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Team reportLigue 1 2026

Rennes

A balanced-territory side, aggressive high-press out of possession, with a high-volume attack. Currently #2 of 18 on 16 points (5-1-2, 18:14). Tactical profile below is built from 8 matches of ball-by-ball event data, contextualised against the league.

balanced-territoryaggressive high-presshigh-volume attack
W
W
W
W
L
W
L
D
W
W
W
L
W
L
W
16
points
#2 of 18 · 8 games
18:14
goals
+4 GD
5-1-2
record
W-D-L
2.00
points/game
#2 in the league
1.81
xG for/game
rank #3
1.77
xG against/game
rank #17
#5
press rank
of 18 · most aggressive
50%
field tilt
#10
Rennes
League average
Expected goals for / game
1.811.41
Expected goals against / game
1.771.41
Field tilt
50%50%
Pass retention
82%83%
Overview

The team

Who they are and how the season went.

Who Are They? — Identity

The question
In one read, what kind of team is Rennes and how good was the season?
Read. Rennes currently sit #2 of 18 on 16 points (5W-1D-2L, 2.00 pts/game), scoring 18 and conceding 14 for a goal difference of +4. On the ball they are a balanced-territory team (50% field tilt, #10 in the league); off it they defend with a aggressive high-press (#5 of 18 for press intensity). Across the 8 matches of event data, they create 1.81 xG/game (#3) and concede 1.77 (#17), a net of +0.04 xG/game — the underlying performance matches the actual goal difference.

Season Context — the league table

The question
Where did Rennes actually finish, and against whom?

The authoritative final table (full season), centred on Rennes.

#teamPWDLGFGAGDPts
1PSG8521169+717
2Rennes85121814+416
3Lille8431116+515
4Monaco8431117+415
5Lyon8422137+614

Match Momentum — when they create and concede danger

The question
Across a whole game, which periods does Rennes actually dominate for chances — and which periods hurt them?

Net xG (created minus conceded) in each 15-minute window, summed across the whole season's matches — above the line is time they dominate for chances, below is time it hurts them. Real on-clock shot timing.

dominant (net xG for)conceding (net xG against)
even0-15'16-30'31-45'46-60'61-75'76-90+'+3.35-1.86
Vision AI Model Insight
Rennes tend to come alive after the break — first-half net xG -1.39, second-half +1.73. Their strongest period is 76-90+' (net +3.35 xG); their most dangerous period to face is 46-60' (net -1.86 xG against them).

xG Race — the season, match by match

Expected goals piling up over 8 matches: Rennes against what their opponents created. A line pulling away upwards is a side creating more than it gives away; the gap at the end is the season’s balance (+0.3 xG). Hover a point for that match.

05101614.514.1PSG (H) 2-2 · xG 0.66 to 1.53Le Mans (H) 3-2 · xG 2.93 to 2.51Angers (A) 2-1 · xG 1.52 to 1.87Marseille (H) 1-0 · xG 1.74 to 1.07Lyon (A) 0-4 · xG 1.13 to 2.31Auxerre (H) 4-1 · xG 1.98 to 0.76Paris FC (A) 3-4 · xG 3.19 to 3.21Strasbourg (H) 3-0 · xG 1.34 to 0.87M1M2M3M4M5M6M7M8
RennesOpponents against Rennes

Tactical DNA

The football question
In five genes, what is Rennes's footballing identity?

Each gene is a 0–100 score — the team's league percentile across the metrics that define that phase of play. It distils the whole report into an identity fingerprint: the taller the gene, the more that trait defines them.

39
Build-Up
possession control from the back
78
Progression
moving the ball upfield with threat
81
Creation
manufacturing chances
58
Press
winning the ball high & hard
6
Solidity
resisting the opponent's threat
Genetic identity
Rennes are defined most by their Creation DNA (81/100 · strong at manufacturing chances), and least by their Solidity DNA (6/100). Percentiles vs the 18 teams in the league.

The Playstyle Wheel

Fifteen style metrics across five domains — Possess, Disrupt, Finish, Press, Defend — each a percentile against the rest of the league. Metrics marked ~proxy use the closest available event-data signal where the standard definition needs data this feed doesn't carry (explicit pressure events, offside/keeper-sweep incidents).

Possess68Disrupt50Finish47Press58Defend55
Possess
Deep buildup
70%
Possession
70%
Field tilt
65%
Disrupt
Central progression ~proxy
45%
Dribble tendency
25%
Progressive passes
80%
Finish
Final-third patience
35%
Shot quality
40%
Open-play xG
65%
Press
Forward press ~proxy
50%
High regains
65%
Pressing efficiency ~proxy
60%
Defend
Def-mid press ~proxy
55%
High line ~proxy
40%
PAdj defensive actions
70%
Rennes is defined most by Possess (68% in the league) and weakest on Finish (47%). Percentiles vs the 20 teams in the league this season.
In possession

In possession

How they keep the ball, build up, progress, create and finish, and where their attacks die.

Keeping the ball6 sections

Field Tilt — Territorial Control

The question
How much of the pitch does Rennes actually control, relative to the rest of the league?

Field tilt = share of final-third touches between the two sides across Rennes's matches, the standard proxy for territorial dominance. Plotted against points per game for every side in the league — the real question isn't just who controls territory, it's whether that control actually converts into results. Dashed lines mark the league average on each axis; Rennes highlighted. Hover any dot for the team.

PSG: 74% tilt, 2.12 pts/gRennes: 50% tilt, 2.00 pts/gLille: 44% tilt, 1.88 pts/gMonaco: 52% tilt, 1.88 pts/gLyon: 49% tilt, 1.75 pts/gParis FC: 46% tilt, 1.75 pts/gLens: 55% tilt, 1.62 pts/gLorient: 40% tilt, 1.50 pts/gMarseille: 58% tilt, 1.50 pts/gNice: 53% tilt, 1.38 pts/gToulouse: 51% tilt, 1.25 pts/gAuxerre: 52% tilt, 1.25 pts/gBrest: 44% tilt, 1.12 pts/gAngers: 43% tilt, 1.00 pts/gStrasbourg: 42% tilt, 0.88 pts/gLe Mans: 41% tilt, 0.88 pts/gTroyes: 54% tilt, 0.62 pts/gLe Havre: 51% tilt, 0.25 pts/gRennes40%52%63%74%0.20.91.52.1FIELD TILT %POINTS / GAME
Vision AI Model Insight
Rennes post 50% field tilt, ranking #10 of 18 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 2.00 points/game sits above the league-average return — a real disconnect: their territorial control isn't showing up on the scoreboard the way it should.

