Combining every season — this one is larger, give it a moment.
Team reportEgyptian Premier League 2025/26
Tala'ea El-Gaish
A balanced-territory side, moderate-press out of possession, with a low-output attack. Currently #14 of 21 on 37 points (9-10-14, 21:34). Tactical profile below is built from 32 matches of ball-by-ball event data, a sample of the full season, contextualised against the league.
balanced-territorymoderate-presslow-output attack
L
L
D
D
W
L
W
L
W
W
L
D
L
L
L
37
points
#14 of 21 · 33 games
21:34
goals
-13 GD
9-10-14
record
W-D-L
1.12
points/game
#14 in the league
0.96
xG for/game
rank #13
1.07
xG against/game
rank #13
#9
press rank
of 21 · most aggressive
53%
field tilt
#5
Record, points, goals and league position come from the league table as it stands today — 33 games played, season in progress. Every tactical metric — xG, PPDA, field tilt, progression, zone maps — is measured from the 32 matches of detailed event data currently loaded, so those samples may not span the whole season.
In one read, what kind of team is Tala'ea El-Gaish and how good was the season?
Read. Tala'ea El-Gaish currently sit #14 of 21 on 37 points (9W-10D-14L, 1.12 pts/game), scoring 21 and conceding 34 for a goal difference of -13.
On the ball they are a balanced-territory team (53% field tilt, #5 in the league); off it they defend with a moderate-press (#9 of 21 for press intensity).
Across the 32 matches of event data, they create 0.96 xG/game (#13) and concede 1.07 (#13), a net of -0.11 xG/game — the underlying performance diverges from the actual goal difference.
Season Context — the league table
The question
Where did Tala'ea El-Gaish actually finish, and against whom?
The authoritative final table (full season), centred on Tala'ea El-Gaish.
#
team
P
W
D
L
GF
GA
GD
Pts
11
Ghazl El Mahalla FC
33
6
20
7
27
26
+1
38
12
Arab Contractors FC
33
7
17
9
28
31
-3
38
13
Modern Sport FC
33
7
16
10
26
34
-8
37
14
Tala'ea El-Gaish
33
9
10
14
21
34
-13
37
15
ENPPI
26
8
12
6
27
25
+2
36
16
Al-Ittihad Alexandria
33
9
9
15
29
38
-9
36
17
Ismailia Electricity Clu
33
7
11
15
35
53
-18
32
xG Race — the season, match by match
Expected goals piling up over 32 matches: Tala'ea El-Gaish 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 (-3.5 xG). Hover a point for that match.
Tala'ea El-GaishOpponents against Tala'ea El-Gaish
Tactical DNA
The football question
In five genes, what is Tala'ea El-Gaish'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.
60
Build-Up
possession control from the back
60
Progression
moving the ball upfield with threat
59
Creation
manufacturing chances
67
Press
winning the ball high & hard
38
Solidity
resisting the opponent's threat
Genetic identity
Tala'ea El-Gaish are defined most by their Press DNA (67/100 · strong at winning the ball high & hard), and least by their Solidity DNA (38/100). Percentiles vs the 21 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
62%
Possession
67%
Field tilt
67%
Disrupt
Central progression ~proxy
17%
Dribble tendency
50%
Progressive passes
54%
Finish
Final-third patience
50%
Shot quality
17%
Open-play xG
38%
Press
Forward press ~proxy
46%
High regains
38%
Pressing efficiency ~proxy
46%
Defend
Def-mid press ~proxy
54%
High line ~proxy
62%
PAdj defensive actions
50%
Tala'ea El-Gaish is defined most by Possess (65% in the league) and weakest on Finish (35%). Percentiles vs the 24 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 Tala'ea El-Gaish actually control, relative to the rest of the league?
Field tilt = share of final-third touches between the two sides across Tala'ea El-Gaish'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; Tala'ea El-Gaish highlighted. Hover any dot for the team.
Vision AI Model Insight
Tala'ea El-Gaish post 53% field tilt, ranking #5 of 21 in the league — comfortably above the league mid-point for territorial control, and their 1.16 points/game sits below the league-average return — a real disconnect: their territorial control isn't showing up on the scoreboard the way it should.
