Combining every season — this one is larger, give it a moment.
Team reportLigue 1 2025/26
Marseille
A possession-dominant side, aggressive high-press out of possession, with a high-volume attack. Finished #6 of 20 on 71 points (22-5-15, 81:58). Tactical profile below is built from 42 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Marseille and how good was the season?
Read. Marseille finished #6 of 20 on 71 points (22W-5D-15L, 1.69 pts/game), scoring 81 and conceding 58 for a goal difference of +23.
On the ball they are a possession-dominant team (60% field tilt, #2 in the league); off it they defend with a aggressive high-press (#6 of 20 for press intensity).
Across the 42 matches of event data, they create 1.53 xG/game (#3) and concede 1.32 (#9), a net of +0.21 xG/game — the underlying performance diverges from the actual goal difference.
Season Context — the league table
The question
Where did Marseille actually finish, and against whom?
The authoritative final table (full season), centred on Marseille.
#
team
P
W
D
L
GF
GA
GD
Pts
3
Lille
42
22
10
10
63
43
+20
76
4
Rennes
42
22
9
11
77
64
+13
75
5
Lyon
42
22
8
12
66
47
+19
74
6
Marseille
42
22
5
15
81
58
+23
71
7
Monaco
42
20
9
13
71
61
+10
69
8
Strasbourg
42
17
9
16
70
65
+5
60
9
Paris FC
42
15
13
14
60
59
+1
58
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Marseille 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)
Vision AI Model Insight
Marseille tend to fade after a strong start — first-half net xG +7.23, second-half +1.68. Their strongest period is 46-60' (net +4.96 xG); their most dangerous period to face is 76-90+' (net -4.48 xG against them).
xG Race — the season, match by match
Expected goals piling up over 42 matches: Marseille 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 (+8.9 xG). Hover a point for that match.
MarseilleOpponents against Marseille
Tactical DNA
The football question
In five genes, what is Marseille'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.
90
Build-Up
possession control from the back
52
Progression
moving the ball upfield with threat
80
Creation
manufacturing chances
80
Press
winning the ball high & hard
55
Solidity
resisting the opponent's threat
Genetic identity
Marseille are defined most by their Build-Up DNA (90/100 · elite at possession control from the back), and least by their Progression DNA (52/100). Percentiles vs the 20 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).
Possess
Deep buildup
85%
Possession
90%
Field tilt
90%
Disrupt
Central progression ~proxy
90%
Dribble tendency
10%
Progressive passes
25%
Finish
Final-third patience
80%
Shot quality
35%
Open-play xG
80%
Press
Forward press ~proxy
70%
High regains
55%
Pressing efficiency ~proxy
90%
Defend
Def-mid press ~proxy
75%
High line ~proxy
85%
PAdj defensive actions
50%
Marseille is defined most by Possess (88% in the league) and weakest on Disrupt (42%). 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.
How much of the pitch does Marseille actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Marseille'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; Marseille highlighted. Hover any dot for the team.
Vision AI Model Insight
Marseille post 60% field tilt, ranking #2 of 20 in the league — a genuinely territory-dominant side, and their 1.69 points/game sits above the league-average return — territory is genuinely converting into results.
Where the time goes — how long each phase lasts
The question
When Marseille has the ball, how much of that time is spent building, progressing and creating?
The share of Marseille'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.
