A territorially-dominated side, aggressive high-press out of possession, with a moderate attack. Finished #20 of 20 on 18 points (2-12-24, 26:71). Tactical profile below is built from 38 matches of ball-by-ball event data, contextualised against the league.
In one read, what kind of team is Pisa and how good was the season?
Read. Pisa finished #20 of 20 on 18 points (2W-12D-24L, 0.47 pts/game), scoring 26 and conceding 71 for a goal difference of -45.
On the ball they are a territorially-dominated team (39% field tilt, #21 in the league); off it they defend with a aggressive high-press (#16 of 23 for press intensity).
Across the 38 matches of event data, they create 1.02 xG/game (#18) and concede 1.44 (#19), a net of -0.43 xG/game — the underlying performance diverges from the actual goal difference.
Season Context — the league table
The question
Where did Pisa actually finish, and against whom?
The authoritative final table (full season), centred on Pisa.
#
team
P
W
D
L
GF
GA
GD
Pts
17
Lecce
38
10
8
20
28
50
-22
38
18
Cremonese
38
8
10
20
32
57
-25
34
19
Hellas Verona
38
3
12
23
25
61
-36
21
20
Pisa
38
2
12
24
26
71
-45
18
Match Momentum — when they create and concede danger
The question
Across a whole game, which periods does Pisa 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
Pisa tend to fade after a strong start — first-half net xG -6.34, second-half -9.91. Their strongest period is 0-15' (net -0.34 xG); their most dangerous period to face is 31-45' (net -5.34 xG against them).
xG Race — the season, match by match
Expected goals piling up over 38 matches: Pisa 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 (-16.2 xG). Hover a point for that match.
PisaOpponents against Pisa
Tactical DNA
The football question
In five genes, what is Pisa'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.
11
Build-Up
possession control from the back
24
Progression
moving the ball upfield with threat
19
Creation
manufacturing chances
20
Press
winning the ball high & hard
17
Solidity
resisting the opponent's threat
Genetic identity
Pisa are defined most by their Progression DNA (24/100 · limited at moving the ball upfield with threat), and least by their Build-Up DNA (11/100). Percentiles vs the 23 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
13%
Possession
4%
Field tilt
9%
Disrupt
Central progression ~proxy
0%
Dribble tendency
65%
Progressive passes
22%
Finish
Final-third patience
43%
Shot quality
52%
Open-play xG
17%
Press
Forward press ~proxy
30%
High regains
35%
Pressing efficiency ~proxy
43%
Defend
Def-mid press ~proxy
9%
High line ~proxy
43%
PAdj defensive actions
26%
Pisa is defined most by Finish (38% in the league) and weakest on Possess (9%). Percentiles vs the 23 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 Pisa actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Pisa'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; Pisa highlighted. Hover any dot for the team.
Vision AI Model Insight
Pisa post 39% field tilt, ranking #21 of 23 in the league — below the league mid-point, spending more of the game defending their own territory than dictating it, and their 0.47 points/game sits below the league-average return — territory is genuinely converting into results.
Where the time goes — how long each phase lasts
The question
When Pisa has the ball, how much of that time is spent building, progressing and creating?
The share of Pisa'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
29.3%
Progression
45.9%
Chance creation
22.1%
Attacking transition
2.7%
Vision AI Model Insight
Progression is where Pisa spends most of its time on the ball (46% 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
Caracciolo ↔ Canestrelli
322p · 5.6xT
Caracciolo ↔ Aebischer
279p · 9.3xT
Aebischer ↔ Canestrelli
274p · 10.2xT
Aebischer ↔ Angori
212p · 9.9xT
Canestrelli ↔ Angori
209p · 11.7xT
Semper ↔ Canestrelli
185p · 7.1xT
Caracciolo ↔ Calabresi
162p · 3.3xT
Aebischer ↔ Léris
155p · 10.3xT
Aebischer ↔ Akinsanmiro
151p · 6.0xT
Caracciolo ↔ Semper
143p · 4.3xT
Vision AI Model Insight
Busiest connection: Antonio Caracciolo ↔ Simone Canestrelli (322 passes). Most dangerous per pass: Mattéo Tramoni ↔ Samuele Angori (0.09 xT/pass over 95 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Pisa had the ball
Every touch across 468 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Pisa 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
13862
ACTIONS
Carries
the ball moved with a player
3069
ACTIONS
Vision AI Model Insight
Their single busiest zone is the centre of the defensive third (13.0% 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: 33% defensive, 47% middle, 20% 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. Pisa leaned on their right (42%). The bars under the pitch put the league’s share beside theirs.
