العربيةSeason2025/262026 · this seasonAll seasons
Building the full report
Combining every season — this one is larger, give it a moment.
Vision AI ← BACK TO SEARCH
Player reportBundesliga 2025/26

Chema Andrés

Brighton
Ball-winning 6 (destroyer) DM
19.2 defensive actions/90
defensive midball-winning 6press resistancescreening
1780
minutes
31 apps
901
passes
84% completed
84%
pass completion
901 passes
61
progressive passes
3.1/90
380
defensive actions
19.2/90
78
tackles + interceptions
48% tackle win
96
recoveries
4.9/90
36
line-breaking passes
1.8/90
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
drop between the centre-backs — mostly in the middle third (67% of his 901 passes)
84% completion · 901× in 31/31 matches
↓
PROGRESS CENTRAL
break a line through the middle
3.1 prog/90 · 36× in 17/31 matches
↓
SCREEN / WIN BALL
protect the back four
8.8 ball-wins/90 · 174× in 31/31 matches
↓
RECYCLE / PROGRESS
keep it ticking, feed the final third
4.3 f3-entries/90 · 86× in 25/31 matches
Signature: Receive → Progress Central → Screen / Win Ball → Recycle / 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: escape pressure — 6× (low confidence, shown as a number only, no tactical conclusion drawn) — omitted from the signature rather than presented as one.
19

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 →
29
passes / match
19.2
def actions / 90
2–59
pass range (matches)
52
clearances
Pass range = his fewest and most passes in any single match this season (2 at the low end, 59 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.

11

How dangerous are his carries?

Real ball-carries

142 tracked carries (7.2/90, 27 progressive, 1178m 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.

2%6%4%3%7%27%20%3%4%8%13%5%
progressivelateral/short% of his 142 carries originating in each zone · own goal left, attacking →
Every carry, exact path — median 6m, longest 34m
By zone — where the carry started → where it ended
8Outside → Inside
127Inside → Inside
5Outside → Outside
2Inside → Outside
First (44)Second (37)Third (35)Fourth (26)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).

40
tackle duels
19
won
21
beaten · 52%
brighter band = more tackle duels · own goal left, attacking →
INSIDE 58%
OUTSIDE 42%
Tackle-duel location — 23 inside · 17 outside
Right Wing
14 · 35%
Right Half-Space
13 · 32%
Central
2 · 5%
Left Half-Space
8 · 20%
Left Wing
3 · 8%
Vision AI beaten in 21 of 40 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 6 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.

02

How does he build & move the ball?

How does he escape the first line?

14%
vertical passes
42×
3%
switches
9×
24%
carries
75×
59%
short circulation
185×
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 →RWRHSCLHSLWRW4869%3323%118%4RHS16729%4935%5929%486%101%1C3089%2722%6740%12422%677%23LHS1871%27%1425%4737%7029%54LW496%329%1465%32FROM
Rows normalised: each row sums to 100% of that lane's completed passes. Grey number = passes from that lane.

Primary route: central areas in the middle third → central areas in the middle third — 6 progressive passes (12% of his progression) at 0.009 xT each. He keeps it in the same lane.

His progression is inward: 44% of progressive passes move the ball toward the middle versus 6% going wider — he cuts in rather than holding width.

Only 5% of his passes switch play, so his threat is same-side — contain the flank he occupies and the route closes.

Quality behind the volume: 17 line-breaking passes and 86 final-third entries, 5.9 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%7%9%4%0%1%7%15%18%9%1%0%3%6%11%4%0%
completedincomplete901 passes · any zone → any zone · own goal left, attacking →
901
passes
84%
completed
142
lost
Vision AIIn line with his 84% season completion rate.
03

How does he progress play?

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

61
progressive · 3.1/90
86
final-third entries · 4.3/90
14
box entries · 0.71/90
13
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?

14 key passes (0.71/90), 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:
7%7%14%50%14%7%
chance creation (14)assist (0)% of the selected group's key passes originating in each zone
14

Can he finish?