Phase
Share of the time
Build-up
23.3%
Progression
50.9%
Chance creation
23.9%
Attacking transition
1.9%
Vision AI Model Insight
Progression is where Marseille spends most of its time on the ball (51% 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.
width = passes between the paircolour = xT per pass: low → high
Top 10 combinations
Emerson ↔ Aguerd
348p · 13.0xT
Højbjerg ↔ Emerson
347p · 14.2xT
Højbjerg ↔ Balerdi
327p · 10.8xT
Højbjerg ↔ Greenwood
290p · 16.4xT
Weah ↔ Greenwood
277p · 16.5xT
Rulli ↔ Balerdi
265p · 8.9xT
Højbjerg ↔ Aguerd
264p · 9.8xT
Pavard ↔ Greenwood
262p · 18.9xT
Pavard ↔ Weah
261p · 13.5xT
Højbjerg ↔ Pavard
261p · 6.7xT
Vision AI Model Insight
Busiest connection: Emerson ↔ Nayef Aguerd (348 passes). Most dangerous per pass: Pierre-Emile Højbjerg ↔ Gerónimo Rulli (0.10 xT/pass over 117 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Marseille had the ball
Every touch across 378 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Marseille 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
24573
ACTIONS
Carries
the ball moved with a player
6519
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the middle third (13.0% of all actions). 64% of actions run through the inside lanes (centre + both half-spaces) versus 36% down the two wings — an inside-dominant, half-space build. By third: 25% defensive, 52% middle, 23% 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. Marseille leaned on their left (41%). The bars under the pitch put the league’s share beside theirs.
Marseille
41%23%36%
League
39%22%39%
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. Marseille made 2155 this season (51.3 a match); 31% 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.
Channel
Entries
Per match
Share
League share
Left wing
674
16.0
31%
30%
Left half-space
365
8.7
17%
15%
Centre
206
4.9
10%
11%
Right half-space
289
6.9
13%
14%
Right wing
621
14.8
29%
31%
Build-up2 sections
Build-Up — the pass map
The football question
How does Marseille 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.
6117build-up passes attempted
86%completed
28%reach the middle third
1%go long into the final third
Pass types
2607CB · 49%
252Long Wide · 5%
28Long Central · 1%
1796Wide → FB · 34%
606Central · 11%
Sequence success — build-up
875build-up sequences this season
14%succeed — reach the next third or a shot
38%turned over with nothing to show
CB2607 · 49%
Long Wide252 · 5%
Long Central28 · 1%
Wide → FB1796 · 34%
Central606 · 11%
◆ Vision AI Insight
Marseille build predominantly down the left, with Rulli as the fulcrum (825 build-up passes). Only 29% 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 → LHS def (400×).
Pass Explorer
Every pass of Marseille’s last 10 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.
From channel
To channel
From third
To third
Outcome
Minutes
Channel to channel · click a cell
Third to third · click a cell
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. 1696 progressive passes across 42 matches (40.4/game).
Origin lane
Right wing
27%
Right half-space
13%
Central
11%
Left half-space
15%
Left wing
34%
Progression is left-dominant: 40% right side · 11% central · 49% left.
Who generates it
Emerson
228 · 13%
Mason Greenwood
189 · 11%
Timothy Weah
162 · 10%
Pierre-Emile Højbjerg
147 · 9%
Igor Paixão
119 · 7%
Top two — Emerson & Mason Greenwood — account for 25% of all progression.
PROGRESSION
40.4 prog passes/game
mostly left
→
PENETRATION
25% reach final third
21% reach the box
→
THREAT
the other 75% is recycled
progress ≠ danger
What came of it.25% 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 left 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 wingbalanced
Right half-spacebalanced
Centralbalanced
Left half-spacebalanced
Left wingbalanced
Progression — the pass map
The football question
Once Marseille 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.
12746progression passes attempted
90%completed
15%break into the final third
9%go backward into the defensive third
Pass types
4648CB · 41%
277Long Wide · 2%
34Long Central · 0%
4872Wide → FB · 43%
1631Central · 14%
Sequence success — progression
1757progression sequences this season
29%succeed — reach the next third or a shot
38%turned over with nothing to show
CB4648 · 41%
Long Wide277 · 2%
Long Central34 · 0%
Wide → FB4872 · 43%
Central1631 · 14%
◆ Vision AI Insight
Marseille progress predominantly down the left, with Højbjerg the busiest midfield outlet (1707 progression passes). Only 15% of passes that start in midfield actually break the final-third line — the rest (76%) is recycled back into midfield or (9%) played backward, the hallmark of a side that carries progression itself through midfield rather than just passing through it. Their most-repeated pattern is LHS mid → C mid (673×) — 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)
12%
Progressive
1%
Neutral / sideways
48%
Safe / backward
39%
13% of passes are progressive-or-better; the remaining 87% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Marseille actually progress the ball with their feet, not a pass?