Pisa
36%22%42%
League
38%23%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. Pisa made 1120 this season (29.5 a match); 32% came into the right 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
296
7.8
26%
28%
Left half-space
153
4.0
14%
15%
Centre
120
3.2
11%
13%
Right half-space
198
5.2
18%
15%
Right wing
353
9.3
32%
28%
Build-up2 sections
Build-Up — the pass map
The football question
How does Pisa 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.
4716build-up passes attempted
75%completed
30%reach the middle third
3%go long into the final third
Pass types
1606CB · 45%
358Long Wide · 10%
74Long Central · 2%
1110Wide → FB · 31%
387Central · 11%
Sequence success — build-up
1014build-up sequences this season
7%succeed — reach the next third or a shot
46%turned over with nothing to show
CB1606 · 45%
Long Wide358 · 10%
Long Central74 · 2%
Wide → FB1110 · 31%
Central387 · 11%
◆ Vision AI Insight
Pisa build predominantly down the left, with Caracciolo as the fulcrum (564 build-up passes). Only 33% 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 (230×).
Pass Explorer
Every pass of Pisa’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. 1492 progressive passes across 38 matches (39.3/game).
Origin lane
Right wing
30%
Right half-space
12%
Central
21%
Left half-space
10%
Left wing
28%
Progression is right-dominant: 42% right side · 21% central · 37% left.
Who generates it
Samuele Angori
176 · 12%
Adrian Semper
174 · 12%
Mehdi Léris
123 · 8%
Simone Canestrelli
114 · 8%
Michel Aebischer
106 · 7%
Top two — Samuele Angori & Adrian Semper — account for 23% of all progression.
PROGRESSION
39.3 prog passes/game
mostly right
→
PENETRATION
29% reach final third
21% reach the box
→
THREAT
the other 71% is recycled
progress ≠ danger
What came of it.29% of progressive passes reached the final third and 21% the box; the rest was recycled in front of the block. 23% of the progression ran through two players, mostly down the right 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 Pisa 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.
6492progression passes attempted
80%completed
16%break into the final third
14%go backward into the defensive third
Pass types
1762CB · 34%
245Long Wide · 5%
44Long Central · 1%
2366Wide → FB · 46%
778Central · 15%
Sequence success — progression
1743progression sequences this season
25%succeed — reach the next third or a shot
46%turned over with nothing to show
CB1762 · 34%
Long Wide245 · 5%
Long Central44 · 1%
Wide → FB2366 · 46%
Central778 · 15%
◆ Vision AI Insight
Pisa progress predominantly down the left, with Aebischer the busiest midfield outlet (834 progression passes). Only 16% of passes that start in midfield actually break the final-third line — the rest (70%) is recycled back into midfield or (14%) 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 → LW mid (265×) — 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)
15%
Progressive
1%
Neutral / sideways
52%
Safe / backward
32%
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.
Where does Pisa actually progress the ball with their feet, not a pass?
686 progressive carries this season across the whole squad (23% of 2928 tracked carries total), grouped into up to 4 spatial patterns by where each carry starts and ends together — not just its origin zone. Median 15m, longest 63m. Most active carrier: Aebischer (84). Filter to one player below.
First (217)Second (203)Third (135)Fourth (131)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 Pisa'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.
