Partial
events()
returns Event[] Every recognised match event in a canonical shape.
Stats Perform adapter
Stats Perform: The modern Stats Perform API envelope (same data as Opta).
Stats Perform is the company Opta became after the 2019 Perform Group / Stats LLC merger, so "Opta data" and "Stats Perform data" are the same event model — the difference is only how you receive it. The modern API delivers MA1 JSON for lineups and MA3 JSON for events; under the hood this adapter unwraps those envelopes and passes the events through the Opta pipeline. Use this adapter when you're on the current API; use the Opta adapter above when you have legacy F24-shaped event arrays. Sample-backed today — widen as more of the feed family is exercised against real data.
Raw feed
Stats Perform
Provider-shaped. Their coordinates, their qualifier codes, their outcome strings.
Messy
Campos adapter
fromStatsPerform.shots(ma3Document)
Flips direction, standardises outcomes, filters own-goals and shootouts, resolves
player labels.
One call
Typed data
ShotEvent[]
Drop into
<ShotMap />, your own React view, a server-side
report, or an analysis script.
Ready
Stats Perform is what Opta became after the 2019 Perform Group / Stats LLC merger.
The event data is identical; what differs is how you receive it. This adapter is for
the modern MA1/MA3 JSON API. Use Opta if you have classic
F24-shaped event arrays instead. Under the hood, this adapter unwraps MA3 documents and
passes events through fromOpta, then rebrands the output as provider: "statsperform".
Get it running
One import, one call per surface.
import { fromStatsPerform } from "@withqwerty/campos-adapters";
const events = fromStatsPerform.events(ma3Document);
const shots = fromStatsPerform.shots(ma3Document);
const passes = fromStatsPerform.passes(ma3Document);
const lineups = fromStatsPerform.matchLineups(ma1Document);
const formation = fromStatsPerform.formations(ma1Document, "home");What this adapter ships
The calls you can make today.
Partial
shots()
returns ShotEvent[] Just the shots, ready to plot.
Partial
passes()
returns PassEvent[] Pass trajectories with start, end, and result.
Partial
matchLineups()
returns MatchLineups Home and away team sheets with starters and bench.
Partial
formations()
returns FormationTeamData Kickoff tactical shape for one side.
Shipped
matchContext()
returns MatchContext Attack direction and period metadata.
What you can build with this
Charts that drop straight onto this adapter's output.
Supported cards plot from this adapter with no extra work. Partial cards plot, but read the scope note. Dimmed cards need a surface this provider doesn't ship.
Pitch charts
Plot events, shots, passes, and formations directly on the pitch.
ShotMap
Usable, but shots() on Stats Perform is narrower than the full surface.
PassMap
Usable, but passes() on Stats Perform is narrower than the full surface.
PassFlow
Usable, but passes() on Stats Perform is narrower than the full surface.
PassNetwork
Usable, but passes() on Stats Perform is narrower than the full surface.
PassSonar
Usable, but passes() on Stats Perform is narrower than the full surface.
Heatmap
Usable, but events() on Stats Perform is narrower than the full surface.
KDE
Usable, but events() on Stats Perform is narrower than the full surface.
Territory
Usable, but events() on Stats Perform is narrower than the full surface.
Formation
Usable, but formations() on Stats Perform is narrower than the full surface.
Match-time + xG
Time-series and xG-driven views from shots().
Bring your own aggregates
These charts are adapter-independent — they take pre-aggregated inputs.
ScatterPlot
Takes pre-aggregated data. No adapter dependency.
RadarChart
Takes pre-aggregated data. No adapter dependency.
PizzaChart
Takes pre-aggregated data. No adapter dependency.
BumpChart
Takes pre-aggregated data. No adapter dependency.
LineChart
Takes pre-aggregated data. No adapter dependency.
CometChart
Takes pre-aggregated data. No adapter dependency.
Beeswarm
Takes pre-aggregated data. No adapter dependency.
DistributionChart
Takes pre-aggregated data. No adapter dependency.
PercentileSurfaces
Takes pre-aggregated data. No adapter dependency.
StatBadge
Takes pre-aggregated data. No adapter dependency.
Two documents, two roles
MA1 for lineups, MA3 for events.
fromStatsPerform.matchLineups(ma1Document) reads the MA1 lineup feed for
starters, bench, formation, and substitution metadata. fromStatsPerform.events(ma3Document),
shots(...), passes(...), and matchContext(...)
all read the MA3 event feed. The two documents are kept separate because that's how the
feed family is actually structured.
Current scope
What's honest about this adapter today.
Sample-backed, not fully exercised.
The adapter ships against representative MA1/MA3 documents. Stats Perform's feed family is large, and we widen the surface as real feeds surface new edge cases — every widening is a credited change in the matrix.
Full canonical product set.
Events, shots, passes, match context, lineups, and formations all ship. What varies by deployment is how complete the MA1/MA3 documents you hand in are — more complete feeds give richer outputs.
Licensed feed, not scraped.
Stats Perform is a commercial provider. The adapter is useful for teams, clubs, agencies, and media organisations that already have access — it doesn't help you acquire the data.
Lineage
What this adapter borrows from whom.
Concrete credits for the projects that did the underlying research or laid the reference tables we read from.
Provider type-ID → canonical kind mapping, coordinate transformers, and direction-by-period normalisation patterns. Our reference for Opta, StatsBomb, Wyscout, Stats Perform, and Sportec.
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