1209 progressive carries this season across the whole squad (20% of 6150 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 56m. Most active carrier: Emerson (118). Filter to one player below.
First (371)Second (330)Third (287)Fourth (221)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 Marseille'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.
616shots
64.4xG
0.10xG per shot
38big chances (0.3+ xG)
80goals
#3key passes / game in the league
#5box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition27% of shots
167
24
17.47
0.10
Cross
4
0
0.77
0.19
Cut-back
14
2
2.04
0.15
Long ball
12
0
1.60
0.13
Pass into the box / short pass
101
18
10.45
0.10
Own creation (carry, dribble, rebound)
36
4
2.62
0.07
Settled attack52% of shots
320
40
30.26
0.09
Cross
45
5
5.02
0.11
Cut-back
29
7
3.56
0.12
Long ball
27
2
2.38
0.09
Pass into the box / short pass
162
17
14.70
0.09
Own creation (carry, dribble, rebound)
57
9
4.61
0.08
Set piece21% of shots
129
16
16.63
0.13
Corner
99
7
7.45
0.08
Free kick
19
1
0.44
0.02
Penalty
11
8
8.73
0.79
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
Player
Set-ups
xG created
Goals
Mason Greenwood
46
5.01
5
Emerson
39
4.64
4
Pierre-Emile Højbjerg
46
4.29
5
Amine Gouiri
33
3.60
5
Pierre-Emerick Aubameyang
24
3.54
5
Who takes them
Player
Shots
xG
Goals
Mason Greenwood
115
13.48
16
Pierre-Emerick Aubameyang
60
9.59
10
Amine Gouiri
55
8.28
13
Igor Paixão
72
5.57
8
Pierre-Emile Højbjerg
58
3.95
5
Vision AI Model Insight
The biggest source of Marseille's chances, by xG, is settled attack (30.3 of 64.4 xG, 320 of 616 shots), mostly pass into the box / short pass. 167 of the 616 shots (27%) came within 15 seconds of winning the ball. 129 of the 616 shots came from set pieces; 80 goals from 64.4 xG (+15.6).
Chance Creation — the pass map
The football question
How does Marseille 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
69CB · 15%
25Long Wide · 5%
42Long Central · 9%
141Wide → FB · 31%
182Central · 40%
Sequence success — final-third
1342final-third sequences this season
25%succeed — produce a shot
34%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
CB69 · 15%
Long Wide25 · 5%
Long Central42 · 9%
Wide → FB141 · 31%
Central182 · 40%
Who creates — volume × threat
57Greenwood
56Emerson
48Højbjerg
42Gouiri
35Weah
35Paixão
25Aubameyang
459key passes #3 of 20
13.5box entries/game #5 of 20
41.4final-3rd entries/game #2 of 20
1.53xG/game #3 of 20
80goals #3 of 20
+15.6finishing vs xG #1 of 20
◆ Vision AI Insight
Marseille lean left — 44% of their key passes come from that flank and its half-space (200 of 459), most often from Emerson (47). They funnel chances into the c of the final third, most often via RHS att → C att (67 key passes, most often from Greenwood). Greenwood is the primary source overall. They generate 1.53 xG a game and finish it clinical — they beat their xG, led by Mason Greenwood (16G), Amine Gouiri (13G), Pierre-Emerick Aubameyang (10G).
Crosses & Cutbacks — squad-wide
The question
How does Marseille deliver into the box from wide areas, and what comes of it?