Where the time goes — how long each phase lasts

The question
When Rennes has the ball, how much of that time is spent building, progressing and creating?

The share of Rennes's time on the ball spent in each phase of play, in the order the phases happen. A phase is where the ball is on the pitch (own third, middle third, final third); a transition or a set piece skips the build-up and is counted on its own.

Build-up: 28.2% of the time on the ball28%Progression: 45.2% of the time on the ball45%Chance creation: 23.9% of the time on the ball24%Attacking transition: 2.8% of the time on the ball45%PROGRESSION
PhaseShare of the time
Build-up28.2%
Progression45.2%
Chance creation23.9%
Attacking transition2.8%
Vision AI Model Insight
Progression is where Rennes spends most of its time on the ball (45% of its time on the ball).

Passing Network

The question
Who actually plays with whom — the real on-pitch connections, not just average positions?

Every pass linked to its likely receiver (the next same-team touch), aggregated into player-pair combinations at each player's average position. Line width = how often the pair combines; colour = threat generated per pass (blue low → red high). Hover a line for the pair, or click a player to isolate their connections.

Brice Samba ↔ Charlie Cresswell: 108 passes, -0.3 combined xTCharlie Cresswell ↔ Anthony Rouault: 91 passes, -0.3 combined xTPrzemyslaw Frankowski ↔ Charlie Cresswell: 88 passes, -0.8 combined xTValentin Rongier ↔ Charlie Cresswell: 79 passes, -0.2 combined xTValentin Rongier ↔ Przemyslaw Frankowski: 68 passes, 0.2 combined xTValentin Rongier ↔ Aboubakar Nagida: 63 passes, 0.0 combined xTAnthony Rouault ↔ Aboubakar Nagida: 62 passes, -0.2 combined xTAdrien Thomasson ↔ Valentin Rongier: 61 passes, 0.7 combined xTMahdi Camara ↔ Aboubakar Nagida: 61 passes, 0.4 combined xTAdrien Thomasson ↔ Przemyslaw Frankowski: 59 passes, 0.6 combined xTBrice Samba ↔ Anthony Rouault: 56 passes, -0.2 combined xTValentin Rongier ↔ Mahdi Camara: 56 passes, 0.4 combined xTValentin Rongier ↔ Anthony Rouault: 46 passes, -0.2 combined xTAdrien Thomasson ↔ Charlie Cresswell: 42 passes, -0.5 combined xTValentin Rongier ↔ Quentin Merlin: 40 passes, 0.5 combined xTMahdi Camara ↔ Anthony Rouault: 38 passes, 0.2 combined xTValentin Rongier ↔ Sebastian Szymanski: 37 passes, 0.4 combined xTAdrien Thomasson ↔ Mahdi Camara: 34 passes, 0.5 combined xTValentin Rongier ↔ Bryan Reynolds: 34 passes, 0.5 combined xTBryan Reynolds ↔ Charlie Cresswell: 34 passes, -0.2 combined xTMousa Al Tamari ↔ Aboubakar Nagida: 34 passes, 1.1 combined xTSebastian Szymanski ↔ Charlie Cresswell: 33 passes, 0.0 combined xTMahdi Camara ↔ Charlie Cresswell: 32 passes, 0.1 combined xTIssa Soumaré ↔ Aboubakar Nagida: 32 passes, 1.1 combined xTAdrien Thomasson — isolate this player's connectionsThomassonValentin Rongier — isolate this player's connectionsRongierLudovic Blas — isolate this player's connectionsBlasPrzemyslaw Frankowski — isolate this player's connectionsFrankowskiMousa Al Tamari — isolate this player's connectionsTamariCharlie Cresswell — isolate this player's connectionsCresswellAboubakar Nagida — isolate this player's connectionsNagidaEstéban Lepaul — isolate this player's connectionsLepaulBrice Samba — isolate this player's connectionsSambaMahdi Camara — isolate this player's connectionsCamaraSebastian Szymanski — isolate this player's connectionsSzymanskiEliezer Mayenda — isolate this player's connectionsMayendaIssa Soumaré — isolate this player's connectionsSoumaréQuentin Merlin — isolate this player's connectionsMerlinAnthony Rouault — isolate this player's connectionsRouaultBryan Reynolds — isolate this player's connectionsReynolds
width = passes between the paircolour = xT per pass: low → high

Top 10 combinations

Samba ↔ Cresswell
108p · -0.3xT
Cresswell ↔ Rouault
91p · -0.3xT
Frankowski ↔ Cresswell
88p · -0.8xT
Rongier ↔ Cresswell
79p · -0.2xT
Rongier ↔ Frankowski
68p · 0.2xT
Rongier ↔ Nagida
63p · 0.0xT
Rouault ↔ Nagida
62p · -0.2xT
Thomasson ↔ Rongier
61p · 0.7xT
Camara ↔ Nagida
61p · 0.4xT
Thomasson ↔ Frankowski
59p · 0.6xT
Vision AI Model Insight
Busiest connection: Brice Samba ↔ Charlie Cresswell (108 passes). Most dangerous per pass: Issa Soumaré ↔ Aboubakar Nagida (0.03 xT/pass over 32 passes) — the combination that hurts opponents most when it fires, not just the one used most.

Touch Density — where Rennes had the ball

Every touch across 72 matches. Brighter means more touches.

Which Zones Do They Attack Through?

The question
Across the whole pitch, where does Rennes actually do its on-ball work?

Passes on one map, carries (the ball travelling with a player) on the other. Each is binned into the 15 pitch zones (three thirds × five vertical lanes) and shaded by its share of that kind of action; the arrows are the real actions.