364shots
38.6xG
0.11xG per shot
23big chances (0.3+ xG)
25goals
#22key passes / game in the league
#16box entries / game in the league
Kind of attack, then how the shot was set up
Shots
Goals
xG
xG / shot
Attacking transition26% of shots
94
6
10.07
0.11
Cross
14
1
1.92
0.14
Cut-back
5
2
0.86
0.17
Long ball
7
1
1.05
0.15
Pass into the box / short pass
37
1
3.31
0.09
Own creation (carry, dribble, rebound)
31
1
2.94
0.09
Settled attack54% of shots
197
9
18.05
0.09
Cross
52
2
5.49
0.11
Cut-back
15
2
1.50
0.10
Long ball
10
0
0.75
0.07
Pass into the box / short pass
71
1
6.54
0.09
Own creation (carry, dribble, rebound)
49
4
3.78
0.08
Set piece20% of shots
73
10
10.45
0.14
Corner
62
4
4.79
0.08
Free kick
4
0
0.11
0.03
Penalty
7
6
5.56
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
Idrissa Touré
18
3.48
0
Mattéo Tramoni
21
2.55
2
Samuele Angori
24
2.31
1
Stefano Moreo
22
2.19
1
Mehdi Léris
22
2.15
3
Who takes them
Player
Shots
xG
Goals
M'Bala Nzola
28
5.57
3
Stefano Moreo
52
5.45
7
Henrik Meister
20
3.60
2
Mattéo Tramoni
28
2.82
2
Idrissa Touré
29
2.53
1
Vision AI Model Insight
The biggest source of Pisa's chances, by xG, is settled attack (18.1 of 38.6 xG, 197 of 364 shots), mostly pass into the box / short pass. 94 of the 364 shots (26%) came within 15 seconds of winning the ball. 73 of the 364 shots came from set pieces; 25 goals from 38.6 xG (-13.6).
Chance Creation — the pass map
The football question
How does Pisa 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
18CB · 7%
14Long Wide · 6%
39Long Central · 15%
64Wide → FB · 25%
119Central · 47%
Sequence success — final-third
952final-third sequences this season
19%succeed — produce a shot
45%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
CB18 · 7%
Long Wide14 · 6%
Long Central39 · 15%
Wide → FB64 · 25%
Central119 · 47%
Who creates — volume × threat
38Angori
32Aebischer
28Tramoni
27Léris
22Moreo
19Touré
15Akinsanmiro
254key passes #22 of 23
10.7box entries/game #16 of 23
24.5final-3rd entries/game #23 of 23
1.02xG/game #18 of 23
25goals #19 of 23
-13.6finishing vs xG #23 of 23
◆ Vision AI Insight
Pisa lean left — 41% of their key passes come from that flank and its half-space (105 of 254), most often from Angori (28). They funnel chances into the c of the final third, most often via LW att → C att (45 key passes, most often from Angori). Angori is the primary source overall. They generate 1.02 xG a game and finish it wasteful — they under-perform their xG, led by Stefano Moreo (7G), M'Bala Nzola (3G), Mattéo Tramoni (2G).
Crosses & Cutbacks — squad-wide
The question
How does Pisa deliver into the box from wide areas, and what comes of it?
602 crosses: 193 found a team-mate (32%), 72 led to a shot (12%). 79 cut-backs: 33 found a team-mate (42%), 23 led to a shot (29%). 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 Pisa actually cross from?
602 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. 22% come from one territory, the advanced left wing; 9 come from the half-spaces and 0 from the centre.
Territory
Crosses
Share
Led to a shot
advanced · left wing
134
22%
22
advanced · right wing
132
22%
12
byline · right wing
131
22%
16
byline · left wing
107
18%
16
deep · right wing
47
8%
1
deep · left wing
42
7%
3
byline · left half-space
3
0%
0
advanced · right half-space
2
0%
1
advanced · left half-space
2
0%
1
deep · right half-space
1
0%
0
deep · left half-space
1
0%
0
Finishing3 sections
Shot Map
364 shots for 38.6 xG (1.02/game, #18 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Moderate attack. 9.6 shots/game at 0.106 xG/shot. Box entries 11/game (#16). Threat created 9.0 xT/game (#17).
Goal Sequences
The move behind each of Pisa’s 26 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 — 26 goals traced.
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Pisa scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
15 · 60%
Set pieces
4 · 16%
Penalties
6 · 24%
By finish
Right foot
14 · 56%
Left foot
6 · 24%
Header
5 · 20%
Vision AI Model Insight
25 goals scored. 60% come in open play; set pieces add 16%. 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
1038
Failed forward pass
769
Failed take-on
325
Lost in the defensive third
1181
Their weakest zone is the right wing in the attacking third: 43% of 874 pass attempts there are lost (377 times). Separately, 30% 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 Pisa 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.