532 crosses: 163 found a team-mate (31%), 53 led to a shot (10%). 152 cut-backs: 76 found a team-mate (50%), 48 led to a shot (32%). 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 Marseille actually cross from?
532 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. 23% come from one territory, the byline right wing; 47 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
byline · right wing
120
23%
15
byline · left wing
110
21%
10
advanced · right wing
102
19%
8
advanced · left wing
98
18%
10
deep · left wing
31
6%
2
deep · right wing
24
5%
0
advanced · right half-space
14
3%
5
byline · right half-space
13
2%
2
byline · left half-space
10
2%
1
advanced · left half-space
6
1%
0
deep · right half-space
2
0%
0
deep · left half-space
2
0%
0
Finishing3 sections
Shot Map
616 shots for 64.4 xG (1.53/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. 14.7 shots/game at 0.104 xG/shot. Box entries 14/game (#5). Threat created 11.7 xT/game (#4).
Goal Sequences
The move behind each of Marseille’s 81 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 — 81 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Marseille scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
64 · 80%
Set pieces
8 · 10%
Penalties
8 · 10%
By finish
Right foot
58 · 72%
Left foot
14 · 18%
Header
8 · 10%
Vision AI Model Insight
80 goals scored. 80% come in open play; set pieces add 10%. 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
How they lose it
Incomplete pass — attacking third
1276
Failed forward pass
851
Failed take-on
448
Lost in the defensive third
828
Their weakest zone is the right half-space in the attacking third: 25% of 1052 pass attempts there are lost (261 times). Separately, 38% 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.
How hard does Marseille 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.
72
Pressing Index /100 · strong
Intensity60
PPDA, high-press share, high-zone actions
Height85
how high up the pitch they defend
Effectiveness85
high recoveries & high-regain share
Disruption58
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
17%
RHS
21%
C
24%
LHS
23%
LW
16%
By third (high / mid / low regain)
Def 45%
Mid 40%
Att 15%
Read
Ranked #6 of 20 for press intensity, this is a high press. 55% of defensive actions happen in the middle & attacking thirds, at an average height of 39. Of recoveries, 59% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#6/20
lower = more intense; rank is what matters
Defensive actions / game
121
#19/20
High-press share
23%
#7/20
def actions won high up
Defensive-action height (0–100)
39.4
#3/20
avg pitch height of actions
High recoveries / game
24.5
#4/20
ball won in mid+att third
High-recovery share
59%
#2/20
share of recoveries won high
Opponent completion allowed
82%
#8/20
lower = more disruptive
Opponent progressive allowed
8.3%
#9/20
of 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 Marseille win it back with a defensive action?
Counted over the 1377 opposition possessions that Marseille 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 Marseille step in. Marseille win it after 5.1 opponent passes in the first half-hour and after 4.3 after the hour mark (sooner).
PASSES THEY GET
4.7passes
median 3 · before Marseille win it
TIME THEY KEEP IT
14sec
median 7s · 32.8 wins per game
How many passes the opponent got in before the ball was won
42%
29%
17%
13%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
5.1
15s
15–30′
5.1
14s
30–45+′
5.2
15s
45–60′
4.5
13s
60–75′
3.9
11s
75–90+′
4.7
15s
average passesaverage seconds
Phases of play
Every moment of the match read twice — what Marseille were doing with the
ball, and what the opposition were doing about it at that exact moment. Built from the
real action sequence in time order, so one possession is split across the phases it
genuinely passed through rather than labelled once by where it began.
6,444phase segments analysed
12.0smedian time before the opposition engage
2.2their passes per defensive action when pressed
#6of 18 for share of defending spent pressing high
High press 9.5%Mid block 15.1%Low block 42.4%Unopposed 33.0%
What opponents do against Marseille
The mirror image, and the part no other section can show: whether teams come
out to press Marseille or sit in and invite them on. A side that is always faced with a low
block is playing a different sport from one that is pressed every week.