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
Awad ↔ Hamdy
725p · 19.3xT
Camacho ↔ Awad
384p · 10.9xT
Camacho ↔ Ouro-Agoro
376p · 8.1xT
Ouro-Agoro ↔ Awad
320p · -4.6xT
Hamdy ↔ Souissi
320p · 7.7xT
Mohareb ↔ Eldin
243p · 1.4xT
Tarek ↔ Mohareb
242p · 8.9xT
Eldin ↔ Zola
225p · 9.5xT
Eldin ↔ Camacho
196p · 9.9xT
Camacho ↔ Hamdy
177p · 5.1xT
Vision AI Model Insight
Busiest connection: Khaled Awad ↔ Ali Hamdy (725 passes). Most dangerous per pass: Ahmed Alaa Eldin ↔ Mohamed Camacho (0.05 xT/pass over 196 passes) — the combination that hurts opponents most when it fires, not just the one used most.
Touch Density — where Tala'ea El-Gaish had the ball
Every touch across 314 matches. Brighter means more touches.
Which Zones Do They Attack Through?
The question
Across the whole pitch, where does Tala'ea El-Gaish 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
12678
ACTIONS
Carries
the ball moved with a player
2600
ACTIONS
Vision AI Model Insight
Their single busiest zone is the right half-space of the middle third (10.7% 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, 48% 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. Tala'ea El-Gaish leaned on their right (45%). The bars under the pitch put the league’s share beside theirs.
Tala'ea El-Gaish
35%20%45%
League
38%24%38%
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. Tala'ea El-Gaish made 1186 this season (37.1 a match); 36% 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
9.2
25%
27%
Left half-space
149
4.7
13%
17%
Centre
136
4.2
11%
15%
Right half-space
174
5.4
15%
16%
Right wing
431
13.5
36%
25%
Build-up2 sections
Build-Up — the pass map
The football question
How does Tala'ea El-Gaish 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.
3910build-up passes attempted
72%completed
39%reach the middle third
3%go long into the final third
Pass types
1215CB · 43%
250Long Wide · 9%
42Long Central · 1%
1052Wide → FB · 37%
273Central · 10%
CB1215 · 43%
Long Wide250 · 9%
Long Central42 · 1%
Wide → FB1052 · 37%
Central273 · 10%
◆ Vision AI Insight
Tala'ea El-Gaish build predominantly down the right, with Camacho as the fulcrum (552 build-up passes). Only 42% of their build-up passes actually advance a third — the rest is lateral circulation, the hallmark of a side that builds forward quickly, progressing the ball more directly. Their single most-repeated pattern is C def → RHS def (131×).
Pass Explorer
Every pass of Tala'ea El-Gaish’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. 1435 progressive passes across 32 matches (44.8/game).
Origin lane
Right wing
33%
Right half-space
18%
Central
15%
Left half-space
12%
Left wing
22%
Progression is right-dominant: 51% right side · 15% central · 34% left.
Who generates it
Ahmed Alaa Eldin
187 · 13%
Ali Hamdy
164 · 11%
Khaled Awad
134 · 9%
Mohamed Camacho
97 · 7%
Amro Tarek
80 · 6%
Top two — Ahmed Alaa Eldin & Ali Hamdy — account for 24% of all progression.
PROGRESSION
44.8 prog passes/game
mostly right
→
PENETRATION
33% reach final third
20% reach the box
→
THREAT
the other 67% is recycled
progress ≠ danger
What came of it.33% of progressive passes reached the final third and 20% the box; the rest was recycled in front of the block. 24% 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 wingbalanced
Progression — the pass map
The football question
Once Tala'ea El-Gaish 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.