45
Pressing Index /100 · average
Intensity54
PPDA, high-press share, high-zone actions
Height43
how high up the pitch they defend
Effectiveness41
high recoveries & high-regain share
Disruption39
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
20%
RHS
19%
C
23%
LHS
20%
LW
18%
By third (high / mid / low regain)
Def 51%
Mid 35%
Att 14%
Read
Ranked #16 of 23 for press intensity, this is a high press. Note the tension: 51% of their raw defensive actions still occur in their own third — a possession effect, not a passive one. Dominating the ball (21% high-press share) means that when they do defend, it is often deep. Of recoveries, 53% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#16/23
lower = more intense; rank is what matters
Defensive actions / game
139
#6/23
High-press share
21%
#8/23
def actions won high up
Defensive-action height (0–100)
37.2
#13/23
avg pitch height of actions
High recoveries / game
20.3
#14/23
ball won in mid+att third
High-recovery share
53%
#13/23
share of recoveries won high
Opponent completion allowed
83%
#18/23
lower = more disruptive
Opponent progressive allowed
9.1%
#10/23
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 Pisa win it back with a defensive action?
Counted over the 1193 opposition possessions that Pisa 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 Pisa step in. Pisa win it after 6.0 opponent passes in the first half-hour and after 4.6 after the hour mark (sooner).
PASSES THEY GET
5.5passes
median 3 · before Pisa win it
TIME THEY KEEP IT
16sec
median 8s · 31.4 wins per game
How many passes the opponent got in before the ball was won
41%
25%
17%
18%
0–2 passes3–5 passes6–9 passes10+ passes
Through the match — every 15 minutes
0–15′
6.5
19s
15–30′
5.4
16s
30–45+′
6.5
19s
45–60′
5.5
16s
60–75′
5.6
17s
75–90+′
3.8
11s
average passesaverage seconds
Phases of play
Every moment of the match read twice — what Pisa 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.
6,313phase segments analysed
5.0smedian time before the opposition engage
2.0their passes per defensive action when pressed
#18of 20 for share of defending spent pressing high
High press 4.9%Mid block 11.0%Low block 53.8%Unopposed 30.2%
What opponents do against Pisa
The mirror image, and the part no other section can show: whether teams come
out to press Pisa 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 11.1%Mid block 12.6%Low block 46.0%Unopposed 30.3%
Which phases actually produce
Phase
Segments
Avg length
Avg actions
Ends in shot
Turned over
Build-up
2,195
3.9s
2.6
0.2%
53.8%
Progression
2,610
5.1s
3.2
0.5%
54.5%
Chance creation
1,389
4.6s
2.8
23.4%
61.8%
Attacking transition
119
6.7s
4.1
7.6%
41.2%
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
976
0.1%
progression
810
0.5%
build_up → progression
401
0.0%
chance_creation
398
32.2%
progression → chance_creation
340
23.2%
build_up → progression → chance_creation
174
24.1%
Attitude in each third
Every other style number here says how much Pisa 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 Pisa 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) 4,716 passes
nothing unusual in this zone
Width of use-0.2320.53
Wide-channel share-0.140.30
Side bias-0.16-0.43
Pass length+0.6024.86
Long-ball share+0.820.31
Forward gain per pass+0.6814.40
Backward-pass share-0.600.17
Deep-pass share+0.800.36
Completion-0.660.74
Seconds between passes-0.023.32
Side used
left 26% · central 47% · right 28%
Progression (middle third) 6,492 passes
more direct, attacking the next line, riskier
Width of use-0.0225.53
Wide-channel share+0.150.41
Side bias-0.52-1.99
Pass length+0.6218.09
Long-ball share+0.970.14
Forward gain per pass+0.884.94
Backward-pass share-0.420.31
Deep-pass share+0.820.20
Completion-0.870.79
Seconds between passes+0.093.24
Side used
left 32% · central 31% · right 37%
Final third 2,654 passes
attacking the next line, riskier, trying to break lines
Width of use+0.5132.86
Wide-channel share+0.330.61
Side bias-0.36-2.99
Pass length+0.8716.82
Long-ball share+1.060.15
Forward gain per pass+1.202.63
Backward-pass share-0.830.33
Deep-pass share+1.070.13
Completion-1.100.61
Seconds between passes+0.353.66
Side used
left 39% · central 14% · right 47%
Reference measured across roughly 3,500 match-teams