High press 4.6%Mid block 10.9%Low block 55.7%Unopposed 28.7%
Which phases actually produce
Phase
Segments
Avg length
Avg actions
Ends in shot
Turned over
Build-up
1,757
5.9s
3.5
0.2%
40.6%
Progression
2,772
8.1s
5.0
0.6%
39.7%
Chance creation
1,788
5.9s
3.6
26.6%
47.0%
Attacking transition
127
6.6s
4.4
4.7%
32.3%
Most common routes through the phases
How a possession actually travelled, in order. The chain is the tactical signature — a move that climbs all three thirds is a different thing from one that never leaves the first.
Route
Times
Ends in shot
build_up
565
0.5%
progression
560
0.9%
progression → chance_creation
348
30.5%
chance_creation
332
44.0%
build_up → progression
292
0.0%
build_up → progression → chance_creation
211
30.8%
Attitude in each third
Every other style number here says how much Marseille 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 Marseille 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) 6,117 passes
nothing unusual in this zone
Width of use-0.2420.50
Wide-channel share-0.550.27
Side bias+0.200.91
Pass length-0.8419.68
Long-ball share-0.800.15
Forward gain per pass-0.668.59
Backward-pass share+0.150.21
Deep-pass share-0.740.22
Completion+0.770.86
Seconds between passes-0.343.12
Side used
left 28% · central 46% · right 26%
Progression (middle third) 12,746 passes
nothing unusual in this zone
Width of use-0.7923.89
Wide-channel share-0.830.35
Side bias+0.441.82
Pass length-0.6716.29
Long-ball share-0.760.07
Forward gain per pass-0.482.87
Backward-pass share+0.350.35
Deep-pass share-0.680.13
Completion+0.760.89
Seconds between passes-0.502.98
Side used
left 36% · central 33% · right 31%
Final third 5,710 passes
nothing unusual in this zone
Width of use-0.3530.74
Wide-channel share-0.360.56
Side bias+0.301.65
Pass length-0.5814.57
Long-ball share-0.680.07
Forward gain per pass-0.600.25
Backward-pass share+0.550.42
Deep-pass share-0.360.08
Completion+0.810.76
Seconds between passes-0.153.29
Side used
left 44% · central 15% · right 40%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Marseille'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 Marseille 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 share17%
#10 of 20 · reaches final third in ≤3 passes
Patient build-up share36%
#3 of 20 · spells of 6+ passes
Tempo (possession length)22.7s
#19 of 20 · shorter = faster tempo
Passes per possession6.1
#2 of 20
Counter-attack shots /game1.36
#2 of 20 · shot within 12s of a regain in own half
Press→shot /game3.43
#6 of 20 · shot within 8s of a high regain
Speed to final third after regain13.5s
#14 of 20 · lower = faster break
Sequence success — attacking transition
118attacking transition sequences this season
19%succeed — produce a shot
39%turned over with nothing to show
Sequence success — defensive transition
400defensive transition sequences this season
67%succeed — reach the next third or a shot
8%turned over with nothing to show
Vision AI Model Insight
Marseille are a patient build-up side: 17% of possessions reach the final third in 3 passes or fewer (#10 of 20), against 36% built patiently over 6+ passes (#3 of 20). Winning the ball back leads to a shot inside 12 seconds 1.36 times a game (#2), and a high regain converts to a shot within 8 seconds 3.43 times a game (#6 of 20) — a modest but real source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Marseille? 1532 opponent progressive passes and 494 shots faced (55.5 xG against) across the season.
Opponent threat by lane (attacking into Marseille)
Right wing
29%
Right half-space
13%
Central
17%
Left half-space
14%
Left wing
27%
Where the danger came from. Opponents generated most of their threat through the right wing (29% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Marseille actually come from — open play, dead balls, and who supplies them?