6081progression passes attempted
77%completed
20%break into the final third
14%go backward into the defensive third
Pass types
1033CB · 22%
289Long Wide · 6%
44Long Central · 1%
2621Wide → FB · 56%
679Central · 15%
CB1033 · 22%
Long Wide289 · 6%
Long Central44 · 1%
Wide → FB2621 · 56%
Central679 · 15%
◆ Vision AI Insight
Tala'ea El-Gaish progress predominantly down the left, with Hamdy the busiest midfield outlet (779 progression passes). Only 20% of passes that start in midfield actually break the final-third line — the rest (66%) 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 RHS mid → RW mid (239×) — 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)
18%
Progressive
1%
Neutral / sideways
50%
Safe / backward
32%
19% of passes are progressive-or-better; the remaining 81% keep possession without advancing it. A control-first side — safe in build-up, reliant on a few players for the incision.
Where does Tala'ea El-Gaish actually progress the ball with their feet, not a pass?
519 progressive carries this season across the whole squad (20% of 2600 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 59m. Most active carrier: Awad (69). Filter to one player below.
First (183)Second (136)Third (111)Fourth (89)grouped by carry pattern (start + end position), largest group first
startendown goal left, attacking →
Chance creation1 section
Chance Creation — the pass map
The football question
How does Tala'ea El-Gaish 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
30CB · 13%
13Long Wide · 5%
35Long Central · 15%
56Wide → FB · 24%
104Central · 44%
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
CB30 · 13%
Long Wide13 · 5%
Long Central35 · 15%
Wide → FB56 · 24%
Central104 · 44%
Who creates — volume × threat
24Awad
21Ouro-Agoro
19Zola
16Hamdy
16Mohareb
15Gabry
15Tarek
238key passes #9 of 21
10.9box entries/game #7 of 21
31.7final-3rd entries/game #9 of 21
0.96xG/game #13 of 21
21goals #19 of 21
-9.6finishing vs xG #20 of 21
◆ Vision AI Insight
Tala'ea El-Gaish lean right — 46% of their key passes come from that flank and its half-space (110 of 238), most often from Awad (23). They funnel chances into the c of the final third, most often via RW att → C att (41 key passes, most often from Zola). Awad is the primary source overall. They generate 0.96 xG a game and finish it wasteful — they under-perform their xG, led by Ismail Ouro-Agoro (5G), Islam Mohareb (3G), Karim Tarek (2G).
Finishing2 sections
Shot Map
355 shots for 30.6 xG (0.96/game, #13 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.
Low-output attack. 11.1 shots/game at 0.086 xG/shot. Box entries 11/game (#7). Threat created 10.5 xT/game (#9).
How Do They Score?
The question
Where do the goals actually come from — open play, dead balls, which foot?
Every goal Tala'ea El-Gaish scored across the loaded matches, broken down by how it was created and finished.
By situation
Open play
14 · 67%
Set pieces
5 · 24%
Penalties
2 · 10%
By finish
Right foot
7 · 33%
Left foot
11 · 52%
Header
3 · 14%
Vision AI Model Insight
21 goals scored. 67% come in open play, but 24% from set pieces — a genuine dead-ball weapon that bypasses the open-play build-up.
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
1045
Failed forward pass
681
Failed take-on
227
Lost in the defensive third
1078
Their weakest zone is the left wing in the attacking third: 44% of 663 pass attempts there are lost (292 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 Tala'ea El-Gaish 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.
63
Pressing Index /100 · strong
Intensity56
PPDA, high-press share, high-zone actions
Height67
how high up the pitch they defend
Effectiveness55
high recoveries & high-regain share
Disruption81
opponent completion & progression allowed
Every defensive action & where it happens
Where they win the ball back — by lane
RW
16%
RHS
21%
C
30%
LHS
20%
LW
14%
By third (high / mid / low regain)
Def 63%
Mid 32%
Att 5%
Read
Ranked #9 of 21 for press intensity, this is a mid block. 37% of defensive actions happen in the middle & attacking thirds, at an average height of 29. Of recoveries, 47% are won high up the pitch.
Every pressing metric, ranked in the league
metric
value
rank
meaning
PPDA (opp passes per def action)
—
#9/21
lower = more intense; rank is what matters
Defensive actions / game
91
#10/21
High-press share
10%
#9/21
def actions won high up
Defensive-action height (0–100)
29.8
#7/21
avg pitch height of actions
High recoveries / game
21.2
#8/21
ball won in mid+att third
High-recovery share
47%
#11/21
share of recoveries won high
Opponent completion allowed
71%
#6/21
lower = more disruptive
Opponent progressive allowed
10.9%
#2/21
of opp passes, lower = better
Honest limit — no transition timing
This source has no cross-event clock or possession sequences, so genuine transition metrics — 5-second counterpress, time-to-recover, press→shot within 10s, and xG/xT generated after a high regain — cannot be computed and are deliberately left out rather than estimated. Every number above is a direct read of recorded defensive actions and opponent passes.