Passes
the ball moved by a pass
4157
ACTIONS
5%6%10%6%5%9%11%9%9%9%6%4%2%4%6%PASSES
Carries
the ball moved with a player
960
ACTIONS
4%9%7%5%3%12%9%9%10%9%7%3%2%2%8%CARRIES
Vision AI Model Insight
Their single busiest zone is the right half-space of the middle third (10.3% of all actions). 60% of actions run through the inside lanes (centre + both half-spaces) versus 40% down the two wings — an inside-dominant, half-space build. By third: 30% defensive, 47% middle, 22% attacking.

Attack Sides

Which channel they attacked through this season: the share of every action made in the opponent’s half, down the left, through the middle and down the right. Rennes leaned on their right (41%). The bars under the pitch put the league’s share beside theirs.

41%Left side19%Middle41%Right sideATTACKING →
Rennes
41%19%41%
League
38%22%40%

Final-Third Entries

Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. Rennes made 321 this season (40.1 a match); 30% came into the left wing. Longer, bolder arrows mean more entries. Entries by carrying the ball in count as well as completed passes; dribbles are not counted.

Left wing: 96 entries (30%)9630%LEFT WINGLeft half-space: 43 entries (13%)4313%LEFT HALF-SPACECentre: 34 entries (11%)3411%CENTRERight half-space: 52 entries (16%)5216%RIGHT HALF-SPACERight wing: 96 entries (30%)9630%RIGHT WINGATTACKING ↑
ChannelEntriesPer matchShareLeague share
Left wing9612.030%30%
Left half-space435.413%13%
Centre344.211%11%
Right half-space526.516%14%
Right wing9612.030%32%
Build-up2 sections

Build-Up — the pass map

The football question
How does Rennes progress possession from defence into attack — and who runs it?

Build-up passes grouped into 5 real categories — not the old zone grid, not raw individual lines: CB (passer is a centre-back), Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top passer.

1274build-up passes attempted
84%completed
28%reach the middle third
1%go long into the final third

Pass types

492CB · 46%
80Long Wide · 7%
6Long Central · 1%
398Wide → FB · 37%
100Central · 9%

Sequence success — build-up

51build-up sequences this season
16%succeed — reach the next third or a shot
37%turned over with nothing to show
CB492 · 46%
right: 268 passes, most from Cresswell268left: 224 passes, most from Rouault224
Long Wide80 · 7%
left: 51 passes, most from Samba51right: 29 passes, most from Samba29
Long Central6 · 1%
left: 5 passes, most from Samba5
Wide → FB398 · 37%
left: 218 passes, most from Samba218right: 180 passes, most from Samba180
Central100 · 9%
left: 57 passes, most from Samba57right: 43 passes, most from Samba43
◆ Vision AI Insight
Rennes build predominantly down the left, with Samba as the fulcrum (222 build-up passes). Only 30% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a possession-controlling side that circulates patiently in midfield before progressing. Their single most-repeated pattern is C def → RHS def (82×).

Pass Explorer

Every pass of Rennes’s last 8 matches as an arrow, theirs first and the opponents’ with other team, each side attacking left to right (solid = completed, dashed grey = failed). Eight families per team — click any map to open it wide, then filter by channel or third, from one to another (or click a cell of the flow grids), by outcome, half, minute and passer. Channels: right wing, right half-space, centre, left half-space, left wing.

Progression4 sections

How They Progress — the mechanism

Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 405 progressive passes across 8 matches (50.6/game).

Origin lane

Right wing
31%
Right half-space
13%
Central
12%
Left half-space
12%
Left wing
32%
Progression is central-dominant: 44% right side · 12% central · 44% left.

Who generates it

Przemyslaw Frankowski
61 · 15%
Aboubakar Nagida
41 · 10%
Adrien Thomasson
41 · 10%
Charlie Cresswell
38 · 9%
Quentin Merlin
29 · 7%
Top two — Przemyslaw Frankowski & Aboubakar Nagida — account for 25% of all progression.
PROGRESSION
50.6 prog passes/game
mostly central
→
PENETRATION
26% reach final third
21% reach the box
→
THREAT
the other 74% is recycled
progress ≠ danger
What came of it. 26% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 25% of the progression ran through two players, mostly down the central side.

Which lanes actually create the threat

Share of passes played from each lane against its share of the threat (xT) they add. Efficient = more threat than volume, sterile = lots of the ball, little damage.

Per lane — volume vs threat
Right wingefficient
Right half-spacebalanced
Centralbalanced
Left half-spacesterile
Left wingefficient

Progression — the pass map

The football question
Once Rennes have the ball in midfield, how do they actually break into the final third — and who carries that job?

Progression passes grouped into 5 real categories: CB, Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top passer.

1948progression passes attempted
85%completed
14%break into the final third
12%go backward into the defensive third

Pass types

614CB · 37%
54Long Wide · 3%
6Long Central · 0%
814Wide → FB · 49%
176Central · 11%

Sequence success — progression

81progression sequences this season
41%succeed — reach the next third or a shot
40%turned over with nothing to show
CB614 · 37%
right: 377 passes, most from Cresswell377left: 237 passes, most from Rouault237
Long Wide54 · 3%
left: 33 passes, most from Blas33right: 21 passes, most from Rongier21
Long Central6 · 0%
right: 5 passes, most from Rongier5
Wide → FB814 · 49%
left: 453 passes, most from Nagida453right: 361 passes, most from Rongier361
Central176 · 11%
left: 103 passes, most from Rongier103right: 73 passes, most from Rongier73
◆ Vision AI Insight
Rennes progress predominantly down the right, with Rongier the busiest midfield outlet (258 progression passes). Only 14% of passes that start in midfield actually break the final-third line — the rest (74%) is recycled back into midfield or (12%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is RHS mid → RW mid (97×) — press that lane and midfield progression stalls.

Decision Quality — not all completed passes are equal

A 90% pass completion can hide a sideways habit. Grading every pass by the threat it adds separates value creation from safe circulation.

Excellent (high xT gain)
14%
Progressive
2%
Neutral / sideways
48%
Safe / backward
37%
15% of passes are progressive-or-better; the remaining 85% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.

Carries Map — progressive ball-carries, squad-wide

The question
Where does Rennes actually progress the ball with their feet, not a pass?

200 progressive carries this season across the whole squad (21% of 960 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 14m, longest 60m. Most active carrier: Frankowski (24). Filter to one player below.

First (64)Second (59)Third (46)Fourth (31)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Chance creation4 sections

Chance creation — how the shots come

The question
Where do Rennes's chances actually come from?