in this competition, per third, so the comparison is with Pisa'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 Pisa 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 share20%
#2 of 23 · reaches final third in ≤3 passes
Patient build-up share20%
#20 of 23 · spells of 6+ passes
Tempo (possession length)14.5s
#4 of 23 · shorter = faster tempo
Passes per possession3.6
#20 of 23
Counter-attack shots /game0.76
#22 of 23 · shot within 12s of a regain in own half
Press→shot /game2.58
#17 of 23 · shot within 8s of a high regain
Speed to final third after regain11.4s
#5 of 23 · lower = faster break
Sequence success — attacking transition
119attacking transition sequences this season
20%succeed — produce a shot
43%turned over with nothing to show
Sequence success — defensive transition
352defensive transition sequences this season
59%succeed — reach the next third or a shot
12%turned over with nothing to show
Vision AI Model Insight
Pisa are a direct, fast-break side: 20% of possessions reach the final third in 3 passes or fewer (#2 of 23), against 20% built patiently over 6+ passes (#20 of 23). Winning the ball back leads to a shot inside 12 seconds 0.76 times a game (#22), and a high regain converts to a shot within 8 seconds 2.58 times a game (#17 of 23) — not yet a major source of chances.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Pisa? 1880 opponent progressive passes and 548 shots faced (54.8 xG against) across the season.
Opponent threat by lane (attacking into Pisa)
Right wing
33%
Right half-space
14%
Central
15%
Left half-space
13%
Left wing
26%
Where the danger came from. Opponents generated most of their threat through the right wing (33% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Pisa actually come from — open play, dead balls, and who supplies them?
Every goal Pisa conceded across the loaded matches — the opponent's shots in Pisa'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 (385 total)
By situation
Open play
57 · 81%
Set pieces
8 · 11%
Penalties
5 · 7%
Vision AI Model Insight
70 goals conceded. 81% come in open play; set pieces account for only 11%, so dead-ball defending is not the main issue. 13% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the centre of the attacking third (21% of key passes faced) — that is the zone to shut off.
Context
Shape and tactics
Set pieces, strengths and weaknesses, and who they resemble.
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.
How much of the goal threat is manufactured from dead balls — a route to goal that bypasses their open-play mechanism entirely.
Open play
15 g · 28.1 xG
Set pieces
4 g · 4.9 xG
Penalties
6 g
16% of goals come from set pieces (4 of 25), worth 4.9 xG from 66 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Pisa's corners go?
135 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 (75)
Delivered into the box 91%Short 9%
Left side (60)
Delivered into the box 95%Short 5%
Where opponents attack Pisa from set pieces
99 shots from opponent corners against Pisa, 7 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 (53)
Shot 53Goals 1
Left flag (46)
Shot 46Goals 6
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
none stand out
Weaknesses (bottom-third vs league)
shots /game — 9.58 (4th pct)
field tilt % — 38.91 (9th pct)
pass retention % — 74.64 (13th pct)
xG conceded /game — 1.44 (17th pct)
xG created /game — 1.02 (22th 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.
Hellas Verona
92%
Lecce
89%
Torino
89%
Cremonese
88%
Parma Calcio 1913
86%
Performance vs Opponent Styles
The question
Not just how Pisa 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 Pisa's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (12m)
0.58
2.17
0.67
vs mid-block opponents (12m)
1.25
1.67
0.67
vs low-block opponents (14m)
0.29
1.79
0.14
Behaviour — how Pisa actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
70%
23%
37
8.1
9.7
vs mid-block opponents
74%
20%
38
9.0
11.5
vs low-block opponents
76%
17%
42
9.8
10.8
Vision AI Model Insight
Facing a high press, retention drops to 70% vs 76% against a low block (6pt lower under pressure), and directness (long-ball share) sits at 23% when pressed vs 17% 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. Pisa are territorially-dominated with a aggressive high-press.