Defending the box2 sections
Vulnerability Map — how opponents hurt them
The report flipped: where do opponents create their threat against Tala'ea El-Gaish? 1306 opponent progressive passes and 338 shots faced (34.1 xG against) across the season.
Opponent threat by lane (attacking into Tala'ea El-Gaish)
Right wing
23%
Right half-space
16%
Central
23%
Left half-space
15%
Left wing
22%
Where the danger came from. Opponents generated most of their threat through the central (23% of the danger conceded).
How Do They Concede?
The question
Where do the goals against Tala'ea El-Gaish actually come from — open play, dead balls, and who supplies them?
Every goal Tala'ea El-Gaish conceded across the loaded matches — the opponent's shots in Tala'ea El-Gaish'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 (216 total)
By situation
Open play
18 · 56%
Set pieces
8 · 25%
Penalties
6 · 19%
Vision AI Model Insight
32 goals conceded. 56% come in open play, and 25% from set pieces — a genuine defensive frailty at dead balls to fix on the training ground. 19% are headers — aerial defending is not where the damage comes from. Their supply line runs mainly through the right wing 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
14 g · 20.9 xG
Set pieces
5 g · 8.1 xG
Penalties
2 g
24% of goals come from set pieces (5 of 21), worth 8.1 xG from 91 shots. Set pieces are a secondary threat; the danger is in open play.
Where do Tala'ea El-Gaish's corners go?
158 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 (85)
Delivered into the box 94%Short 6%
Left side (73)
Delivered into the box 89%Short 11%
Where opponents attack Tala'ea El-Gaish from set pieces
42 shots from opponent corners against Tala'ea El-Gaish, 4 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 (21)
Shot 21Goals 4
Left flag (21)
Shot 21Goals 0
Tactical Strengths & Weaknesses
Strengths (top-third vs league)
field tilt % — 53.42 (76th pct)
shots /game — 11.09 (71th pct)
box entries /game — 10.91 (67th pct)
Weaknesses (bottom-third vs league)
none stand out
Style Archetype & Similar Teams
Team archetype: Reactive low-block counter. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.
Pyramids FC
28%
Petrojet
26%
Wadi Degla
26%
Arab Contractors FC
19%
Al Ahly FC
15%
Performance vs Opponent Styles
The question
Not just how Tala'ea El-Gaish 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 Tala'ea El-Gaish's own passing behaviour to the result.
Results
opponent type
goals for/g
goals against/g
points/g
vs high-pressing opponents (10m)
0.80
0.80
1.60
vs mid-block opponents (10m)
0.50
0.70
1.20
vs low-block opponents (12m)
0.67
1.42
0.75
Behaviour — how Tala'ea El-Gaish actually play against each
opponent type
retention
directness (long balls)
prog. passes/g
xT/g
box entries/g
vs high-pressing opponents
71%
21%
38
8.9
6.9
vs mid-block opponents
70%
18%
48
11.4
12.7
vs low-block opponents
74%
18%
47
11.2
12.8
Vision AI Model Insight
Facing a high press, retention drops to 71% vs 74% against a low block (3pt lower under pressure), and directness (long-ball share) sits at 21% when pressed vs 18% against a low block — a mild adjustment, not a wholesale change.
Scouting Summary — the team in brief
In brief. Tala'ea El-Gaish are balanced-territory with a moderate-press.
Their attack creates 0.96 xG a game and they concede 1.07 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 Tala'ea El-Gaish’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.
