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Home fortressHome attack vs home concession balanceSportra
Sportra Intelligence
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.
Data pipeline
Sportra Intelligence runs in four steps for every statistics tab:
- Gather — Sportra loads fixture, team, and player datasets when you open the 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 fortress) summarizes the season profile for quick reading.
Season intelligence
Home-Dominant Attack
Much more aggressive at home; away performances lean conservative.
Fast starterSecond-half surgeLow chaos
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.
39
Away attackShare of goals scored on the road44
Defensive reliabilityClean sheets and goals conceded rate11
Match chaosOver 3.5 goal frequency (higher = more open games)73
Form momentumLast five results weighted to wins11
Tactical flexibilityDistinct formations per match (higher = more adaptive)Season extremes
Biggest results, streaks, and set-piece record.
Form & momentum
- PPG
- 1.74
- Record
- 18W 12D 8L
- Momentum
- 73%
- Resilience
- low
Goals per game
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 |
Goal markets & chaos
Over/under lines for team goals and opponent goals — full threshold matrix from Sportra.
Team goals (over/under)
Over 0.579% over
Over 1.553% over
Over 2.529% over
Over 3.511% over
Over 4.53% over
Opponent goals (over/under)
Over 0.566% over
Over 1.526% over
Over 2.53% over
Over 3.50% over
Over 4.50% over
Low-chaos — controlled scorelines
Scoring distribution
- 0-15′
- 16-30′
- 31-45′
- 46-60′
- 61-75′
- 76-90′
- 91-105′
Full statistics tables
On the live site, expandable tables list fixture, goal, minute, and formation blocks for the selected season.
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.
Season intelligence
Wide creator
Profile as Midfielder: creator, high usage. Archetype: Wide creator. Season rating 7.6.
- Finisher
- Creator
- Ball carrier
- Pressure magnet
- Defensive work
- High usage
11Goals
9Assists
34Apps
2980′Minutes
Card attributes
Scaled 0–99 from season output — map to fantasy, comparisons, or scouting cards.
Derived metrics
Per-90 rates, efficiency ratios, and Sportra indices from season totals.
Goal efficiency
How clinical and direct the player was in front of goal — volume, accuracy, and conversion.
Chance creation
Playmaking output: assists, key passes, and custom chance-creation signals.
Ball carrying
Isolation threat and progressive carrying — volume plus success rate.
Pressure & discipline
How often they draw fouls and stay out of trouble with cards.
Defensive work
Tackles, duels, and off-ball defensive contribution.
Involvement
Minutes, availability, and how central they were to the team.
Full stat breakdown
Every tracked category for this league and season, grouped by Sportra.
Season summary
- Appearances
- 34
- Lineups
- 32
- Minutes
- 2980
- Position
- Midfielder
- Rating
- 7.6
- Goals Total
- 11
- Assists
- 9
Appearances & minutes
- Appearences
- 34
- Lineups
- 32
- Minutes
- 2980
- Rating
- 7.60
- Position
- Midfielder
Shooting
- Total
- 78
- On
- 34
Goals & keepers
- Total
- 11
- Assists
- 9
Passing
- Total
- 2100
- Key
- 72
- Accuracy
- 82%
Defending
- Total
- 42
- Blocks
- 12
- Interceptions
- 28
Duels
- Total
- 280
- Won
- 145
Dribbling
- Attempts
- 38
- Success
- 22
Fouls
- Drawn
- 48
- Committed
- 55
Discipline
- Yellow
- 8
- Red
- 0
Penalties
- Scored
- 6
- Missed
- 1
- Won
- 3
- Committed
- 1
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 | Shown with a readable label |
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.
Attacking
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 |
Possession & passing
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% |
Set pieces
Dead-ball situations that can swing momentum and territory.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
3 | Corner kicks | 6Lead |
Defensive & goalkeeping
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 |
Discipline
Physical intensity and referee involvement — fouls and cards.
| Manchester United | Statistic | Bayern Munich |
|---|---|---|
11 | Fouls | 9Lead |
2 | Yellow cards | 1Lead |
0 | Red cards | 0 |
Tactical insights
Scouting-style duels — each row compares both teams, shows share of the pie, and who had the edge. Categories summarize who won more signals.