Every shot sorted twice. First by the kind of attack: an attacking transition (the shot came within 15 seconds of winning the ball), a settled attack (open play after the team had the ball), or a set piece. Then by how it was set up: a cross, a cut-back, a long ball, a pass into the box, or no pass at all (the player created it himself). So a cut-back from an attacking transition is counted apart from a cut-back in a settled attack.

129shots
14.5xG
0.11xG per shot
10big chances (0.3+ xG)
17goals
#3key passes / game in the league
#2box entries / game in the league
Attacking transition: 39 shots (30%)30%39Settled attack: 63 shots (49%)49%63Set piece: 27 shots (21%)21%27129SHOTS
Kind of attack, then how the shot was set upShotsGoalsxGxG / shot
Attacking transition 30% of shots3954.630.12
Cross200.330.16
Cut-back100.220.22
Long ball200.270.13
Pass into the box / short pass2553.300.13
Own creation (carry, dribble, rebound)900.510.06
Settled attack 49% of shots6375.190.08
Cross1111.410.13
Cut-back920.970.11
Long ball410.540.13
Pass into the box / short pass2731.660.06
Own creation (carry, dribble, rebound)1200.620.05
Set piece 21% of shots2754.670.17
Corner2211.470.07
Free kick100.020.02
Penalty443.180.79

Every attempt to create — and what came of it

Every pass into the box, every cut-back and every pass before a shot. Red led to a shot, gold to a goal; grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball. Filter by outcome, type or player; tap an arrow for the detail.

Who sets the shots up

PlayerSet-upsxG createdGoals
Ludovic Blas101.662
Przemyslaw Frankowski91.242
Mousa Al Tamari70.971
Adrien Thomasson110.892
Valentin Rongier90.810

Who takes them

PlayerShotsxGGoals
Estéban Lepaul285.327
Ludovic Blas141.280
Mahdi Camara81.070
Adrien Thomasson51.002
Boulaye Dia50.873
Vision AI Model Insight
The biggest source of Rennes's chances, by xG, is settled attack (5.2 of 14.5 xG, 63 of 129 shots), mostly pass into the box / short pass. 39 of the 129 shots (30%) came within 15 seconds of winning the ball. 27 of the 129 shots came from set pieces; 17 goals from 14.5 xG (+2.5).

Chance Creation — the pass map

The football question
How does Rennes consistently create dangerous chances — from which zones, and who creates them?

Key passes (the pass immediately before a shot) grouped into 5 real categories: CB, Wide→FB, Central, Long Wide, Long Central. Each gets its own panel below, so nothing competes for attention. Arrow width = volume, labelled with the exact count; hover for the top creator.

Pass types

10CB · 11%
5Long Wide · 5%
13Long Central · 14%
27Wide → FB · 29%
37Central · 40%

Sequence success — final-third

67final-third sequences this season
33%succeed — produce a shot
39%turned over with nothing to show

Danger Funnel — which service carries threat

Every key pass pooled by where it was played FROM, then drawn with its arrow width set by total xT rather than by count. A zone that produces a lot of cheap balls shrinks; one that produces a few decisive ones dominates. Where this disagrees with the volume map, the volume map is the misleading one.

0 key passes shown● low threat● mid● high threatarrow width = total xT, not count
CB10 · 11%
right: 8 passes, most from Frankowski8left: 2 passes, most from Frankowski2
Long Wide5 · 5%
right: 4 passes, most from Blas4
Long Central13 · 14%
right: 8 passes, most from Szymanski8left: 5 passes, most from Thomasson5
Wide → FB27 · 29%
right: 17 passes, most from Rongier17left: 10 passes, most from Thomasson10
Central37 · 40%
left: 22 passes, most from Nagida22right: 15 passes, most from Thomasson15

Who creates — volume × threat

16Thomasson
11Blas
8Tamari
8Frankowski
8Rongier
7Nagida
6Lepaul
92key passes #3 of 18
15.0box entries/game #2 of 18
31.5final-3rd entries/game #11 of 18
1.81xG/game #3 of 18
17goals #1 of 18
+2.5finishing vs xG #2 of 18
◆ Vision AI Insight
Rennes lean right — 41% of their key passes come from that flank and its half-space (38 of 92), most often from Frankowski (7). They funnel chances into the c of the final third, most often via LW att → C att (13 key passes, most often from Nagida). Thomasson is the primary source overall. They generate 1.81 xG a game and finish it clinical — they beat their xG, led by Estéban Lepaul (7G), Sebastian Szymanski (3G), Boulaye Dia (3G).

Crosses & Cutbacks — squad-wide

The question
How does Rennes deliver into the box from wide areas, and what comes of it?

118 crosses: 41 found a team-mate (35%), 14 led to a shot (12%). 42 cut-backs: 20 found a team-mate (48%), 10 led to a shot (24%). A cross starts wide and is aimed into the box; a cut-back starts near the byline and is squared back. Grey ones were tried but no shot came: solid found a team-mate, dashed lost the ball.

Crosses by Territory

The question
Which part of the final third does Rennes actually cross from?

118 crosses this season (the same crosses as the map above), split into fifteen territories — five channels (both wings, both half-spaces and the centre) by three depths from the halfway line to the byline. 32% come from one territory, the byline left wing; 4 come from the half-spaces and 0 from the centre.

deep right wing: 12 crosses (10%)10%12deep right half-space: 0 crosses (0%)deep centre: 0 crosses (0%)deep left half-space: 0 crosses (0%)deep left wing: 4 crosses (3%)3%4advanced right wing: 21 crosses (18%)18%21advanced right half-space: 0 crosses (0%)advanced centre: 0 crosses (0%)advanced left half-space: 2 crosses (2%)2%2advanced left wing: 22 crosses (19%)19%22byline right wing: 17 crosses (14%)14%17byline right half-space: 1 crosses (1%)1%1byline centre: 0 crosses (0%)byline left half-space: 1 crosses (1%)1%1byline left wing: 38 crosses (32%)32%38
TerritoryCrossesShareLed to a shot
byline · left wing3832%4
advanced · left wing2219%3
advanced · right wing2118%3
byline · right wing1714%1
deep · right wing1210%2
deep · left wing43%0
advanced · left half-space22%0
byline · right half-space11%1
byline · left half-space11%0
Finishing3 sections

Shot Map

129 shots for 14.5 xG (1.81/game, #3 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

High-volume attack. 16.1 shots/game at 0.112 xG/shot. Box entries 15/game (#2). Threat created 11.5 xT/game (#6).

