Sportra Intelligence: How We Gather, Process, and Show Football Data
Sportra's data layer — from collection and aggregation to team, player, and match intelligence, plus pre-match predictions fans can trust.
Sportra Intelligence is Sportra's data layer: we collect match and season records, normalize and aggregate them into consistent structures, then derive comparisons, scores, and summaries you see in the app.
Nothing is hand-counted from video — results come from the datasets we maintain and update.
The previews below use fixed sample data (Manchester United, Bruno Fernandes, Manchester United vs Bayern Munich). On the live site, the same views load for the fixture, club, or player you open.
Data pipeline
Sportra Intelligence runs in four steps for every statistics tab:
- Gather — Sportra loads fixture, team, and player datasets when you open a page (match detail, club season, or player season). There is no background interval refresh for those views.
- Process — Values are cleaned (percentages, ranges, missing fields) so numbers can be compared side by side.
- Aggregate — Season rows, home/away splits, minute buckets, and team-vs-team pairs are rolled up into the blocks shown in the UI.
- Present — Base totals appear in tables and bars; Sportra Intelligence adds derived metrics, scores, and short narratives on top.
| Layer | What you see |
|---|---|
| Base data | Shots, passes, cards, season totals, home/away splits — as gathered for that page |
| Sportra Intelligence | Derived rates, 0–100 scores, archetypes, impact ranks, and match comparisons |
Team and player pages use the league and season you select. Match pages use that fixture only.
Overview
The same intelligence layer powers the Statistics, Players, and Predictions tabs on matches, plus Statistics on team and player profiles. Where the dataset includes a field, we show it; where it does not, we omit the derived metric rather than guess.
Labels such as archetypes, impact leaders, and comparison winners are Sportra definitions for reading the game on Sportra — they are not official competition statistics.
Team statistics — Manchester United
Where: Team page → Statistics tab.
Season totals are grouped into blocks (fixture record, goals, minutes, formations, and more). Sportra Intelligence turns those blocks into charts, 0–100 scores, traits, and an archetype summary. Full season tables remain available under Full statistics tables when present.
Season data blocks
| Block | Content |
|---|---|
| Fixture record | Played, wins, draws, losses — home, away, and total |
| Goals | Scored and conceded — totals and averages per game |
| By minute | Goals and cards by time window (e.g. 0–15, 46–60) |
| Goal thresholds | Over/under counts (e.g. over 2.5 goals) |
| Formations | Formation usage counts |
| Form & records | Recent W/D/L, biggest wins/losses, clean sheets, streaks |
Season intelligence (0–100)
- Home fortress — home attack share vs an even split, plus home goals vs home conceded
- Away attack — away goal share vs an even split
- Defensive reliability — clean sheet rate blended with goals conceded per game
- Match chaos — share of high-scoring games from threshold data
- Form momentum — recent form string weighted toward wins
- Tactical flexibility — distinct formations used relative to matches played
Traits and archetype
Traits are rule-based tags (for example, a late-finisher tag when a high share of goals come after 76′). The archetype headline (such as Home-Dominant Attack) summarizes the season profile for quick reading.
Sample output for Manchester United includes traits like Fast starter, Second-half surge, Low chaos, formation identity (4-2-3-1 in 84% of matches), clean-sheet rate, and form momentum (e.g. 18W 12D 8L in last 38 — 1.74 PPG). Season charts cover goals per game (home/away/total), home vs away personality, match-phase goals, discipline by minute, tactical identity, and goal markets.
Player statistics — Bruno Fernandes
Where: Player page → Statistics tab.
Season output is merged into one profile: hero metrics, card-style attributes, derived rates, then a full stat breakdown. Non-penalty goals are shown as total goals minus penalties scored when both exist.
Stat groups
Appearances, shooting, goals, passing, tackling, duels, dribbling, fouls, cards, and penalties — combined for the selected league and season. If multiple rows exist for the same competition, counting stats are summed and the highest rating is kept.
Derived categories
| Category | Examples | How it is calculated |
|---|---|---|
| Goal efficiency | Goals per 90, non-penalty goals per 90, shot accuracy, conversion | Per 90 and shot/goal ratios |
| Chance creation | Assists per 90, key passes per match, chance creation index | (Key passes × 2) + assists |
| Ball carrying | Dribbles per 90, dribble success rate | Successful dribbles ÷ attempts |
| Pressure & discipline | Fouls drawn per 90, fouls per yellow | Volume and discipline proxy |
| Defensive work | Tackles per 90, duel win rate, defensive actions per 90 | Tackles + blocks + interceptions |
| Goalkeeping | Saves per 90, conceded per 90, save % | Saves ÷ (saves + conceded) |
| Involvement | Starting rate, minutes per appearance | Lineups ÷ appearances; minutes ÷ appearances |
Some tiles include an intensity bar: value compared to a fixed Sportra benchmark, capped at 100 — a visual cue, not a league percentile.