Every goal Marseille conceded across the loaded matches — the opponent's shots in Marseille'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
Every opponent key pass against them (354 total)
By situation
Open play
46 · 82%
Set pieces
2 · 4%
Penalties
8 · 14%
Vision AI Model Insight
56 goals conceded. 82% come in open play; set pieces account for only 4%, so dead-ball defending is not the main issue. 23% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the left half-space of the attacking third (19% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
64 g · 47.7 xG
Set pieces
8 g · 7.9 xG
Penalties
8 g
10% of goals come from set pieces (8 of 80), worth 7.9 xG from 118 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Marseille's corners go?
211 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 (103)
Delivered into the box 96%Short 4%
Left side (108)
Delivered into the box 94%Short 6%
Where opponents attack Marseille from set pieces
48 shots from opponent corners against Marseille, 2 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 (19)
Shot 19Goals 0
Left flag (29)
Shot 29Goals 2
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
field tilt % — 60.14 (90th pct)
pass retention % — 86.21 (90th pct)
xG created /game — 1.53 (85th pct)
shots /game — 14.67 (85th pct)
threat created /game — 11.73 (80th pct)
Weaknesses (bottom-third vs league)
progression /game — 40.38 (25th pct)
Style Archetype & Similar Teams
Team archetype: High-press possession side. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.
PSG
78%
Lyon
75%
Strasbourg
64%
Monaco
51%
Lille
50%
Performance vs Opponent Styles
The question
Not just how Marseille 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 Marseille's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (14m)
1.71
1.64
1.57
vs mid-block opponents (14m)
1.21
1.29
1.43
vs low-block opponents (14m)
2.86
1.21
2.07
Behaviour — how Marseille actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
82%
12%
37
9.7
12.1
vs mid-block opponents
86%
9%
42
12.1
13.4
vs low-block opponents
89%
7%
42
13.4
14.9
Vision AI Model Insight
Facing a high press, retention drops to 82% vs 89% against a low block (8pt lower under pressure), and directness (long-ball share) sits at 12% when pressed vs 7% against a low block — a real style switch: they go noticeably more direct when pressed rather than trying to play through it.
Scouting Summary — the team in brief
In brief. Marseille are possession-dominant with a aggressive high-press.
Their attack creates 1.53 xG a game and they concede 1.32 a game.
[Event-data based — no tracking, so off-ball structure and marking scheme need video.]
For each of ten match numbers, the one match this season that departed furthest from Marseille’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.
Defensive actionsvs Le Havre · 4-3 · 2026-10-25177avg 121
Progressive passesat Le Havre · 1-0 · 2026-05-1019avg 40
Pass accuracyat Lyon · 0-1 · 2025-08-3177%avg 85%
Field tiltat Lyon · 0-1 · 2025-08-3128%avg 60%
Expected goalsvs Le Havre · 6-2 · 2025-10-182.86avg 1.53
Passesvs PSG · 1-0 · 2025-09-22336avg 585
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 Marseille’s last 12 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).
+21.4on-ball value, 12 matches
Where the value came from
Passes6962 actions+6.52
Carries1794 actions-0.23
Dribbles222 actions+0.54
Shots178 actions+10.18
Ball wins768 actions+4.38
Most on-ball value (OBV)
Actions
OBV
per 100
Amine Gouiri
420
+2.38
+0.57
Mason Greenwood
223
+2.13
+0.96
Emerson
993
+1.88
+0.19
Himad Abdelli
590
+1.85
+0.31
Pierre-Emile Højbjerg
1075
+1.81
+0.17
Timothy Weah
737
+1.55
+0.21
Igor Paixão
495
+1.20
+0.24
Angel Gomes
339
+1.19
+0.35
Biggest single moves
OBV
1 Amine Gouiri · shot
+0.841
2 Mason Greenwood · shot
+0.828
3 Himad Abdelli · shot
+0.802
4 Amine Gouiri · shot
+0.786
5 Angel Gomes · pass
+0.531
6 Leonardo Balerdi · shot
+0.510
Set Pieces by Player
Who delivers Marseille’s dead balls and who finishes them this season. 211 corners taken, most by Emerson (61); 118 shots from corners and free kicks, 8 goals, led by Pierre-Emerick Aubameyang (3 goals, 1.42 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.
