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Player reportPremier League 2025/26

Mathys Tel

Tottenham
Central midfielder AM
balanced central profile
attacking midadvanced playmaker (8)creationbetween the lines
1852
minutes
37 apps
33
key passes
1.60/90
32
progressive passes
1.6/90
16
box entries
0.78/90
23
final-3rd entries
1.1/90
5
goals
3.36 xG
125
dribbles
42% won
71%
pass completion
616 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
Left Wing, Attacking third — between the lines — mostly in the attacking third (56% of his 616 passes)
71% completion · 616× in 36/36 matches
↓
TURN / BEAT MAN
face forward in the pocket
42% won · 125× in 30/36 matches
↓
CREATE
through-ball, cut-back, key pass
1.60/90 · 33× in 18/36 matches
↓
FINISH
arrive and shoot from central zones
5 goals · 3.36 xG · 44× in 23/36 matches
Signature: receive between the lines → turn → create or finish.
02

attacking mid radar — percentile vs his peers

hierarchical score 58/100

A position-aware radar: these 12 axes are the metrics that matter for a attacking mid. Each axis is his percentile among the 57 attacking mids in the league (min 450 min). (padj) = possession-adjusted: defensive volumes are scaled by how much defending his team actually does, so opportunity is not confused with ability.

xA/9051% · #28/57(0.07)Half-space/9047% · #30/57(2.92)Box deliveries/9077% · #13/57(2.48)xT/9070% · #17/57(0.84)Progressive/9079% · #12/57(4.28)Dribbles/9096% · #2/57(2.58)Dribble %74% · #15/57(42.40)xG/9039% · #35/57(0.16)Shots/9065% · #20/57(2.14)Final-3rd/9042% · #33/57(2.48)Pass %25% · #43/57(71.43)Duel win %54% · #26/57(15.57)
Radar read: elite for dribbles/90 (96%), progressive/90 (79%), box deliveries/90 (77%); weakest axes pass % (25%), xg/90 (39%). Percentiles, not raw values — 50% = league-average attacking mid.
League distribution — every dot a attacking mid, dashed cross = league average, diamond = him
X Y
Full context table — him vs league average vs top 5%
metrichimleague avgtop 5%pctl
xA/900.070.070.1851%
Half-space/902.922.926.3447%
Box deliveries/902.481.733.6877%
xT/900.840.631.3670%
Progressive/904.282.796.0979%
Dribbles/902.581.082.3896%
Dribble %42.4034.6947.9774%
xG/900.160.180.3539%
Shots/902.141.892.9165%
Final-3rd/902.482.755.3442%
Pass %71.4375.6184.5425%
Duel win %15.5715.1334.3554%

Evidence-based evaluation

Same underlying data, read by Vision AI: several independent dimensions with the specific evidence behind each, not one number.

Chance Creation: strong (70/100 vs role peers), driven by shot-creating actions/90 (well above peer average, 93rd percentile).
Progression Value: strong (76/100 vs role peers), driven by progressive passes/90 (well above peer average, 79th percentile).
Decision Quality: below-average (37/100 vs role peers), driven by pass completion vs difficulty-adjusted expectation (pts) (below peer average, 37th percentile).
Finishing: average (49/100 vs role peers), driven by xG/90 (below peer average, 39th percentile).
Possession Value: average (50/100 vs role peers), driven by location-weighted turnover cost/90 (below peer average, 21st percentile). Times dispossessed/90 is well controlled (100th percentile).
41%
avg opponent strength faced
0%
of matches vs top-third teams
Tactical fit (Tottenham): his Territory (wide vs central) (96) sits well above his own team's average (50, itself the 39% mark league-wide) — the single biggest gap between him and how Tottenham plays on the whole.
03

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 →
17
passes / match
4.2
dribbles / match
2–41
pass range (matches)
1–13
dribble range (matches)
Pass range = his fewest and most passes in any single match this season (2 at the low end, 41 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.

10

How dangerous are his carries?

Real ball-carries

238 tracked carries (11.6/90, 88 progressive, 2831m 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.