Tala'ea El-Gaish
across 32 matches this season
PPDAvs Modern Sport FC · 1-0 · 2025-09-1425.6avg 12.3
Defensive actionsvs Al Ahly FC · 2-1 · 2026-03-09137avg 91
Expected goalsat Ismailia Electricity Club · 2-2 · 2026-02-232.37avg 0.94
Final-third entriesvs Ghazl El Mahalla FC · 1-0 · 2026-05-0759avg 37
Progressive passesvs National Bank of Egypt · 1-0 · 2026-04-0925avg 45
Threat from passingvs El Gouna FC · 0-1 · 2025-10-0410.04avg 6.41
Pass accuracyvs El Gouna FC · 0-1 · 2025-10-0463%avg 72%
Field tiltvs Al Ahly FC · 2-1 · 2026-03-0928%avg 53%
Set Pieces by Player
Who delivers Tala'ea El-Gaish’s dead balls and who finishes them this season. 158 corners taken, most by Ghaith Al Madadha (35); 52 shots from corners and free kicks, 1 goals, led by Mohamed Atef (1 goals, 0.44 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
Ghaith Al Madadha
35
29 (83%)
2
—
0.11
—
—
Ismail Ouro-Agoro
—
—
9
—
0.56
—
2/2
Ali Hamdy
18
15 (83%)
3
—
0.11
1
—
Ahmed Abdel Rahman Zola
26
23 (88%)
—
—
0.00
—
—
Ragab Omran
18
16 (89%)
2
—
0.08
1
—
Ahmed Alaa Eldin
—
—
7
—
0.62
—
—
Mohamed Camacho
—
—
6
—
0.46
—
—
Mohamed Hany
10
10 (100%)
2
—
0.02
—
—
Ahmed Tarek
14
12 (86%)
—
—
0.00
—
—
Mostafa Khawaga
4
4 (100%)
3
—
0.10
1
—
Alpha Boubacar Keita
6
6 (100%)
2
—
0.06
1
—
Hamed Khaled El Gabry
11
9 (82%)
—
—
0.00
—
—
Karim Tarek
6
3 (50%)
1
—
0.03
—
—
Houssem Eddine Souissi
—
—
3
—
0.32
—
—
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
Khaled Awad
D
2532
0.85
33
30.3
Ahmed Abdel Rahman Zola
M
1148
1.49
37
17.2
Ismail Ouro-Agoro
F
2240
0.84
26
7.3
Ali Hamdy
M
2564
0.56
30
42.8
Islam Mohareb
F
1583
0.91
21
12.9
Ghaith Al Madadha
M
1199
0.98
23
11.0
Karim Tarek
M
1042
1.30
20
5.9
Hamed Khaled El Gabry
D
1217
1.11
17
10.6
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)
Alpha Boubacar Keita
FB
1314
26 (35%)
6 (33%)
Amro Tarek
FB
1664
17 (29%)
14 (50%)
Karim Tarek
W
1042
11 (36%)
18 (44%)
Mohamed Hany
W
569
13 (23%)
6 (33%)
Defensive Volume Leaders
Who does the defensive work — tackles, interceptions, recoveries.
player
pos
min
def actions
tackles
intercept
recoveries
Mohamed Camacho
D
2610
334
25
28
100
Ali Hamdy
M
2564
325
52
39
193
Ahmed Alaa Eldin
D
2371
277
33
30
84
Khaled Awad
D
2532
265
33
25
115
Amro Tarek
D
1664
180
32
17
66
Houssem Eddine Souissi
M
1454
146
36
8
64
Mohamed Shaaban
G
1546
136
0
0
111
Alpha Boubacar Keita
D
1314
119
15
9
79
Full Squad Data
Every player with 100+ minutes (28 players).