Goal Sequences

The move behind each of Rennes’s 18 goals this season, from the moment they got the ball to the finish. Pick a goal from the list, then step through it or press Play: numbered circles are passes and touches, dotted lines are carries (the ball travelling with a player), dashed grey is a pass that was lost, the star is the shot.

Each goal’s possession, rebuilt from the raw event feed — 18 goals traced.

How Do They Score?

The question
Where do the goals actually come from — open play, dead balls, which foot?

Every goal Rennes scored across the loaded matches, broken down by how it was created and finished.

By situation

Open play
12 · 71%
Set pieces
1 · 6%
Penalties
4 · 24%

By finish

Right foot
12 · 71%
Left foot
4 · 24%
Header
1 · 6%
Vision AI Model Insight
17 goals scored. 71% come in open play; set pieces add 6%. Open play is clearly their main route to goal.
When they lose it1 section

Ball-Loss Map — where attacks die

Every turnover has a location and a cause. This is a rate, not a raw count — the share of pass attempts from each zone that end in a turnover, so a zone they simply play through more often doesn't automatically look riskier. Grey cells are real zones with too few attempts to trust a rate.

Loss rate by zone

55 of 192 pass attempts lost here (29%).29%55/192Cresswell37 of 230 pass attempts lost here (16%).16%37/230Cresswell44 of 415 pass attempts lost here (11%).11%44/415Samba21 of 246 pass attempts lost here (9%).9%21/246Samba41 of 191 pass attempts lost here (21%).21%41/191Nagida69 of 392 pass attempts lost here (18%).18%69/392Frankowski57 of 437 pass attempts lost here (13%).13%57/437Cresswell53 of 378 pass attempts lost here (14%).14%53/378Cresswell45 of 358 pass attempts lost here (13%).13%45/358Rouault60 of 383 pass attempts lost here (16%).16%60/383Nagida48 of 254 pass attempts lost here (19%).19%48/254Frankowski38 of 155 pass attempts lost here (25%).25%38/155Tamari19 of 103 pass attempts lost here (18%).18%19/103Thomasson57 of 169 pass attempts lost here (34%).34%57/169Nagida84 of 254 pass attempts lost here (33%).33%84/254Thomassonattacking →

How they lose it

Incomplete pass — attacking third
246
Failed forward pass
160
Failed take-on
79
Lost in the defensive third
198
Their weakest zone is the left half-space in the attacking third: 34% of 169 pass attempts there are lost (57 times). Separately, 34% of all losses happen in the attacking third — a fair share happen deeper, which invites transitions.
Out of possession

Out of possession

How they press, where they win the ball back, and how they concede.

Pressing2 sections

Pressing — the full picture

The football question
How hard does Rennes press, where, and does it actually work — beyond a single PPDA number?

A composite Pressing Index built from four event-derived dimensions, each ranked against the league. Not one metric — intensity, height, effectiveness and opponent disruption together. The pitch shows every defensive action (the only five events this data records); the white line is the average height that feeds the score. Toggle by action type below, hover any dot for the player.

57
Pressing Index
/100 · average
Intensity50
PPDA, high-press share, high-zone actions
Height50
how high up the pitch they defend
Effectiveness61
high recoveries & high-regain share
Disruption69
opponent completion & progression allowed

Every defensive action & where it happens

Where they win the ball back — by lane

RW
18%
RHS
20%
C
20%
LHS
19%
LW
23%
By third (high / mid / low regain)
Def 48%
Mid 37%
Att 15%
Read
Ranked #5 of 18 for press intensity, this is a high press. 52% of defensive actions happen in the middle & attacking thirds, at an average height of 38. Of recoveries, 59% are won high up the pitch.

Every pressing metric, ranked in the league

metricvaluerankmeaning
PPDA (opp passes per def action)—#5/18lower = more intense; rank is what matters
Defensive actions / game162#6/18
High-press share22%#10/18def actions won high up
Defensive-action height (0–100)38.5#9/18avg pitch height of actions
High recoveries / game23.1#11/18ball won in mid+att third
High-recovery share59%#3/18share of recoveries won high
Opponent completion allowed81%#3/18lower = more disruptive
Opponent progressive allowed8.4%#8/18of opp passes, lower = better
Transition timing
This source carries per-event timestamps, so genuine transition metrics — counter-attack shots, press→shot conversions, time-to-recover — are measured; see the dedicated Transitions section below.

How long they keep it — passes and seconds until the ball is won

The question
Once the opponent has the ball, how many passes and how many seconds pass before Rennes win it back with a defensive action?

Counted over the 248 opposition possessions that Rennes ended with a tackle, interception, recovery or challenge. Fewer passes and seconds means the ball is won quickly (a press); more means the opponent is allowed to play before Rennes step in. Rennes win it after 5.6 opponent passes in the first half-hour and after 4.7 after the hour mark (sooner).

PASSES THEY GET
5.1passes
median 4 · before Rennes win it
TIME THEY KEEP IT
15sec
median 8s · 31.0 wins per game
How many passes the opponent got in before the ball was won
38%
31%
15%
17%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
5.9
18s
15–30′
5.4
17s
30–45+′
6.4
20s
45–60′
3.8
11s
60–75′
3.9
10s
75–90+′
5.1
14s
average passesaverage seconds

Attitude in each third

Every other style number here says how much Rennes does. This says how: wide or central, short or long, patient or direct. Bars are standard deviations from the league mean for passes played from that third; a solid bar marks a dimension where Rennes are genuinely unusual, and a verdict is only written where something clears 0.85 sd — a side that is ordinary in a third is told so rather than given a label for average play.