1%2%1%7%2%0%1%1%2%2%4%12%19%35%12%
progressivelateral/short% of his 238 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 10m, longest 68m
By zone — where the carry started → where it ended
46Outside → Inside
35Inside → Inside
133Outside → Outside
24Inside → Outside
First (115)Second (63)Third (31)Fourth (29)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: 6.08 dribbles attempted /90.

brighter band = more dribbles · own goal left, attacking →
INSIDE 34%
OUTSIDE 66%
Dribble location — 43 inside · 82 outside
Right Wing
14 · 11%
Right Half-Space
8 · 6%
Central
4 · 3%
Left Half-Space
31 · 25%
Left Wing
68 · 54%
Vision AI His carries cluster wide — a drifting playmaker.
18

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 →RWRHSCLHSLWRW5946%2724%1425%152%13%2RHS2124%552%1119%45%1C2921%610%345%1324%7LHS745%45%435%2630%2224%18LW2570%12%59%2326%6663%162FROM
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 final third → the left half-space in the final third — 15 progressive passes (17% of his progression) at 0.079 xT each. He moves it inside.

His progression is inward: 74% of progressive passes move the ball toward the middle versus 0% going wider — he cuts in rather than holding width.

11% of his passes are cross-field switches — he changes the point of attack often.

Quality behind the volume: 32 line-breaking passes and 23 final-third entries, 5.1 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%1%1%3%5%6%0%0%2%2%3%1%2%5%11%15%16%25%
completedincomplete616 passes · any zone → any zone · own goal left, attacking →
616
passes
71%
completed
176
lost
Vision AIIn line with his 71% season completion rate.
14

How does he progress play?

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

32
progressive · 1.6/90
23
final-third entries · 1.1/90
16
box entries · 0.78/90
19
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.
04

How does he create chances?

33 key passes (1.60/90), 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%5%5%5%5%18%50%
chance creation (22)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 (18)from the right (4)of 22 key passes landing in the final thirdattacking ↑ toward goal
12

Can he finish?

44 shots · 3.36 xG · 5 goals (+1.64 vs xG). Mostly right-footed. Circle size = xG.

shots  44
on target  25
goals  5
xG  3.36
xG on target  4.20
xG / shot  0.076
Where he shoots from — click an area of the box
13

Where does he become vulnerable?

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

167
attacking third (cheap)
58
middle third
23
own third (dangerous)
Vision AI 67% of losses are in the attacking third — he gambles where a turnover costs little.
Mistake danger (proxy): 2.12 danger-index/90 · 0.176 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
16

What is his passing profile?

616
passes attempted
39%
mostly backward
57%
mostly short
Direction
Forward
167 · 27%
Sideways
208 · 34%
Backward
241 · 39%
Length (completed)
Short (<15m)
252 · 57%
Medium
142 · 32%
Long (>30m)
46 · 10%
15

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.

0.800.450.390.340.340.33
own goal left, attacking →
Highest-value routes (xT)
0.80
Left Wing Mid third → Left Wing Att third
7 passes
0.45
Left Wing Att third → Left Wing Att third
3 passes
0.39
Left Wing Mid third → Right Half-Space Att third
1 passes
0.34
Left Wing Mid third → Left Half-Space Att third
1 passes
0.34
Left Half-Space Att third → Central Att third
1 passes · 1 to a shot
0.33
Right Wing Att third → Central Att third
1 passes · 1 to a shot
08

Where Does He Receive?

The zones where Mathys Tel 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
33%
Primary
Left Wing, Attacking third
19%
Secondary
Left Wing, Middle third
12%
Third
Left Half-Space, Attacking 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 Mathys Tel 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:
16406910812820333161336246108233841
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%1%1%3%5%6%0%0%2%2%3%1%2%5%11%15%16%25%
own goal left, attacking →
17

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.

33Key pass
16Cross
18Cutback
32Progressive
89Long ball
40Switch
By zone — where the pass started → where it landed
124Outside → Inside
91Inside → Inside
192Outside → Outside
33Inside → Outside
By direction
167Forward
241Backward
208Sideways
own goal left, attacking →
07

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 — 7 passes worth 0.80 xT.
Where do his chances come from?
Of 33 key passes, his busiest route is a delivery where he plays inside from the right wing toward the central in the final third — 9 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 half-space in the final third: 44% of his 16 touches there are lost (7 times).
22%2/9 lost—3 touches · too few—5 touches · too few23%3/13 lost24%8/34 lost6%1/17 lost9%1/11 lost38%6/16 lost26%10/38 lost20%25/126 lost28%14/50 lost44%7/16 lost6%1/16 lost43%27/63 lost35%69/199 lostRWRHSCLHSLWDEFMIDATT
05

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 238 ball-carries, his dominant tendency is that he drives along the touchline (56%). He carries from outside into the middle 46 times and out toward the touchline 24 — a genuine inside forward who cuts in with the ball.
06

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
12 · 5%
Progressive / key pass
31 · 13%
Simple pass
125 · 53%
No clean link
70 · 29%
Of 238 carries, 5% flow straight into a shot of his own, 13% 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.
11

Crosses & Cutbacks

16 crosses (0.78/90, 8 completed) and 18 cutbacks (0.87/90, 5 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.