player
pos
apps
min
goals
xG
key P
prog
def
xT
Mohamed Camacho
D
29
2610
0
0.9
4
97
334
29.9
Ali Hamdy
M
31
2564
0
1.0
16
164
325
42.8
Khaled Awad
D
29
2532
0
0.5
24
134
265
30.3
Ahmed Alaa Eldin
D
28
2371
0
1.2
10
187
277
40.4
Ismail Ouro-Agoro
F
30
2240
5
7.7
21
34
97
7.3
Amro Tarek
D
23
1664
3
2.9
9
80
180
18.9
Islam Mohareb
F
25
1583
3
4.2
16
47
102
12.9
Mohamed Shaaban
G
18
1546
0
0.0
0
56
136
11.7
Houssem Eddine Souissi
M
24
1454
1
0.8
7
73
146
16.0
Alpha Boubacar Keita
D
22
1314
0
0.5
13
71
119
13.9
Hamed Khaled El Gabry
D
21
1217
0
0.9
15
46
111
10.6
Ghaith Al Madadha
M
24
1199
1
1.1
13
49
69
11.0
Ahmed Abdel Rahman Zola
M
22
1148
0
0.3
19
78
104
17.2
Karim Tarek
M
17
1042
2
2.1
15
36
61
5.9
Ahmed Tarek
M
16
844
0
1.0
11
38
53
9.2
Khaled Stouhi
D
12
843
0
0.1
1
43
89
13.1
Mohamed Atef
M
21
770
2
1.5
9
36
60
6.4
Omar Radwan
G
8
720
0
0.0
0
15
74
3.7
Mostafa Khawaga
M
13
650
0
0.3
4
35
57
8.5
Emad El-Sayed
G
7
627
0
0.0
0
11
51
2.8
Mohamed Hany
M
18
569
0
0.5
10
30
41
6.8
Yehia Mostafa
M
10
468
1
0.3
4
22
55
5.0
Khaled Abo Ziada
M
10
464
1
0.5
6
26
34
6.6
Ragab Omran
M
13
435
1
0.4
9
22
29
4.0
Fares Hatem
F
9
313
1
1.0
1
1
13
0.4
Ahmed Khaled
F
9
305
1
0.7
0
0
7
0.1
Dilson
F
6
146
0
0.6
1
1
4
0.2
Mahmoud Abdel Aziz
D
3
106
0
0.5
0
1
16
0.3
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.
Mohamed Camacho
Stopper / marker · Defender
minutes2610
goals · xG0 · 0.9
prog passes /903.3
key passes /900.14
def actions /9011.5
pass accuracy78%
Ali Hamdy
Box-to-box midfielder · Midfielder
minutes2564
goals · xG0 · 1.0
prog passes /905.8
key passes /900.56
def actions /9011.4
pass accuracy73%
Khaled Awad
Ball-playing defender · Defender
minutes2532
goals · xG0 · 0.5
prog passes /904.8
key passes /900.85
def actions /909.4
pass accuracy71%
Ahmed Alaa Eldin
Ball-playing defender · Defender
minutes2371
goals · xG0 · 1.2
prog passes /907.1
key passes /900.38
def actions /9010.5
pass accuracy72%
Ismail Ouro-Agoro
Box-to-box midfielder · Midfielder
minutes2240
goals · xG5 · 7.7
prog passes /901.4
key passes /900.84
def actions /903.9
pass accuracy69%
Amro Tarek
Stopper / marker · Defender
minutes1664
goals · xG3 · 2.9
prog passes /904.3
key passes /900.49
def actions /909.7
pass accuracy71%
Islam Mohareb
Box-to-box midfielder · Midfielder
minutes1583
goals · xG3 · 4.2
prog passes /902.7
key passes /900.91
def actions /905.8
pass accuracy71%
Mohamed Shaaban
Goalkeeper · Goalkeeper
minutes1546
goals · xG0 · 0.0
prog passes /903.3
key passes /900.00
def actions /907.9
pass accuracy58%
Houssem Eddine Souissi
Ball-winner / destroyer · Midfielder
minutes1454
goals · xG1 · 0.8
prog passes /904.5
key passes /900.43
def actions /909.0
pass accuracy80%
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 — below-average: xG created /game (38th pct)
Sign a higher-volume goalscorer or chance creator. The data flags this because the attack under-produces xG (0.96, 38th percentile vs the league).
Need — below-average: xG conceded /game (38th pct)
Sign a defensive organiser / shot-suppressing centre-back. The data flags this because too much xG is conceded (1.07, 38th percentile vs the league).
Need — below-average: pass retention % (43th pct)
Sign a secure ball-retaining midfielder. The data flags this because possession is turned over cheaply (72.11, 43th percentile vs the league).