Build-up (own third) 1,274 passes

nothing unusual in this zone

Width of use+0.4121.85
Wide-channel share+0.010.31
Side bias+0.010.21
Pass length-0.7719.91
Long-ball share-0.420.19
Forward gain per pass-0.638.74
Backward-pass share+0.280.21
Deep-pass share-0.610.23
Completion+0.560.84
Seconds between passes-0.333.12
Side used

left 30% · central 40% · right 30%

Progression (middle third) 1,948 passes

nothing unusual in this zone

Width of use+0.3626.32
Wide-channel share+0.250.42
Side bias-0.20-0.72
Pass length-0.7016.25
Long-ball share-0.440.08
Forward gain per pass+0.053.68
Backward-pass share-0.090.33
Deep-pass share-0.240.15
Completion+0.070.85
Seconds between passes-0.443.00
Side used

left 36% · central 26% · right 39%

Final third 935 passes

nothing unusual in this zone

Width of use-0.3830.68
Wide-channel share-0.340.56
Side bias+0.190.85
Pass length-0.4214.81
Long-ball share-0.520.08
Forward gain per pass-0.410.49
Backward-pass share+0.380.41
Deep-pass share-0.210.08
Completion+0.430.73
Seconds between passes-0.363.12
Side used

left 43% · central 16% · right 41%

Reference measured across roughly 3,500 match-teams in this competition, per third, so the comparison is with Rennes's own league. The means behave as football should: width of use grows 21.0 → 25.6 → 31.6 going forward, pass length shrinks 22.7 → 17.2 → 15.5 m, and completion is hardest in the final third. Tempo is integer-resolution because the feed records whole seconds.

Transitions1 section

Transitions — attacking & defensive

The question
When Rennes win or lose the ball, what actually happens in the seconds after?

Reconstructed from the full timestamped event stream: real possession spells (not zone-clustered), and shots that follow a regain within a fixed window. This phase of play needs ordered, per-event timestamps — which every match here carries.

Direct play share16%
#12 of 18 · reaches final third in ≤3 passes
Patient build-up share30%
#9 of 18 · spells of 6+ passes
Tempo (possession length)18.3s
#10 of 18 · shorter = faster tempo
Passes per possession4.9
#10 of 18
Counter-attack shots /game0.86
#15 of 18 · shot within 12s of a regain in own half
Press→shot /game3.64
#3 of 18 · shot within 8s of a high regain
Speed to final third after regain12.8s
#10 of 18 · lower = faster break

Sequence success — defensive transition

29defensive transition sequences this season
79%succeed — reach the next third or a shot
10%turned over with nothing to show
Vision AI Model Insight
Rennes are a patient build-up side: 16% of possessions reach the final third in 3 passes or fewer (#12 of 18), against 30% built patiently over 6+ passes (#9 of 18). Winning the ball back leads to a shot inside 12 seconds 0.86 times a game (#15), and a high regain converts to a shot within 8 seconds 3.64 times a game (#3 of 18) — a genuine transition weapon.
Defending the box2 sections

Vulnerability Map — how opponents hurt them

The report flipped: where do opponents create their threat against Rennes? 348 opponent progressive passes and 121 shots faced (14.1 xG against) across the season.

Opponent threat by lane (attacking into Rennes)

Right wing
30%
Right half-space
12%
Central
9%
Left half-space
20%
Left wing
29%
Where the danger came from. Opponents generated most of their threat through the right wing (30% of the danger conceded).

How Do They Concede?

The question
Where do the goals against Rennes actually come from — open play, dead balls, and who supplies them?

Every goal Rennes conceded across the loaded matches — the opponent's shots in Rennes's own matches — plus every individual opponent key pass faced, each drawn as its own real arrow (not zone-clustered) with the % share of each zone behind it.

Where the goals go in

← opponent shot at own goal

Every opponent key pass against them (86 total)

1%1%1%3%6%2%19%16%27%14%9%Lucas HernándezOusmane DembéléAchraf HakimiDésiré DouéMika GodtsJoão NevesFabián RuizFerran TorresMika GodtsFabián RuizLucas BuadésLouis MafoutaLucas CalodatAlexandre LaurayLucas BretelleAdil BourabaaAlexandre LaurayJean VercruysseAntoine RabillardAmine SbaïBranco van den BoomenKhvicha KvaratskheliaFabián RuizBranco van den BoomenJim AllevinahJim AllevinahBranco van den BoomenCarlens ArcusBranco van den BoomenAmine SbaïBranco van den BoomenJordan LefortRomain FaivreMamadou DiopCameron ArcherDanny NamasoRomain FaivreNaouirou AhamadaRomain FaivreRomain FaivreRémy Labeau LascaryCorentin TolissoErnest NuamahLoïs OpendaPavel SulcPavel SulcZachary AthekamePavel SulcCorentin TolissoAbner ViníciusZachary AthekameAdama CamaraPablo PagisPablo PagisLassine SinayokoIlan KebbalLassine SinayokoAdama CamaraPierre Lees-MelouAdama CamaraLassine SinayokoLuca KoleoshoIlan KebbalIlan KebbalIlan KebbalAmine GouiriTimothy WeahIgor PaixãoHimad AbdelliEmersonAngel GomesPierre-Emile HøjbjergAmine GouiriIgor PaixãoEmersonAmine HaritGenesis AntwiGessime YassineGiovanni ReynaPape DiopConrad HarderOsoGiovanni ReynaJacobo OrtegaPape DiopNoah Nartey← own goal

By situation

Open play
11 · 79%
Set pieces
1 · 7%
Penalties
2 · 14%
Vision AI Model Insight
14 goals conceded. 79% come in open play; set pieces account for only 7%, so dead-ball defending is not the main issue. 14% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (27% of key passes faced) — that is the zone to shut off.
Context

Shape and tactics

Set pieces, strengths and weaknesses, and who they resemble.

Premium
Tactical Phase Read
The tactical idea behind each phase of this team's play, written from the same numbers shown above — what they do in build-up, how they progress, where they create, and how they defend it.
Subscribe →

Set-Piece Threat

How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.

Open play
12 g · 9.8 xG
Set pieces
1 g · 1.5 xG
Penalties
4 g
6% of goals come from set pieces (1 of 17), worth 1.5 xG from 23 shots. Set pieces are a secondary threat; the danger is in open play.

Where do Rennes's corners go?