Shooting efficiency
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
2Manchester United
duels won1Bayern Munich
Manchester United leads shot accuracy (+33% vs Bayern Munich)
- 1Manchester United57%57% shareBayern Munich43%43% share
Manchester United leads shot accuracy (+33% vs Bayern Munich)
- 2Manchester United0.11053% shareBayern Munich0.09847% share
Manchester United leads (0.110 vs 0.098).
- 3Manchester United43%38% shareBayern Munich71%63% share
Bayern Munich leads box penetration (+67% vs Manchester United)
Tactical identity
Playing style signals: whether chances came from patient possession or direct vertical play.
Bayern Munich leads this block
0Manchester United
duels won2Bayern Munich
Bayern Munich leads possession efficiency (+156% vs Manchester United)
- 1Manchester United0.01628% shareBayern Munich0.04072% share
Bayern Munich leads possession efficiency (+156% vs Manchester United)
- 2Manchester United7977% shareBayern Munich2423% share
Manchester United — slower buildup (more passes per shot)
Pressure & control
Territorial dominance built from box presence, set pieces, and sustained threat.
Bayern Munich leads this block
0Manchester United
duels won1Bayern Munich
Bayern Munich leads territorial pressure (+273% vs Manchester United)
- 1Manchester United1521% shareBayern Munich5679% share
Bayern Munich leads territorial pressure (+273% vs Manchester United)
Defensive
How well each side limited chance quality and how demanding the keepers’ workload was.
Manchester United leads this block
2Manchester United
duels won0Bayern Munich
Manchester United — stronger shot quality allowed
- 1Manchester United0.09847% shareBayern Munich0.11053% share
Manchester United — stronger shot quality allowed
- 2Manchester United0.3457% shareBayern Munich0.2643% share
Manchester United leads keeper workload (+33% vs Bayern Munich)
Gameplay profile
Archetype ratings you can map to card modifiers, AI behaviour, or match narratives.
3Manchester United
duels won3Bayern Munich
- 1Manchester United15.058% shareBayern Munich11.042% share
Manchester United leads (15.0 vs 11.0).
- 2Manchester United41.649% shareBayern Munich42.851% share
Bayern Munich leads (42.8 vs 41.6).
- 3Manchester United6.022% shareBayern Munich21.078% share
Bayern Munich leads (21.0 vs 6.0).
- 4Manchester United0.11053% shareBayern Munich0.09847% share
Manchester United leads (0.110 vs 0.098).
- 5Manchester United90.250% shareBayern Munich89.050% share
Manchester United leads (90.2 vs 89.0).
- 6Manchester United15.042% shareBayern Munich21.058% share
Bayern Munich leads (21.0 vs 15.0).
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, 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
Bruno Fernandes leads the player ratings (Rating 8.4).
- 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).
- Kingsley Coman (F) logged the full 90 minutes with a 7.5 rating. Contributed 1 goal and 1 assist.
- Harry Kane (F) logged the full 90 minutes with a 7.8 rating. Contributed 1 goal.
- 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).
Top performers
- Best player
- Playmaker
- Wall
- Defensive anchor
- Dribbler
- Attacking threat
- Risky player
- Captain
Squad totals
Summed from every player on the pitch — useful for spotting which side controlled each phase.
Total shots
Passes
Key passes
Tackles
Duels won
Successful dribbles
Saves
Sportra impact score
Sportra blend of rating, goals, creativity, defending, and discipline.
- 1Manchester United118
- 2Bayern Munich99
- 3Bayern Munich93
- 4Manchester United89
- 5Bayern Munich79
- 6Manchester United71
Player comparison
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 | — |
Full squad box scores
Every player with box scores, derived metrics, and expandable full stat breakdowns.