Their attack creates 1.02 xG a game and they concede 1.44 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 Pisa’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.
Pisa
across 38 matches this season
Final-third entriesvs Parma Calcio 1913 · 0-1 · 2025-12-0861avg 29
Threat from passingvs Atalanta · 1-1 · 2026-01-169.90avg 5.68
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 Pisa’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).
+14.4on-ball value, 12 matches
Where the value came from
Passes4537 actions+6.37
Carries924 actions-0.98
Dribbles151 actions+0.45
Shots99 actions+5.00
Ball wins690 actions+3.54
Most on-ball value (OBV)
Actions
OBV
per 100
Antonio Caracciolo
571
+2.00
+0.35
Stefano Moreo
352
+1.63
+0.46
Michel Aebischer
668
+1.40
+0.21
Samuele Angori
592
+1.38
+0.23
Simone Canestrelli
608
+0.96
+0.16
Filip Stojilkovic
92
+0.82
+0.89
Nícolas
172
+0.71
+0.41
Ebenezer Akinsanmiro
307
+0.71
+0.23
Biggest single moves
OBV
1 Stefano Moreo · shot
+0.822
2 Antonio Caracciolo · shot
+0.573
3 Michel Aebischer · pass
+0.395
4 Gabriele Piccinini · shot
+0.342
5 Ebenezer Akinsanmiro · take-on
+0.328
6 Rosen Bozhinov · shot
+0.307
Set Pieces by Player
Who delivers Pisa’s dead balls and who finishes them this season. 135 corners taken, most by Samuele Angori (54); 66 shots from corners and free kicks, 4 goals, led by Antonio Caracciolo (1 goals, 1.30 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
Samuele Angori
54
48 (89%)
2
—
0.06
2
—
Stefano Moreo
—
—
14
1
0.75
—
2/2
Mattéo Tramoni
31
24 (77%)
3
1
0.15
—
1/1
Mehdi Léris
20
17 (85%)
5
—
0.19
—
—
Michel Aebischer
20
16 (80%)
3
—
0.09
1
—
Antonio Caracciolo
—
—
9
1
1.30
—
—
Simone Canestrelli
—
—
8
1
0.98
—
—
Idrissa Touré
—
—
7
—
0.45
—
—
Juan Cuadrado
7
7 (100%)
2
—
0.05
1
1/1
Mateus Lusuardi
—
—
4
—
0.13
—
—
M'Bala Nzola
—
—
1
—
0.10
—
2/3
Giovanni Bonfanti
—
—
2
—
0.13
—
—
Gabriele Piccinini
1
1 (100%)
1
—
0.21
—
—
Isak Vural
1
1 (100%)
1
—
0.02
—
—
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
Samuele Angori
M
2695
1.27
64
34.0
Mehdi Léris
M
1981
1.23
48
22.0
Mattéo Tramoni
M
1652
1.53
42
15.5
Michel Aebischer
M
3021
0.95
38
33.3
Idrissa Touré
M
2450
0.70
34
17.3
Stefano Moreo
F
2402
0.82
28
10.8
Juan Cuadrado
M
578
2.02
25
12.5
Simone Canestrelli
D
3355
0.21
18
30.5
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Antonio Caracciolo
D
3214
583
71
50
115
Simone Canestrelli
D
3355
546
40
33
97
Idrissa Touré
M
2450
534
43
23
111
Michel Aebischer
M
3021
394
65
37
169
Stefano Moreo
F
2402
376
17
22
78
Mehdi Léris
M
1981
361
67
22
106
Samuele Angori
M
2695
320
46
22
101
Arturo Calabresi
D
1568
239
19
19
57
Full Squad Data
Every player with 100+ minutes (29 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Simone Canestrelli
D
37
3355
1
1.7
8
114
546
30.5
Antonio Caracciolo
D
35
3214
2
2.1
0
78
583
22.1
Michel Aebischer
M
35
3021
1
0.8
32
106
394
33.3
Samuele Angori
M
35
2695
0
1.4
38
176
320
34.0
Idrissa Touré
M
32
2450
1
2.5
19
100
534
17.3
Stefano Moreo
