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Home fortressHome attack vs home concession balance
Sportra
How we gather football data, process it, and show it on match, team, and player pages
Last updated: 21 May 2026
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.
Sportra Intelligence runs in four steps for every statistics tab:
| 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.
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.
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.
| 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 |
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 fortress) summarizes the season profile for quick reading.
Season intelligence
Much more aggressive at home; away performances lean conservative.
61% of goals scored at home — clear home attacking lift (40 home vs 26 away). Away blanking is more common (6 away vs 2 home).
Peak scoring window: 16-30′ (26% of goals for).
Yellow cards peak in the 76-90′ window (29% of cautions). Late-game discipline risk is elevated.
4-2-3-1 in 84% of matches — stable tactical identity.
13 clean sheets in 38 matches (0.95 conceded per game).
18W 12D 8L in last 38 — 1.74 PPG. Results swing match-to-match.
Low-chaos — controlled scorelines
Averaging 1.7 goals scored and 0.9 conceded per match this season.
Biggest results, streaks, and set-piece record.
Average scoring and concession rates for the season.
| Metric | Home | Away | Total |
|---|---|---|---|
| Goals per game | 2.1 | 1.4 | 1.7 |
| Conceded per game | 0.9 | 1.0 | 0.9 |
Played, wins, draws, and losses by venue
Where this team's results and goals are won
When they score and when they leak
Yellow and red cards across match phases
Formation usage this season
Over/under lines for team goals and opponent goals — full threshold matrix from Sportra.
Low-chaos — controlled scorelines
On the live site, expandable tables list fixture, goal, minute, and formation blocks for the selected season.
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.
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.
| 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.
Season intelligence
Profile as Midfielder: creator, high usage. Archetype: Wide creator. Season rating 7.6.
Scaled 0–99 from season output — map to fantasy, comparisons, or scouting cards.
Scouting profile
Per-90 rates, efficiency ratios, and Sportra indices from season totals.
How clinical and direct the player was in front of goal — volume, accuracy, and conversion.
Playmaking output: assists, key passes, and custom chance-creation signals.
Isolation threat and progressive carrying — volume plus success rate.
How often they draw fouls and stay out of trouble with cards.
Tackles, duels, and off-ball defensive contribution.
Minutes, availability, and how central they were to the team.
Every tracked category for this league and season, grouped by Sportra.
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).
| 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 | Shown with a readable label |
Comparison bars highlight the leading side; fouls and cards favour the lower value.
Visual snapshot of possession, chance quality, and shooting.
Possession
Expected goals (xG)
Total shots
Shots on target
Shot volume, box entries, and chance quality — who threatened the goal more.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
7 | Total shotsAll attempts including blocked and off-target. | 21Lead |
4 | Shots on target | 9Lead |
3 | Shots inside the box | 15Lead |
4 | Shots outside the box | 6Lead |
0.77 | Expected goals (xG)Quality of chances created — not just shot count. | 2.05Lead |
2Lead | OffsidesTiming of runs — high counts can mean aggressive lines. | 4 |
How each side moved the ball and shared control of the match.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
49% | Ball possession | 51%Lead |
555Lead | Total passes | 502 |
472Lead | Accurate passes | 421 |
85%Lead | Pass accuracy | 84% |
Dead-ball situations that can swing momentum and territory.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
3 | Corner kicks | 6Lead |
Blocks, saves, and how much danger was actually allowed.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
2 | Blocked shotsDefensive actions — also counts as part of attacking pressure faced. | 11Lead |
6Lead | Goalkeeper saves | 3 |
0.2 | Goals preventedKeeper performance vs expected — positive is above average. | 0.6Lead |
Physical intensity and referee involvement — fouls and cards.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
11 | Fouls | 9Lead |
2 | Yellow cards | 1Lead |
0 | Red cards | 0 |
Scouting-style duels — each row compares both teams, shows share of the pie, and who had the edge. Categories summarize who won more signals.
How clinical and dangerous each attack was — not just how often they shot, but where and how good those chances were.
Manchester United leads this block
Manchester United leads shot accuracy (+33% vs Bayern Munich)
Manchester United leads shot accuracy (+33% vs Bayern Munich)
Manchester United leads (0.110 vs 0.098).
Bayern Munich leads box penetration (+67% vs Manchester United)
Playing style signals: whether chances came from patient possession or direct vertical play.
