Match events¶

Every player in a clubs/matches response carries four fields, match_event_aggregate_0 to match_event_aggregate_3. Each is a comma-separated list of event_id:count pairs:

"match_event_aggregate_0": "0:2,109:3,145:5,174:19,215:21,216:5,24:17,30:8,6:1",
"match_event_aggregate_1": "97:10",
"match_event_aggregate_2": "",
"match_event_aggregate_3": ""

215:21 means event 215 fired 21 times for that player in that match. An id that appears in no bucket has a count of 0. EA does not document the ids. They are far more detailed than the named fields: pass direction and length, possession won by pitch third, positioning feedback and more.

Credit

The mappings on this page come from the community EA FC Pro Clubs API research project, which derived them from about 51,000 FC 27 player-match rows (its dataset is in that repository). They are observations, not EA documentation. New findings and corrections belong there; this package follows its confirmed table.

Using it¶

from fc_clubs_api import FC27API

api = FC27API(output="dataframe")
players = api.get_match_players(club_id, include_events=True)

players[["name", "passesCompleted", "passesCompletedForward",
         "possessionWonAttackingThird", "outOfPosition"]]

include_events=True adds every stat in the confirmed table as a column. Where EA already sends a field with the same name (goals, assists, shots), EA's value is kept.

Working from raw JSON, or want the raw counters:

from fc_clubs_api.events import parse_event_aggregates, decode_events, EVENT_STATS

matches = api.get_club_matches(club_id, output="raw")
player = next(iter(matches[0]["players"][str(club_id)].values()))

parse_event_aggregates(player)   # {215: 21, 216: 5, 30: 8, ...}  every id, raw counts
decode_events(player)            # {"passesCompleted": 21, "passesCompletedForward": 8, ...}

for stat in EVENT_STATS:         # the table below, as data
    print(stat.name, stat.formula, stat.description)

Confirmed (high confidence)¶

Decoded by include_events=True. Formulas with max(0, ...) are remainders: the direction (or length) events don't cover every pass, so the rest is reported as "unknown". In the research data the three direction events summed to the completed total 98.0% of the time, and the four length events 97.7%.

Stats marked "a tag, not a partition" describe some goals or assists (a weak-foot goal is also a goal); they don't add up to the total.

Passing¶

Column	Formula	Meaning
`passesCompleted`	`event_215`	Passes completed (excludes offside passes)
`passesFailed`	`event_216`	Passes failed
`passesCompletedForward`	`event_30`	Completed passes played forward
`passesCompletedBackward`	`event_32`	Completed passes played backward
`passesCompletedSideways`	`event_34`	Completed passes played sideways
`passesCompletedDirectionUnknown`	`max(0, event_215 - (event_30 + event_32 + event_34))`	Completed passes with no direction event
`passesCompletedShort`	`event_24`	Completed short passes
`passesCompletedMedium`	`event_26`	Completed medium passes
`passesCompletedLong`	`event_28`	Completed long passes
`passesCompletedCross`	`event_36`	Completed crosses (includes set pieces)
`passesCompletedLengthUnknown`	`max(0, event_215 - (event_24 + event_26 + event_28 + event_36))`	Completed passes with no length event
`passesFailedForward`	`event_31`	Failed passes played forward
`passesFailedBackward`	`event_33`	Failed passes played backward
`passesFailedSideways`	`event_35`	Failed passes played sideways
`passesFailedDirectionUnknown`	`max(0, event_216 - (event_31 + event_33 + event_35))`	Failed passes with no direction event
`passesFailedShort`	`event_25`	Failed short passes
`passesFailedMedium`	`event_27`	Failed medium passes
`passesFailedLong`	`event_29`	Failed long passes
`passesFailedCross`	`event_37`	Failed crosses (open play only)
`passesFailedLengthUnknown`	`max(0, event_216 - (event_25 + event_27 + event_29 + event_37))`	Failed passes with no length event
`firstTimePasses`	`event_143`	First-time passes
`switchesOfPlay`	`event_144`	Switch-of-play passes
`flairPasses`	`event_147`	Fancy / flair passes
`throughPasses`	`event_152`	Successful through balls
`offsidePasses`	`event_153`	Passes caught offside

Shooting and goals¶

Column	Formula	Meaning
`shots`	`event_217 + event_218`	Shots (on + off target)
`shotsOnTarget`	`event_217`	Shots on target (blocked shots can fold in)
`shotsOnTargetInsideBox`	`event_13`	Shots on target from inside the box
`shotsOnTargetOutsideBox`	`event_18`	Shots on target from outside the box
`shotsOffTarget`	`event_218`	Shots off target
`shotsOffTargetInsideBox`	`event_14`	Shots off target from inside the box
`shotsOffTargetOutsideBox`	`event_19`	Shots off target from outside the box
`shotsSaved`	`event_202`	Shots saved
`goals`	`event_214`	Goals
`goalsFirstTime`	`event_128`	Goals from first-time shots (a tag, not a partition)
`goalsWeakFoot`	`event_131`	Goals with the weak foot (a tag, not a partition)
`goalsOffPost`	`event_136`	Goals in off the post (a tag, not a partition)
`assists`	`event_11`	Assists
`secondAssists`	`event_115`	Second assists
`throughBallAssists`	`event_118`	Assists from through balls (a tag, not a partition)

