%
Aerial win rate: 0.0%
Clearances /904.8544%
Ball-Winning58%vs 50 centre-backs
"How actively does he win the ball back?"
Interceptions /901.1862%
Ball recoveries /903.0340%
Tackles /901.4562%
Duels won /902.8870%
Breaking Pressure
only 57 pressured-passing actions across 1 high-press match -- not enough sample (needs 5+ matches and 12+ actions)
Progression84%vs 50 centre-backs
"Can he move the team forward with a pass, not just recycle it sideways?"
Progressive passes /906.2294%
Line-breaking passes /901.6290%
Threat added by passing /901.7xT96%
Pass accuracy87.43%58%
Ball-Carrying98%vs 50 centre-backs
"Does he advance the ball himself when the pass isn't on?"
Progressive carries /9015.0498%
Carry distance /90308.42m98%
centre-backstopper centre-backbuild-upline-breaking
768
minutes
8 apps
667
passes
90% completed
90%
pass completion
667 passes
86
progressive passes
10.1/90
50
line-breaking passes
5.9/90
161
defensive actions
18.9/90
23
tackles + interceptions
60% tackle win
37
clearances
4.3/90
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
in the first line of build-up — mostly in the middle third (64% of his 667 passes)
90% completion · 667× in 8/8 matches
↓
BREAK A LINE
vertical pass past the opponent midfield
10.1 prog/90 · 50× in 8/8 matches
↓
SWITCH PLAY
diagonal to the far side
cross-field balls · 19× in 6/8 matches
↓
PROGRESS
entries into the final third
8.7/90 · 74× in 8/8 matches
Signature: Receive → Break A Line → Switch Play → Progress — the only steps proven repeatable this season (4 of 5 in the full pattern). Not enough evidence yet for the rest of the chain below.
Not a pattern: carry out — 2× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
17

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 →
83
passes / match
18.9
def actions / 90
62–112
pass range (matches)
37
clearances
Pass range = his fewest and most passes in any single match this season (62 at the low end, 112 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.

10

How dangerous are his carries?

Real ball-carries

244 tracked carries (28.6/90, 78 progressive, 2465m 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.

5%13%21%9%3%1%10%18%17%1%1%
progressivelateral/short% of his 244 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 8m, longest 39m
By zone — where the carry started → where it ended
13Outside → Inside
201Inside → Inside
21Outside → Outside
9Inside → Outside
First (86)Second (74)Third (47)Fourth (37)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).

15
tackle duels
9
won
6
beaten · 40%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 67%
OUTSIDE 33%
Tackle-duel location — 10 inside · 5 outside
Right Wing
5 · 33%
Right Half-Space
5 · 33%
Central
3 · 20%
Left Half-Space
2 · 13%
Left Wing
0 · 0%
Vision AI beaten in 6 of 15 tackle duels (40% loss rate) — a solid 1v1 defensive record.
Every tackle duel, exact location
wonlost — dribbled pastown goal left, attacking →

He attempted only 1 dribble of his own all season — dribbling is not part of this role; his ball-carrying is covered above, his defending against the dribble below.

02

How does he build & move the ball?

How does he escape the first line?

17%
vertical passes
62×
4%
switches
14×
46%
carries
170×
34%
short circulation
125×
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 →RWRHSCLHSLWRW9337%3438%3525%231%1RHS33326%8621%7142%1409%302%6C16513%2116%2736%6028%476%10LHS911%133%322%233%3LW0FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: the right half-space in the middle third → the right half-space in the final third — 10 progressive passes (17% of his progression) at 0.143 xT each. He keeps it in the same lane.

His progression is inward: 43% of progressive passes move the ball toward the middle versus 8% going wider — he cuts in rather than holding width.

Only 8% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 22 line-breaking passes and 74 final-third entries, 14.0 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
4%14%18%16%5%1%9%14%14%2%0%0%0%0%
completedincomplete667 passes · any zone → any zone · own goal left, attacking →
667
passes
90%
completed
67
lost
Vision AIIn line with his 90% season completion rate.
03

How does he progress play?

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

86
progressive · 10.1/90
74
final-third entries · 8.7/90
7
box entries · 0.82/90
43
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.
12

How does he create chances?

7 key passes (0.82/90), 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:
14%14%14%43%14%
chance creation (7)assist (0)% of the selected group's key passes originating in each zone
07

Where does he become vulnerable?

68 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.

8
attacking third (cheap)
38
middle third
22
own third (dangerous)
Vision AI 12% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 3.48 danger-index/90 · 0.437 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
05

What is his passing profile?

667
passes attempted
53%
mostly forward
53%
mostly medium
Direction
Forward
355 · 53%
Sideways
230 · 34%
Backward
82 · 12%
Length (completed)
Short (<15m)
243 · 40%
Medium
318 · 53%
Long (>30m)
39 · 6%
06

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.

1.640.710.600.490.480.45
own goal left, attacking →
Highest-value routes (xT)
1.64
Right Half-Space Mid third → Right Half-Space Att third
7 passes
0.71
Right Half-Space Mid third → Right Half-Space Mid third
8 passes
0.60
Right Half-Space Mid third → Central Att third
3 passes · 1 to a shot
0.49
Right Half-Space Mid third → Central Mid third
4 passes
0.48
Right Half-Space Mid third → Right Wing Att third
8 passes
0.45
Right Half-Space Mid third → Right Wing Mid third
8 passes
08

Where Does He Receive?

The zones where Jan Paul van Hecke 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
37%
Primary
Right Half-Space, Middle third
18%
Secondary
Central, Middle third
13%
Third
Right Half-Space, Defensive third
These are the zones where he collected the ball most.
09

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Jan Paul van Hecke 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:
13117609691147309612311033
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.