19 shots · 1.69 xG · 4 goals (+2.31 vs xG). Mostly right-footed. Circle size = xG.

shots  19
on target  10
goals  4
xG  1.69
xG on target  2.34
xG / shot  0.089
Where he shoots from — click an area of the box
05

Where does he become vulnerable?

145 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.

23
attacking third (cheap)
86
middle third
36
own third (dangerous)
Vision AI 16% of losses are in the attacking third — a notable share happen deeper, which invites transitions.
Mistake danger (proxy): 2.86 danger-index/90 · 0.391 avg/turnover. Weights each loss by threat conceded at that location. True xT-conceded needs the opponent possession model; positional proxy.
06

What is his passing profile?

901
passes attempted
45%
mostly forward
57%
mostly short
Direction
Forward
408 · 45%
Sideways
306 · 34%
Backward
187 · 21%
Length (completed)
Short (<15m)
430 · 57%
Medium
305 · 40%
Long (>30m)
24 · 3%
07

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.

0.520.400.400.330.270.26
own goal left, attacking →
Highest-value routes (xT)
0.52
Central Mid third → Central Mid third
6 passes
0.40
Left Half-Space Mid third → Left Wing Att third
5 passes
0.40
Right Wing Mid third → Right Half-Space Att third
1 passes · 1 to a shot
0.33
Central Def third → Central Mid third
4 passes
0.27
Central Att third → Right Half-Space Att third
1 passes
0.26
Right Half-Space Mid third → Right Half-Space Mid third
3 passes
09

Where Does He Receive?

The zones where Chema Andrés 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
26%
Primary
Central, Middle third
17%
Secondary
Left Half-Space, Middle third
15%
Third
Right Half-Space, Middle third
These are the zones where he collected the ball most.
10

Where Does He Operate? — Every Zone

Every on-ball touch (pass, dribble, shot) binned into a 6×3 grid — raw counts of where Chema Andrés 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:
232541013328611351668421366786344
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%7%9%4%0%1%7%15%18%9%1%0%3%6%11%4%0%
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.

14Key pass
2Cross
7Cutback
61Progressive
36Long ball
16Switch
By zone — where the pass started → where it landed
32Outside → Inside
506Inside → Inside
65Outside → Outside
156Inside → Outside
By direction
408Forward
187Backward
306Sideways
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 central in the middle third — 6 passes worth 0.52 xT.
Where do his chances come from?
Of 14 key passes, his busiest route is a delivery where he plays straight through the central in the final third — 6 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 defensive third: 41% of his 32 touches there are lost (13 times).
38%5/13 lost41%13/32 lost11%5/46 lost24%8/33 lost36%4/11 lost22%8/37 lost16%22/138 lost12%29/236 lost13%20/155 lost13%5/38 lost0%0/11 lost9%3/35 lost18%13/73 lost21%7/34 lost0%0/9 lostRWRHSCLHSLWDEFMIDATT
13

Crosses & Cutbacks

2 crosses (0.10/90, 1 completed) and 7 cutbacks (0.35/90, 3 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.

15

How & where does he defend?

380 defensive actions across the season (19.2/90). 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 →
40
tackles · 48% won
38
interceptions · 1.9/90
96
recoveries · 4.9/90
52
clearances · 2.6/90
25
blocks
40
avg action height
52
won high (att 3rd)
177
middle third
151
own third
Vision AI A mid-block defender. He wins the ball mainly by stepping in — tackles, interceptions & recoveries outweigh clearances. 174 proactive ball-wins (8.8/90), tackle success 48%. He defends high, stepping out to intercept — suits a high line.
16

Can he play under pressure?