20

How & where does he defend?

215 defensive actions across the season (10.4/90). 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 →
20
tackles · 60% won
6
interceptions · 0.3/90
87
recoveries · 4.2/90
14
clearances · 0.7/90
11
blocks
47
avg action height
48
won high (att 3rd)
102
middle third
65
own third
Vision AI A front-foot / high defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 113 proactive ball-wins (5.5/90), tackle success 60%. 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.

99
attacking-half actions · 4.81/90 — 68th of 149 attacking mids in the league by total count
19

Against Different Pressing Intensities

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Does Mathys Tel keep producing when the game is tight and the press is high? Tiers of ~12-13 matches — directional evidence, not proof.

press tier
xT /90
prog /90
key P /90
dribble%
High press (PPDA 4.1, 12m)
0.88
1.2
2.06
49%
Mid press (PPDA 5.4, 12m)
0.89
2.2
1.60
39%
Low press (PPDA 7.0, 13m)
0.78
1.5
1.25
40%
Team

Team context

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

21

Impact on the Team

Tottenham's output per match with Mathys Tel (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
0.83
1.50
-0.67
xG for /match
0.90
1.36
-0.46
goals against /match
1.00
2.00
-1.00
points /match
1.33
0.50
+0.83
22

His Share of the Team

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

category
share
him / team
goals
9%
5 / 54
successful take-ons
9%
53 / 619
box entries
6%
51 / 919
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

23

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)61%Half-space creator60%
Why Advanced playmaker (8) 61%: a weighted blend of progression 79 (weight 25%) + creativity 46 (weight 35%) + final-third threat 62 (weight 25%) + box threat 57 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
territory (wide vs central), carrying, dribbling
Strong
through-balls, progression
Average
crossing, transition, line-breaking, press resistance, final-third threat, box threat, creativity, ball-winning, receiving zones, build-up
Weak
defensive aggression, retention, passing directness
Unknown
aerial ability, marking, off-ball running — not in event data
Territory (wide vs central)
97
Carrying
93
Dribbling
89
Through-balls ~proxy
80
Progression
79
Crossing
68
Transition ~proxy
66
Line-breaking
64
Press resistance ~proxy
64
Final-third threat
62
Box threat
57
Creativity
46
Ball-winning
45
Receiving zones
43
Build-up
42
Defensive aggression
39
Retention
38
Passing directness
14
24

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 / 77 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.

Pedro Neto Chelsea · 174 cm / 78 kg
83%
Driven by: territory (wide vs central) (18%), carrying (16%), passing directness (12%). Different mechanism — Tel more via ball-winning; Neto more via receiving zones, line-breaking.
Samuel Chukwueze AC Milan · Serie A · 172 cm / 70 kg
77%
Driven by: territory (wide vs central) (19%), carrying (13%), progression (10%). Different mechanism — Tel more via dribbling, defensive aggression; Chukwueze more via build-up.
Savinho Man City · 179 cm / 66 kg
77%
Driven by: carrying (18%), territory (wide vs central) (17%), passing directness (14%). Different mechanism — Tel more via dribbling, defensive aggression; Savinho more via line-breaking, creativity.
Ander Barrenetxea Real Sociedad · La Liga · 175 cm / 74 kg
69%
Driven by: dribbling (20%), carrying (18%), territory (wide vs central) (14%). Different mechanism — Tel more via territory (wide vs central); Barrenetxea more via passing directness, ball-winning.
Wilson Odobert Tottenham 25/26 · 182 cm / 76 kg
68%
Driven by: dribbling (19%), carrying (13%), territory (wide vs central) (12%). Different mechanism — Tel more via defensive aggression, territory (wide vs central); Odobert more via retention, passing directness.
Kamaldeen Sulemana Atalanta · Serie A 25/26 · 175 cm / 70 kg
67%
Driven by: carrying (22%), passing directness (16%), dribbling (14%). Different mechanism — Tel more via territory (wide vs central), ball-winning; Sulemana more via receiving zones, retention.
25

Summary

Mathys Tel is an advanced playmaker (8) / half-space creator: 1.60 key passes /90, 1.6 progressive passes, 5 goals from 3.36 xG. A between-the-lines creator. [Off-ball movement into pockets needs tracking.]

Based on 37 matches (1852 minutes) this season — a reliable read. 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 creativity — 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.

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