Bayern Munich leads this block
Bayern Munich leads possession efficiency (+156% vs Manchester United)
Bayern Munich leads possession efficiency (+156% vs Manchester United)
Manchester United — slower buildup (more passes per shot)
Territorial dominance built from box presence, set pieces, and sustained threat.
Bayern Munich leads this block
Bayern Munich leads territorial pressure (+273% vs Manchester United)
Bayern Munich leads territorial pressure (+273% vs Manchester United)
How well each side limited chance quality and how demanding the keepers’ workload was.
Manchester United leads this block
Manchester United — stronger shot quality allowed
Manchester United — stronger shot quality allowed
Manchester United leads keeper workload (+33% vs Bayern Munich)
Archetype ratings you can map to card modifiers, AI behaviour, or match narratives.
Manchester United leads (15.0 vs 11.0).
Bayern Munich leads (42.8 vs 41.6).
Bayern Munich leads (21.0 vs 6.0).
Manchester United leads (0.110 vs 0.098).
Manchester United leads (90.2 vs 89.0).
Bayern Munich leads (21.0 vs 15.0).
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.
Minutes, rating, position, goals, assists, saves, cards — plus derived passing, duel, and discipline metrics for that appearance.
Badges mark standouts (best rating, playmaker, wall, and similar). Captain is shown when flagged in the data. Team totals aggregate all players on each side for head-to-head bars.
Player intelligence
Summed from every player on the pitch — useful for spotting which side controlled each phase.
Starters and key minutes — highest match ratings first.
Sportra blend of rating, goals, creativity, defending, and discipline.
Side-by-side match box scores — sorted by rating.
| Player | Rating | Minutes | Goals | Assists | Key passes | Def. contrib. |
|---|---|---|---|---|---|---|
| 90 | 1 | 1 | 6 | 5 | ||
| 90 | 1 | 0 | 1 | 0 | ||
| 85 | 1 | 1 | 3 | 1 | ||
| 90 | 0 | 0 | 0 | — | ||
| 78 | 0 | 0 | 0 | 0 | ||
| 90 | 0 | 0 | 0 | — |
Every player with box scores, derived metrics, and expandable full stat breakdowns.
90′ · 6 SV
André Onana played the full 90 minutes for Manchester United (rating 7.1). Completed around 20 of 28 passes (71%). Faced 8 shots on target (75% save rate).
78′
Rasmus Højlund (F) logged 78 minutes with a 6.9 rating. 2 shots without finding the net.
90′ · 1G · 1A
Bruno Fernandes (M) logged the full 90 minutes with a 8.4 rating. Contributed 1 goal and 1 assist. 5 defensive actions (5.0 per 90).
90′ · 3 SV
Manuel Neuer played the full 90 minutes for Bayern Munich (rating 6.8). Completed around 21 of 24 passes (88%). Faced 4 shots on target (75% save rate).
85′ · 1G · 1A
Kingsley Coman (F) logged the full 90 minutes with a 7.5 rating. Contributed 1 goal and 1 assist.
90′ · 1G
Harry Kane (F) logged the full 90 minutes with a 7.8 rating. Contributed 1 goal.
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.
Match DNA
Match outlookDouble chance : Manchester United or draw
Low tempo / cageyPrimary 1X2 blend plus secondary markets from Sportra's pre-match model.
Top-two gap 15 pts — medium confidence
1.45xG blend0.75
Projected line: 1–1
Likely scorelines (Poisson)
Model comparison and season shape — strength, attacking, defensive, and goal tendencies.
Weighted momentum, recent result run, and form-window W–D–L — the live pulse before kickoff.
Momentum is balanced — recent results cancel out.
Wins, draws, and losses across the sampled form window
League totals anchoring the snapshot — points, goal balance, and season shape vs opponent.
3W · 6D · 4L · 13 played
4W · 2D · 7L · 13 played
League table W–D–L, goal balance, and form-run counts from league profile signals
Attack vs opponent defense in the matchup comparison.
Manchester United's attack (43%) vs Bayern Munich's defense (38%).
+5Bayern Munich runs into a stronger home defensive profile.
-5Average goals for and against — home, away, and overall splits.
Blank spells, clean sheets, and under/over tendencies.
Biggest wins and losses, plus longest win/loss runs.
Derived indices from the full statistical profile.
From 3 meetings included in this prediction snapshot.
Sample data only (Premier League · 2019–20 (illustrative)). Live pages use the same views with Sportra data for your selected fixture, team, player, league, and season.
Questions: Contact · Data licensing: Data attribution