- —
90′ · 6 SV
- 28.0 ps/90
- 20 acc ps
- 75% saves
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′
- 13.8 ps/90
- 9 acc ps
- 2.3 sh/90
- 33% duels
- 0% drib
Rasmus Højlund (F) logged 78 minutes with a 6.9 rating. 2 shots without finding the net.
- —
90′ · 1G · 1A
- 68.0 ps/90
- 58 acc ps
- 5 def
- 4.0 sh/90
- 57% duels
- 75% drib
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
- 24.0 ps/90
- 21 acc ps
- 75% saves
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
- 32.8 ps/90
- 26 acc ps
- 1 def
- 5.3 sh/90
- 58% duels
- 71% drib
Kingsley Coman (F) logged the full 90 minutes with a 7.5 rating. Contributed 1 goal and 1 assist.
- —
90′ · 1G
- 22.0 ps/90
- 18 acc ps
- 6.0 sh/90
- 55% duels
- 50% drib
Harry Kane (F) logged the full 90 minutes with a 7.8 rating. Contributed 1 goal.
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
Match DNA
Defensive grind — model leans Manchester United, projected 1–1
Match outlookDouble chance : Manchester United or draw
Low tempo / cageyTempoMedium
VolatilityLow
Expected goalsMedium
Tactical styleDefensive grind
Upset potentialMedium
Draw riskMedium
Model confidenceMedium
Outcome model
Primary 1X2 blend plus secondary markets from Sportra's pre-match model.
Goal expectancy
1.45xG blend0.75
Projected line: 1–1
Likely scorelines (Poisson)
- Goals marketUnder 3.5
- Double chanceManchester United or Draw
Form & momentum
Weighted momentum, recent result run, and form-window W–D–L — the live pulse before kickoff.
29Cold spellManchester United
Weighted momentum
Momentum is balanced — recent results cancel out.
36Cold spellBayern Munich
Manchester United · Inconsistent in front of goalBayern Munich · High-risk / fragile
Manchester United
4W · 3D · 6LRecent →WLWWLWLDLDLDL
Momentum index
Bayern Munich
4W · 2D · 7LRecent →WWLLLLDLDLWLW
Momentum index
Form split comparison
Wins, draws, and losses across the sampled form window
Season record
League totals anchoring the snapshot — points, goal balance, and season shape vs opponent.
Table gapManchester United +1
Manchester United
15 pts23% wins
3W · 6D · 4L · 13 played
For16
Against13
Bayern Munich
14 pts31% wins
4W · 2D · 7L · 13 played
For11
Against24
Season shape comparison
League table W–D–L, goal balance, and form-run counts from league profile signals
Matchup edges
Attack vs opponent defense in the matchup comparison.
- Manchester United offensive edge
Manchester United's attack (43%) vs Bayern Munich's defense (38%).
+5 - Bayern Munich offensive edge
Bayern Munich runs into a stronger home defensive profile.
-5
Goals profile
Average goals for and against — home, away, and overall splits.
Goals for Goals against
Season avg
Manchester United
1.21.0
Bayern Munich
0.51.7
At home
Manchester United
1.40.8
Bayern Munich
0.61.5
On the road
Manchester United
1.01.2
Bayern Munich
0.41.9
Scoring reliability
Blank spells, clean sheets, and under/over tendencies.
- Failed to score42%38%
- Clean sheet31%15%
- Under 3.5 goals72%68%
Extremes & streaks
Biggest wins and losses, plus longest win/loss runs.
Manchester United
Biggest win3-0
Biggest loss0-2
Win run 2Loss run 4
Bayern Munich
Biggest win4-1
Biggest loss0-6
Win run 3Loss run 5
Sportra ratings
Derived indices from the full statistical profile.
Manchester UnitedInconsistent in front of goal
Bayern MunichHigh-risk / fragile
H2H in this snapshot
From 3 meetings included in this prediction snapshot.
1Manchester United33%
1Draws
1Bayern Munich33%
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.
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.
Questions: Contact · Data licensing: Data attribution