F
37
2402
7
5.4
22
35
376
10.8
Adrian Semper
G
25
2358
0
0.0
0
174
46
32.5
Mehdi Léris
M
34
1981
2
1.8
27
123
361
22.0
Mattéo Tramoni
M
27
1652
2
2.8
28
65
191
15.5
Henrik Meister
F
28
1588
2
3.6
3
6
135
1.5
Arturo Calabresi
D
26
1568
0
0.3
3
76
239
16.8
Marius Marin
M
23
1318
0
0.1
1
44
193
11.9
Gabriele Piccinini
M
25
959
0
2.1
7
13
116
3.0
Malthe Højholt
M
17
890
0
0.4
2
14
91
4.1
Isak Vural
M
15
789
0
0.6
3
11
77
3.8
Rosen Bozhinov
D
9
699
0
0.3
4
33
97
9.0
Filip Stojilkovic
F
13
682
0
2.0
1
3
25
0.8
Simone Scuffet
G
7
665
0
0.0
0
59
14
10.8
Felipe Loyola
M
11
594
1
0.6
3
11
71
3.0
Juan Cuadrado
M
19
578
1
1.1
13
57
78
12.5
Nícolas
G
6
563
0
0.0
0
41
13
8.0
Rafiu Durosinmi
F
12
525
1
0.8
3
4
69
1.1
Raúl Albiol
D
8
520
0
0.1
3
21
111
6.5
Giovanni Bonfanti
D
9
514
0
0.4
3
30
85
6.6
Francesco Coppola
D
7
488
0
0.1
0
31
70
6.3
Mateus Lusuardi
D
3
205
0
0.1
0
6
34
1.8
Lorran
M
9
167
1
0.6
1
7
22
1.3
Samuel Iling-Junior
M
5
122
0
0.0
1
5
10
0.8
Daniel Denoon
D
2
122
0
0.0
0
2
14
0.2
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.
Simone Canestrelli
Stopper / marker · Defender
minutes3355
goals · xG1 · 1.7
prog passes /903.1
key passes /900.21
def actions /9014.6
pass accuracy78%
Antonio Caracciolo
Stopper / marker · Defender
minutes3214
goals · xG2 · 2.1
prog passes /902.2
key passes /900.00
def actions /9016.3
pass accuracy84%
Michel Aebischer
Ball-winner / destroyer · Midfielder
minutes3021
goals · xG1 · 0.8
prog passes /903.2
key passes /900.95
def actions /9011.7
pass accuracy84%
Samuele Angori
Box-to-box midfielder · Midfielder
minutes2695
goals · xG0 · 1.4
prog passes /905.9
key passes /901.27
def actions /9010.7
pass accuracy66%
Idrissa Touré
Ball-winner / destroyer · Midfielder
minutes2450
goals · xG1 · 2.5
prog passes /903.7
key passes /900.70
def actions /9019.6
pass accuracy62%
Stefano Moreo
Ball-winner / destroyer · Midfielder
minutes2402
goals · xG7 · 5.4
prog passes /901.3
key passes /900.82
def actions /9014.1
pass accuracy57%
Adrian Semper
Goalkeeper · Goalkeeper
minutes2358
goals · xG0 · 0.0
prog passes /906.6
key passes /900.00
def actions /901.8
pass accuracy65%
Mehdi Léris
Box-to-box midfielder · Midfielder
minutes1981
goals · xG2 · 1.8
prog passes /905.6
key passes /901.23
def actions /9016.4
pass accuracy66%
Mattéo Tramoni
Ball-winner / destroyer · Midfielder
minutes1652
goals · xG2 · 2.8
prog passes /903.5
key passes /901.53
def actions /9010.4
pass accuracy66%
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: shots /game (4th pct)
Sign a shot-taking forward to raise shot volume. The data flags this because shot volume is low (9.58, 4th percentile vs the league).
Need — bottom-third: field tilt % (9th pct)
Sign a possession-controlling midfielder to win the territorial battle. The data flags this because they get pinned back (38.91, 9th percentile vs the league).
Need — bottom-third: pass retention % (13th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (74.64, 13th percentile vs the league).