Split by how hard the opponent pressed (opponent PPDA — lower = more intense press). Can Chema Andrés 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 ~10-11 matches — directional evidence, not proof.

press tier
completion
prog /90
line-breaks /90
xT /90
High press (PPDA 4.6, 10m)
79%
2.0
2.0
0.69
Mid press (PPDA 6.2, 10m)
83%
3.6
2.6
0.95
Low press (PPDA 8.5, 11m)
88%
3.5
1.0
1.02
Team

Team context

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

17

Impact on the Team

Brighton's output per match with Chema Andrés (1 matches) versus without him (6 matches). Insufficient evidence — the without-sample is only 6 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 (1)
WITHOUT (6)
Δ
goals against /match
5.00
1.33
+3.67
points /match
0.00
1.00
-1.00
goals for /match
1.00
1.50
-0.50
xG for /match
1.13
1.86
-0.73
18

His Share of the Team

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

category
share
him / team
interceptions
9%
32 / 369
goals
5%
4 / 80
tackles
5%
30 / 666
Recruitment

Style and verdict

Style profile, closest comparables, and the summary.

20

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.

Ball-winning 677%Tempo controller68%Deep-lying playmaker62%
Why Ball-winning 6 77%: a weighted blend of ball-winning 73 (weight 40%) + defensive aggression 76 (weight 30%) + retention 78 (weight 15%) + progression 46 (weight 15%). The score reflects how distinctively his profile SHAPE matches this archetype vs his peers.
Elite
receiving zones
Strong
passing directness, final-third threat, retention, defensive aggression, ball-winning, press resistance
Average
box threat, transition, creativity, build-up, through-balls, dribbling, progression, crossing, line-breaking
Weak
carrying, territory (wide vs central)
Unknown
aerial ability, marking, off-ball running — not in event data
Receiving zones
94
Passing directness
79
Final-third threat
78
Retention
78
Defensive aggression
76
Ball-winning
73
Press resistance ~proxy
71
Box threat
70
Transition ~proxy
65
Creativity
64
Build-up
52
Through-balls ~proxy
50
Dribbling
47
Progression
46
Crossing
43
Line-breaking
42
Carrying
37
Territory (wide vs central)
4
21

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: 190 cm / 82 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 Bundesliga, La Liga, Ligue 1, 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.

Mamadou Sangaré Brentford · Premier League · 181 cm / 72 kg
72%
Driven by: defensive aggression (17%), receiving zones (15%), ball-winning (15%). Different mechanism — Sangaré more via dribbling, line-breaking.
Nico González Newcastle · Premier League · 189 cm / 88 kg
71%
Driven by: receiving zones (17%), territory (wide vs central) (13%), defensive aggression (12%). Different mechanism — Andres more via box threat; González more via carrying, dribbling.
Pape Diop Strasbourg · Ligue 1 · 182 cm
69%
Driven by: receiving zones (22%), ball-winning (18%), territory (wide vs central) (17%). Different mechanism — Andres more via passing directness, press resistance; Diop more via line-breaking.
Aurélien Tchouaméni Real Madrid · La Liga · 187 cm / 81 kg
69%
Driven by: territory (wide vs central) (17%), receiving zones (16%), passing directness (10%). Different mechanism — Andres more via dribbling, press resistance; Tchouaméni more via progression, line-breaking.
Jobe Bellingham Borussia Dortmund · 188 cm / 73 kg
66%
Driven by: territory (wide vs central) (22%), receiving zones (20%), defensive aggression (12%). Different mechanism — Andres more via passing directness, through-balls; Bellingham more via carrying, line-breaking.
Morten Hjulmand Atletico · La Liga · 185 cm / 77 kg
62%
Driven by: receiving zones (20%), territory (wide vs central) (17%), retention (14%). Different mechanism — Andres more via through-balls, passing directness; Hjulmand more via line-breaking, build-up.
22

Summary

Chema Andrés is a ball-winning 6 / tempo controller: 84% completion, 36 line-breaks and 3.1 progressive passes /90, resisting pressure with 50% dribble success. A central controller. [Off-ball screening position and scanning need tracking data.]

Based on 31 matches (1780 minutes) this season — a reliable read. He profiles as a ball-winning 6 / tempo controller — 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 ball-winning 6 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