4%14%18%16%5%1%9%14%14%2%0%0%0%0%
own goal left, attacking →
11

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.

7Key pass
2Cross
86Progressive
50Long ball
19Switch
By zone — where the pass started → where it landed
58Outside → Inside
380Inside → Inside
35Outside → Outside
127Inside → Outside
By direction
355Forward
82Backward
230Sideways
own goal left, attacking →
04

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 right hs, advancing it forward in the middle third — 7 passes worth 1.64 xT.
Where do his chances come from?
Of 7 key passes, his busiest route is a delivery where he plays inside from the right hs toward the central 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 right wing in the final third: 25% of his 12 touches there are lost (3 times).
20%10/51 lost10%9/89 lost4%2/48 lost—2 touches · too few—0 touches · too few19%10/53 lost7%17/248 lost9%11/119 lost0%0/8 lost—0 touches · too few25%3/12 lost8%2/24 lost15%2/13 lost—0 touches · too few—0 touches · too fewRWRHSCLHSLWDEFMIDATT
Out of possession

Out of possession

Where and how he defends and presses.

13

How & where does he defend?

161 defensive actions across the season (18.9/90). 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 →
15
tackles · 60% won
8
interceptions · 0.9/90
29
recoveries · 3.4/90
37
clearances · 4.3/90
1
blocks
34
avg action height
12
won high (att 3rd)
60
middle third
89
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 52 proactive ball-wins (6.1/90), tackle success 60%. He defends mostly around the middle third.
14

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Jan Paul van Hecke 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 ~2-4 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 4.1, 2m)
89%
8.4
3.7
1.51
Mid press (PPDA 5.0, 2m)
90%
8.9
5.1
2.03
Low press (PPDA 7.5, 4m)
90%
11.5
7.3
2.29
Team

Team context

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

15

Impact on the Team

Insufficient sample: Jan Paul van Hecke played nearly every Tottenham 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.

16

His Share of the Team

Of everything Tottenham produced this season, the categories where the biggest share ran through Jan Paul van Hecke specifically — his share of the team total, not a per-90 rate.

category
share
him / team
final-third entries
16%
389 / 2476
clearances
15%
227 / 1475
goals
14%
1 / 7
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

18

Playing-Style Profile

Not raw event counts — football style scores: weighted models scored 0–100 against the 515 centre-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.

Stopper centre-back69%Ball-playing centre-back68%
Why Stopper centre-back 69%: a weighted blend of defensive aggression 68 (weight 35%) + ball-winning 58 (weight 40%) + retention 52 (weight 15%) + transition 76 (weight 10%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
progression, final-third threat, line-breaking, receiving zones
Strong
carrying, passing directness, transition, through-balls, box threat, creativity
Average
defensive aggression, build-up, crossing, ball-winning, retention
Weak
press resistance, territory (wide vs central), dribbling
Unknown
aerial ability, marking, off-ball running — not in event data
Progression
96
Final-third threat
91
Line-breaking
89
Receiving zones
89
Carrying
83
Passing directness
80
Transition ~proxy
76
Through-balls ~proxy
74
Box threat
71
Creativity
70
Defensive aggression
68
Build-up
64
Crossing
59
Ball-winning
58
Retention
52
Press resistance ~proxy
35
Territory (wide vs central)
23
Dribbling
16
19

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: 189 cm / 79 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.

Marcos Senesi Tottenham · 185 cm / 78 kg
84%
Driven by: progression (16%), transition (12%), final-third threat (12%). Different mechanism — Hecke more via retention; Senesi more via territory (wide vs central), ball-winning.
Manuel Akanji Inter · Serie A · 188 cm / 91 kg
83%
Driven by: progression (15%), receiving zones (13%), final-third threat (12%). Different mechanism — Hecke more via passing directness; Akanji more via retention, crossing.
Ramy Bensebaini Borussia Dortmund · Bundesliga · 187 cm / 82 kg
79%
Driven by: progression (18%), final-third threat (15%), receiving zones (12%). Different mechanism — Hecke more via passing directness, build-up; Bensebaini more via territory (wide vs central), crossing.
Pau Cubarsí Barcelona · La Liga · 183 cm / 79 kg
78%
Driven by: transition (15%), final-third threat (12%), dribbling (11%). Different mechanism — Hecke more via line-breaking, box threat; Cubarsí more via retention.
Eric García Barcelona · La Liga · 180 cm / 77 kg
78%
Driven by: progression (15%), final-third threat (14%), receiving zones (13%). Different mechanism — Hecke more via carrying, passing directness; García more via territory (wide vs central), ball-winning.
Andreas Christensen Barcelona · La Liga · 189 cm / 84 kg
77%
Driven by: dribbling (14%), receiving zones (14%), transition (13%). Different mechanism — Hecke more via progression, line-breaking; Christensen more via retention.
20

Summary

Jan Paul van Hecke is a stopper centre-back / ball-playing centre-back: 90% pass completion, 50 line-breaking passes and 10.1 progressive passes /90. A build-and-progress centre-back whose value is in beating the first line with the pass, not in raw defensive volume. [Aerial duels, marking, line-height and 1v1 recovery need aerial-event + tracking data, absent here.]

Based on 8 matches (768 minutes) — an early read, treat with caution until more minutes are logged. He profiles as a stopper centre-back / ball-playing centre-back — best used in a system built around that identity. His biggest room for growth is retention — even a modest improvement there would meaningfully lift his overall stopper centre-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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