ZED FC

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

Expected goals piling up over 32 matches: ZED FC 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 (-2.7 xG). Hover a point for that match.

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.

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).

Field tilt = share of final-third touches between the two sides across ZED FC'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; ZED FC highlighted. Hover any dot for the team.

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.

Every touch across 314 matches. Brighter means more touches.

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.

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. ZED FC leaned on their right (41%). The bars under the pitch put the league’s share beside theirs.

Every completed pass or carry that took the ball from outside the final third into it, by the channel it arrived in. ZED FC made 1137 this season (35.5 a match); 27% 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.

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.

Every pass of ZED FC’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.

Not just how many progressive passes, but where they start, who plays them, and whether they actually penetrate. 1359 progressive passes across 32 matches (42.5/game).

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.

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.

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

479 progressive carries this season across the whole squad (19% of 2573 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 54m. Most active carrier: Saad (53). Filter to one player below.

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.

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.

348 shots for 32.7 xG (1.02/game, #11 in the league). Click an area of the box to see who shoots from there; filter by outcome, player or match.

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

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.

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.

Every pressing metric, ranked in the league

The report flipped: where do opponents create their threat against ZED FC? 1334 opponent progressive passes and 363 shots faced (35.5 xG against) across the season.

Opponent threat by lane (attacking into ZED FC)

Every goal ZED FC conceded across the loaded matches — the opponent's shots in ZED FC'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.

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

Team archetype: Reactive low-block counter. Their closest stylistic matches in the league (cosine similarity on style metrics) — sides that play a similar way.

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

Results

Behaviour — how ZED FC actually play against each

For each of ten match numbers, the one match this season that departed furthest from ZED FC’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.

Who delivers ZED FC’s dead balls and who finishes them this season. 119 corners taken, most by Mahmoud Saber (45); 58 shots from corners and free kicks, 4 goals, led by Ali Gamal (1 goals, 0.69 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.

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.

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

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

Every player with 100+ minutes (33 players).

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

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.