43 corners taken this season, split by which flag they were taken from — arrows from the flag, dots at the delivery point, shaded by % of that side's corners landing in each zone (same treatment as the concede map below). No swing-direction (inswinger/outswinger) data is recorded here, only a start and end point per pass, which cannot show how the ball curved — so this shows what is genuinely knowable: where it lands, and short vs actually delivered. Tap or hover a dot for who took it and the match; filter to one match below and the shading recomputes for just that game.

Right side (11)

27%45%18%9%
Delivered into the box 100%Short 0%

Left side (32)

12%22%19%12%3%16%12%
Delivered into the box 97%Short 3%

Where opponents attack Rennes from set pieces

21 shots from opponent corners against Rennes, 1 conceded, split by the flag the corner came from — arrows from the flag, dots where the shot was taken (gold = goal), shaded by the % of that flag's shots in each zone. Tap or hover a shot for who took it, the minute and the match; filter to one match and the shading recomputes for just that game.

Right flag (14)

7%7%57%14%7%7%
Shot 14Goals 0

Left flag (7)

14%14%57%14%
Shot 7Goals 1

Tactical Strengths & Weaknesses

Strengths (top-third vs league)
  • progression /game — 50.62 (89th pct)
  • xG created /game — 1.81 (83th pct)
  • box entries /game — 15.00 (83th pct)
  • shots /game — 16.12 (78th pct)
  • press intensity (PPDA) — 5.26 (72th pct)
Weaknesses (bottom-third vs league)
  • xG conceded /game — 1.77 (6th pct)
  • pass retention % — 82.49 (33th pct)

Style Archetype & Similar Teams

Team archetype: Direct / counter high-press. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

Le Havre
49%
PSG
46%
Toulouse
45%
Lens
39%
Marseille
37%

Performance vs Opponent Styles

The question
Not just how Rennes results against a high press or a low block — how does their own play actually change?

Every match split into three tiers by how hard that specific opponent pressed (opponent PPDA — lower means a more aggressive press), matching Rennes's own passing behaviour to the result.

Results

opponent typegoals for/ggoals against/gpoints/g
vs high-pressing opponents (2m)1.003.000.50
vs mid-block opponents (2m)2.002.001.50
vs low-block opponents (4m)3.001.003.00

Behaviour — how Rennes actually play against each

opponent typeretentiondirectness (long balls)prog. passes/gxT/gbox entries/g
vs high-pressing opponents79%14%479.79.0
vs mid-block opponents81%12%4310.811.5
vs low-block opponents84%10%5612.819.8
Vision AI Model Insight
Facing a high press, retention drops to 79% vs 84% against a low block (5pt lower under pressure), and directness (long-ball share) sits at 14% when pressed vs 10% against a low block — a mild adjustment, not a wholesale change.

Scouting Summary — the team in brief

In brief. Rennes are balanced-territory with a aggressive high-press. Their attack creates 1.81 xG a game and they concede 1.77 a game. [Event-data based — no tracking, so off-ball structure and marking scheme need video.]
Squad

Players

Who drives the numbers.

Against Their Own Norm

For each of ten match numbers, the one match this season that departed furthest from Rennes’s own average, the eight biggest swings first. Bar right of centre means more than usual, left means less. It shows how much the way they play moves from game to game, and which opponent moved it.

Rennes
across 8 matches this season
Passesvs PSG · 2-2 · 2026-08-23355avg 520
Field tiltvs PSG · 2-2 · 2026-08-2319%avg 50%
PPDAvs PSG · 2-2 · 2026-08-238.8avg 5.3
Pass accuracyvs PSG · 2-2 · 2026-08-2376%avg 82%
Progressive carriesvs Le Mans · 3-2 · 2026-08-3077avg 45
Defensive actionsat Lyon · 0-4 · 2026-09-19143avg 162
Threat from passingat Paris FC · 3-4 · 2026-10-183.66avg 6.27
Expected goalsat Paris FC · 3-4 · 2026-10-183.19avg 1.81

On-Ball Value — who moved the game

Every pass, carry, take-on, shot and ball win is worth the change it made to the chance of scoring minus the chance of conceding in the next 10 seconds. This is Rennes’s last 8 matches added up: where the value came from, who produced it, and the six biggest single moves. OBV only measures what a player does with the ball: it shows who added the most on-ball value, not who was the most important player (defending off the ball, positioning and pressing are not in it).

+16.2on-ball value, 8 matches
Where the value came from
Passes4157 actions+6.13
Carries960 actions+0.29
Dribbles132 actions+0.17
Shots129 actions+6.89
Ball wins491 actions+2.75
Most on-ball value (OBV)ActionsOBVper 100
Estéban Lepaul200+3.30+1.65
Ludovic Blas218+1.78+0.82
Adrien Thomasson429+1.61+0.37
Aboubakar Nagida415+1.53+0.37
Przemyslaw Frankowski515+1.21+0.24
Bryan Reynolds178+1.01+0.56
Mahdi Camara374+0.83+0.22
Anthony Rouault388+0.79+0.20
123456
Biggest single movesOBV
1  Estéban Lepaul · shot+0.823
2  Estéban Lepaul · shot+0.794
3  Estéban Lepaul · shot+0.742
4  Przemyslaw Frankowski · pass+0.451
5  Estéban Lepaul · shot+0.409
6  Adrien Thomasson · shot+0.403

Set Pieces by Player

Who delivers Rennes’s dead balls and who finishes them this season. 43 corners taken, most by Adrien Thomasson (25); 23 shots from corners and free kicks, 1 goals, led by Adrien Thomasson (1 goals, 0.31 xG). “Into the box” counts corners that landed inside the penalty area; free-kick takers are the players who shot from one, because this feed does not mark who delivers the others.