Player
Corners taken
Into the box
Set-piece shots
Goals
xG
Free-kick shots
Penalties
Mason Greenwood
48
38 (79%)
18
—
0.56
8
6/8
Emerson
61
55 (90%)
4
—
0.11
2
—
Pierre-Emile Højbjerg
—
—
19
—
1.10
3
—
Igor Paixão
25
14 (56%)
9
—
0.27
3
—
Leonardo Balerdi
—
—
17
—
1.92
—
—
Amine Gouiri
28
23 (82%)
2
—
0.06
1
1/2
Pierre-Emerick Aubameyang
1
0 (0%)
9
3
1.42
—
—
Nayef Aguerd
—
—
9
—
0.69
—
—
Benjamin Pavard
—
—
6
1
0.34
—
—
Amine Harit
14
14 (100%)
1
—
0.03
—
—
Angel Gomes
8
7 (88%)
3
2
0.08
1
—
Amir Murillo
—
—
3
—
0.10
1
—
Geoffrey Kondogbia
—
—
3
—
0.20
—
—
Hamed Traoré
4
4 (100%)
1
—
0.04
—
—
Top Performers
Ranked by Vision AI Score — the same tactical behavioural evaluation each player's own report page shows (min 300 minutes). Coloured chips are that player's strongest capability blocks.
Chance creation leaders — key passes /90 and box entries.
player
pos
min
key P /90
box entries
xT
Mason Greenwood
M
2575
1.99
85
40.1
Emerson
D
2998
1.68
62
47.1
Pierre-Emile Højbjerg
M
3427
1.26
46
56.4
Igor Paixão
M
2618
1.20
52
21.6
Amine Gouiri
F
2088
1.81
42
13.1
Timothy Weah
D
3017
1.04
48
34.5
Pierre-Emerick Aubameyang
F
2131
1.06
25
8.4
Angel Gomes
M
1417
1.33
20
14.0
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.
player
pos
min
crosses (completed)
cutbacks (completed)
Igor Paixão
W
2618
28 (36%)
31 (39%)
Emerson
FB
2998
33 (36%)
24 (33%)
Keyliane Abdallah
W
229
4 (75%)
6 (17%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Pierre-Emile Højbjerg
M
3427
466
46
38
192
Leonardo Balerdi
D
2135
413
49
27
119
Nayef Aguerd
D
2026
379
27
29
94
Emerson
D
2998
377
55
46
106
Timothy Weah
D
3017
357
65
25
125
Igor Paixão
M
2618
331
38
20
113
Benjamin Pavard
D
2049
277
28
25
65
CJ Egan-Riley
D
1478
231
19
10
60
Full Squad Data
Every player with 100+ minutes (34 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Pierre-Emile Højbjerg
M
38
3427
5
4.0
48
147
466
56.4
Timothy Weah
D
36
3017
3
2.2
35
162
357
34.5
Emerson
D
36
2998
0
0.9
56
228
377
47.1
Gerónimo Rulli
G
29
2777
0
0.1
0
68
90
21.3
Igor Paixão
M
37
2618
8
5.6
35
119
331
21.6
Mason Greenwood
M
32
2575
16
13.5
57
189
133
40.1
Leonardo Balerdi
D
26
2135
0
2.1
3
35
413
26.0
Pierre-Emerick Aubameyang
F
30
2131
10
9.6
25
38
119
8.4
Amine Gouiri
F
30
2088
13
8.3
42
51
164
13.1
Benjamin Pavard
D
27
2049
1
0.7
9
53
277
26.6
Nayef Aguerd
D
24
2026
1
1.1
2
66
379
31.4
CJ Egan-Riley
D
19
1478
1
0.1
2
40
231
18.2
Facundo Medina
D
17
1444
0
0.4
7
83
215
27.0
Angel Gomes
M
22
1417
4
2.4
21
38
125
14.0
Jeffrey de Lange
G
13