Card attributes (0–99)
Scaled from season output — map to fantasy, comparisons, or scouting cards: Attack, Vision, Control, Precision, Pressure, Defense, Engine, Discipline, Flair. Each rating is scaled 0–99 relative to elite benchmarks for the metric mix — not an absolute world ranking.
Sample profile: Wide creator — 7.6 avg rating, 11 goals, 9 assists, 34 apps, 2980′ minutes, Midfielder.
Match statistics — Manchester United vs Bayern Munich
Where: Match page → Statistics tab.
Home and away team totals are paired stat-by-stat, grouped into six themes, then extended with Sportra Intelligence derived rows (efficiency, pressure, gameplay ratings).
Comparison groups
| Group | Examples | Notes |
|---|---|---|
| Attacking | xG, shots, shots on target, inside/outside box, offsides | |
| Possession & passing | Possession %, passes, pass accuracy | |
| Set pieces | Corners | |
| Defensive & goalkeeping | Blocks, saves, goals prevented | |
| Discipline | Fouls, yellow and red cards | Lower is better on comparison bars |
| Other | Any remaining stat types | Readable labels |
Derived match metrics
- Shot accuracy — shots on target ÷ total shots
- xG per shot — expected goals ÷ total shots
- Inside box ratio — inside-box shots ÷ total shots
- Attack pressure — (in-box shots × 2) + corners + shots on target + blocks faced
- Gameplay ratings — aggression, control, siege pressure, clinical index, defensive compactness, chaos factor
Comparison bars highlight the leading side; fouls and cards favour the lower value.
Tactical insights group scouting-style duels: shooting efficiency, tactical identity, pressure & control, defensive workload, and gameplay profile — each row compares both teams with share-of-pie visuals and edge labels.
Match player statistics
Where: Match page → Players tab.
Each player line from the match dataset is processed into a box score, derived rates, an impact score, optional badges, and team-level duel bars that sum both squads.
Per player
Minutes, rating, position, goals, assists, saves, cards — plus derived passing, duel, and discipline metrics for that appearance.
Impact score
- Outfield: rating, goals, assists, key passes, shots on target, tackles, interceptions, saves, and card penalties combined into one ranking score
- Goalkeeper: rating, saves, goals conceded, and passing volume
Badges mark standouts (best rating, playmaker, wall, defensive anchor, dribbler, attacking threat, risky player, captain). Team totals aggregate all players on each side for head-to-head bars.
Sample highlights: Bruno Fernandes leads ratings (8.4) with playmaker and captain badges; squad totals, lineup ratings, Sportra impact score ranking, and expandable full box scores for every player.
Predictions
Where: Match page → Predictions tab.
Pre-match outlook is built from processed season and head-to-head signals for both teams — win/draw/away shares, comparison bars, form, goal tendencies, and recent meetings. It is available before kickoff and does not update from live match events.
What the tab includes
- Written advice and outcome percentages (home, draw, away)
- Side-by-side comparison (form, attack, defence, goals, head-to-head, overall)
- Season and streak metrics per team
- Recent head-to-head fixtures when available
- Charts — outcome donut, profile radar, scoreline bars, season anchors, signal grids
Sample Match DNA: Defensive grind — model leans Manchester United, projected 1–1. Includes tempo, volatility, expected goals, tactical style, upset potential, draw risk, and model confidence. Outcome model shows win probabilities, goal expectancy, likely scorelines (Poisson), goals market, double chance, matchup profile, form & momentum, season record, matchup edges, goals profile, scoring reliability, extremes & streaks, and Sportra ratings (attack, defense, momentum, matchup edge, volatility, form index, H2H pull).
Calculation rules
Cleaning values
- Percentages are stored as plain numbers (58% → 58)
- Ranges such as 3–5 use the midpoint
- Missing values stay out of derived maths
Rates
- Per 90: (value ÷ minutes) × 90 when minutes > 0
- Per match: value ÷ appearances when appearances > 0
- Ratios: shot accuracy, conversion, duel win %, pass accuracy
Match comparisons
Higher is usually better; fouls and cards favour the lower total. Ties show as neutral.
Limits
- If a stat is missing from the dataset for that page, related derived metrics are not shown.
- Penalty shootout scores on match headers follow the PEN status and phase breakdown used elsewhere on Sportra.
- Match, team, and player detail pages show the dataset from when the page was loaded. To see updated statistics, reload the page — we do not poll upstream on a fixed interval for those tabs.
- Predictions reflect pre-match data only.
Sample data in this article is illustrative (Premier League · 2019–20). Live pages use the same views with Sportra data for your selected fixture, team, player, league, and season.
Explore Sportra Intelligence
Read the full interactive breakdown on the product:
sportra.app/sportra-intelligence