PlayerCorners takenInto the boxSet-piece shotsGoalsxGFree-kick shotsPenalties
Adrien Thomasson2521 (84%)210.31——
Estéban Lepaul——3—0.22—4/4
Issa Soumaré——6—0.44——
Sebastian Szymanski1212 (100%)——0.00——
Anthony Rouault——3—0.19——
Charlie Cresswell——3—0.16——
Djaoui Cissé42 (50%)1—0.021—
Valentin Rongier——2—0.04——
Przemyslaw Frankowski——1—0.03——
Quentin Merlin——1—0.02——
Mahdi Camara——1—0.08——
Ludovic Blas11 (100%)——0.00——
Mousa Al Tamari10 (0%)——0.00——

Top Performers

Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 216 minutes). Coloured chips are that player's strongest capability blocks.

playerposminVision AI Scorecapability blocks
Brice SambaGK6648.6Shot-Stopping 86%
Adrien ThomassonCM5487.5Chance Creation 66%Progression 60%Successful Dribble 54%Ball-Carrying 31%
Charlie CresswellCB7696.8Progression 41%Aerial & Box Defending 40%Ball-Carrying 40%Ball-Winning 34%
Anthony RouaultCB4766.5Progression 74%Ball-Carrying 54%Aerial & Box Defending 41%Ball-Winning 38%
Estéban LepaulST5736.4Finishing 92%Box Threat 82%Ball-Carrying 35%Aerial Threat 0%
Valentin RongierCM6926.3Progression 74%Ball-Carrying 67%Successful Dribble 66%Chance Creation 46%
Aboubakar NagidaFB4565.7Ball-Winning 74%Ball-Carrying 50%Wide Delivery 48%
Mahdi CamaraCM5375.7Successful Dribble 62%Ball-Carrying 57%Progression 34%Chance Creation 14%
Przemyslaw FrankowskiCB5754.2Progression 72%Ball-Winning 44%Ball-Carrying 28%Aerial & Box Defending 26%
Mousa Al TamariST4684.0Ball-Carrying 75%Finishing 67%Box Threat 18%Aerial Threat 0%

Top Creators

Chance creation leaders — key passes /90 and box entries.

playerposminkey P /90box entriesxT
Adrien ThomassonM5482.63157.4
Przemyslaw FrankowskiD5751.251510.6
Mousa Al TamariF4681.54152.6
Ludovic BlasM3223.07103.8
Sebastian SzymanskiM4051.11134.7
Valentin RongierM6921.0499.2
Aboubakar NagidaD4561.38108.4
Mahdi CamaraM5370.6794.7

Wide Delivery Leaders

Crosses and cutbacks — wingers and full-backs only (by real average position, not the raw D/M position code), ranked by combined volume.

playerposmincrosses (completed)cutbacks (completed)
Aboubakar NagidaFB4568 (50%)4 (50%)
Quentin MerlinFB2586 (0%)3 (100%)
Bryan ReynoldsFB2497 (29%)1 (0%)
Issa SoumaréW37205 (60%)

Defensive Volume Leaders

Who does the defensive work — tackles, interceptions, recoveries.

playerposmindef actionstacklesinterceptrecoveries
Charlie CresswellD7691458727
Valentin RongierM692138211032
Aboubakar NagidaD456113171330
Adrien ThomassonM54810912630
Przemyslaw FrankowskiD57510714923
Anthony RouaultD476879314
Abdelhamid Aït BoudlalD3888312916
Mahdi CamaraM537747527

Full Squad Data

Every player with 100+ minutes (21 players).

playerposappsmingoalsxGkey PprogdefxT
Charlie CresswellD876900.213814510.4
Valentin RongierM869210.38271389.2
Brice SambaG766400.0022166.1
Przemyslaw FrankowskiD857510.386110710.6
Estéban LepaulF757375.367482.4
Adrien ThomassonM854821.016411097.4
Mahdi CamaraM753701.1422744.7
Anthony RouaultD547600.3122875.9
Mousa Al TamariF846800.8815492.6
Aboubakar NagidaD845600.27411138.4
Sebastian SzymanskiM640530.5516554.7
Abdelhamid Aït BoudlalD438800.006833.0
Issa SoumaréF637200.8210651.8
Ludovic BlasM832201.31117423.8
Quentin MerlinD525800.0329474.7
Bryan ReynoldsD524900.4417303.7
Boulaye DiaF618530.931210.4
Eliezer MayendaM618000.423220.6
Arnaud NordinM311300.50380.6
Djaoui CisséM310700.224240.7
Nicolas LemaîtreG110500.00340.5

Player Role Architecture

The question
Who does what — and what tactical job does each key player actually perform?

The nine most-used players (450+ minutes), each with the role their event fingerprint points to — not just their listed position.

Charlie Cresswell
Stopper / marker · Defender
minutes769
goals · xG0 · 0.2
prog passes /904.4
key passes /900.12
def actions /9017.0
pass accuracy84%
Valentin Rongier
Ball-winner / destroyer · Midfielder
minutes692
goals · xG1 · 0.3
prog passes /903.5
key passes /901.04
def actions /9017.9
pass accuracy90%
Brice Samba
Goalkeeper · Goalkeeper
minutes664
goals · xG0 · 0.0
prog passes /903.0
key passes /900.00
def actions /902.2
pass accuracy84%
Przemyslaw Frankowski
Ball-playing defender · Defender
minutes575
goals · xG1 · 0.3
prog passes /909.5
key passes /901.25
def actions /9016.7
pass accuracy80%
Estéban Lepaul
Poacher / finisher · Forward
minutes573
goals · xG7 · 5.3
prog passes /901.1
key passes /900.94
def actions /907.5
pass accuracy83%
Adrien Thomasson
Advanced creator · Attacking mid
minutes548
goals · xG2 · 1.0
prog passes /906.7
key passes /902.63
def actions /9017.9
pass accuracy78%
Mahdi Camara
Ball-winner / destroyer · Midfielder
minutes537
goals · xG0 · 1.1
prog passes /903.7
key passes /900.67
def actions /9012.4
pass accuracy90%
Anthony Rouault
Stopper / marker · Defender
minutes476
goals · xG0 · 0.3
prog passes /904.2
key passes /900.19
def actions /9016.4
pass accuracy87%
Mousa Al Tamari
Ball-winner / destroyer · Midfielder
minutes468
goals · xG0 · 0.8
prog passes /902.9
key passes /901.54
def actions /909.4
pass accuracy73%

Recruitment Intelligence — profiles to sign

The question
If you were sporting director, which player profiles would move the needle most?

Each recruitment target is derived directly from the team's weakest areas vs the league — the gap, why it shows in the data, and the profile that closes it.

Need — bottom-third: xG conceded /game (6th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.77, 6th percentile vs the league).
Need — bottom-third: pass retention % (33th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (82.49, 33th percentile vs the league).
Need — below-average: field tilt % (44th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (49.92, 44th percentile vs the league).
Vision AI · building report