1240
0
0.0
1
31
24
8.9
Quinten Timber
M
16
1179
0
1.0
8
26
124
10.0
Amir Murillo
D
16
1049
2
0.8
11
53
125
11.6
Arthur Vermeeren
M
20
965
0
0.2
10
25
144
8.7
Himad Abdelli
M
16
817
5
3.7
7
20
118
8.7
Geoffrey Kondogbia
M
14
802
0
0.2
2
25
162
9.1
Matt O'Riley
M
15
790
1
0.6
12
21
98
7.2
Bilal Nadir
M
20
701
0
0.6
10
20
83
5.8
Amine Harit
M
8
657
2
0.5
15
35
74
8.0
Hamed Traoré
M
13
652
2
1.6
10
29
65
5.6
Tochukwu Nnadi
M
13
631
0
0.5
3
23
88
5.8
Robinio Vaz
F
14
438
4
1.9
6
2
42
0.6
Ethan Nwaneri
M
9
351
2
0.7
5
13
31
3.9
Ulisses Garcia
D
8
292
0
0.3
1
15
19
1.9
Keyliane Abdallah
M
8
229
1
0.7
3
13
23
2.3
Nouhoum Kamissoko
M
6
216
1
0.2
2
3
53
1.7
Neal Maupay
F
8
198
0
0.4
2
1
28
0.8
Derek Cornelius
D
5
115
0
0.1
0
1
12
0.7
Darryl Bakola
M
8
114
0
0.1
1
2
14
0.8
Kelyann Bezahaf
D
2
110
0
0.0
0
5
19
1.5
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.
Pierre-Emile Højbjerg
Ball-winner / destroyer · Midfielder
minutes3427
goals · xG5 · 4.0
prog passes /903.9
key passes /901.26
def actions /9012.2
pass accuracy89%
Timothy Weah
Ball-playing defender · Defender
minutes3017
goals · xG3 · 2.2
prog passes /904.8
key passes /901.04
def actions /9010.6
pass accuracy84%
Emerson
Ball-playing defender · Defender
minutes2998
goals · xG0 · 0.9
prog passes /906.8
key passes /901.68
def actions /9011.3
pass accuracy84%
Gerónimo Rulli
Goalkeeper · Goalkeeper
minutes2777
goals · xG0 · 0.1
prog passes /902.2
key passes /900.00
def actions /902.9
pass accuracy82%
Igor Paixão
Poacher / finisher · Forward
minutes2618
goals · xG8 · 5.6
prog passes /904.1
key passes /901.20
def actions /9011.4
pass accuracy78%
Mason Greenwood
Creative forward · Forward
minutes2575
goals · xG16 · 13.5
prog passes /906.6
key passes /901.99
def actions /904.6
pass accuracy77%
Leonardo Balerdi
Stopper / marker · Defender
minutes2135
goals · xG0 · 2.1
prog passes /901.5
key passes /900.13
def actions /9017.4
pass accuracy92%
Pierre-Emerick Aubameyang
Poacher / finisher · Forward
minutes2131
goals · xG10 · 9.6
prog passes /901.6
key passes /901.06
def actions /905.0
pass accuracy77%
Amine Gouiri
Creative forward · Forward
minutes2088
goals · xG13 · 8.3
prog passes /902.2
key passes /901.81
def actions /907.1
pass accuracy81%
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: progression /game (25th pct)
Sign a progressive passer / ball-carrier to break lines. The data flags this because progression is limited (40.38, 25th percentile vs the league).
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