Dribbling¶

Column	Formula	Meaning
`dribblesCompleted`	`event_174`	Dribbles completed
`dribblesCarried`	`event_97`	Dribbles carried
`dribblesBeat`	`max(0, event_112 - event_38)`	Players beaten without a skill move
`dribblesSkillMoveBeat`	`event_38`	Players beaten with a skill move

Defending and goalkeeping¶

Column	Formula	Meaning
`tacklesWon`	`event_0`	Tackles won
`tacklesLost`	`event_1`	Tackles lost
`standingTacklesWon`	`event_229`	Standing tackles won
`slidingTacklesWon`	`event_230`	Sliding tackles won
`cleanTackles`	`event_164`	Successful tackles on the ball
`dangerousTackles`	`event_163`	Dangerous tackles
`interceptions`	`event_6`	Interceptions
`opponentsDispossessed`	`event_158`	Opponents dispossessed
`crossesBlocked`	`event_156`	Crosses blocked
`aerialDuelsWonAttacking`	`event_265`	Aerial duels won when attacking
`aerialDuelsWonDefending`	`event_266`	Aerial duels won when defending
`goodDirectionSaves`	`event_267`	Saves diving the right way

Possession¶

Column	Formula	Meaning
`possessionLostDefensiveThird`	`event_105`	Possession lost in the defensive third
`possessionLostMiddleThird`	`event_106`	Possession lost in the middle third
`possessionLostAttackingThird`	`event_107`	Possession lost in the attacking third
`possessionWonDefensiveThird`	`event_108`	Possession won in the defensive third
`possessionWonMiddleThird`	`event_109`	Possession won in the middle third
`possessionWonAttackingThird`	`event_110`	Possession won in the attacking third

Discipline and set pieces¶

Column	Formula	Meaning
`foulsConceded`	`event_2 + event_3`	Fouls conceded, all areas
`foulsConcededDefensiveThird`	`event_3`	Fouls conceded around the defensive third
`foulsWon`	`event_4`	Times this player was fouled
`yellowCards`	`event_95 + event_213`	Yellow cards (immediate + delayed)
`yellowCardsImmediate`	`event_95`	Yellow cards shown as play stopped
`yellowCardsDelayed`	`event_213`	Yellow cards shown after advantage was played
`penaltiesConceded`	`event_94`	Penalties conceded
`cornersConceded`	`event_10`	Corners conceded
`cornersTaken`	`event_145`	Corners taken

Positioning and match feedback¶

Column	Formula	Meaning
`inPosition`	`event_111`	Times the feedback praised this player's positioning
`outOfPosition`	`event_219`	Times out of position, any severity
`outOfPositionSeverity1`	`event_99`	Out of position, severity 1 of 5
`outOfPositionSeverity2`	`event_100`	Out of position, severity 2 of 5
`outOfPositionSeverity3`	`event_101`	Out of position, severity 3 of 5
`outOfPositionSeverity4`	`event_102`	Out of position, severity 4 of 5
`outOfPositionSeverity5`	`event_103`	Out of position, severity 5 of 5
`feedbackUseTheBall`	`event_212`	Feedback: 'Use the ball'
`feedbackPickYourPass`	`event_207`	Feedback: 'Pick your pass'
`feedbackNoGoodOption`	`event_175`	Feedback: 'No good option'
`feedbackGoodOptionTaken`	`event_176`	Feedback: 'Good option taken'
`feedbackBestOptionTaken`	`event_177`	Feedback: 'Best option taken'
`feedbackShouldHavePassedElsewhere`	`event_182`	Feedback: 'Should have passed elsewhere'
`feedbackChoseToPass`	`event_183`	Feedback: 'Chose to pass'

Left out on purpose: event_171 (free kicks for bad tackles). The research is confident about what triggers it but not about what to call it.

Partial mappings (not decoded)¶

Supported by the data but not accounting for every case. Use with care.

Event	Likely meaning	Evidence
`event_151`	Bad / hospital passes	4 of 4 matches checked
`event_121`	Tackle success indicator	Matches `event_229` 98.5% of the time
`event_157`	Crosses attempted, open play	Add `event_145` when a corner is crossed
`event_96`	Red card trigger / severe foul	82.7% precision, 16.6% coverage
`event_104`	Times caught offside	Presence right, count often too low
`event_49`, `event_50`	Save sub-types	Each on ~18–20% of goalkeeper rows
`event_12`, `event_124`, `event_137`	Goals by technique	Together with `event_128`, 85.8% of goals; tags overlap
`event_140`, `event_93`, `event_238`	Goals by technique	~99% precision
`event_123`	Chipped goals	~99% precision
`event_179`	Feedback: "Should have shot"	2 of 2 cases
`event_150`	Tiki-taka playstyle pass	1 case, label uncertain
`event_159`	Tackle ending a dribble	1 case, label uncertain

Exploratory findings (not decoded)¶

Events that almost never fire without a goal, so they probably tag a goal technique. None has been tied to a named technique yet. Precision = share of firings on a goal; recall = share of goals tagged.

Event	Precision	Recall
`event_46`	≥ 98.6%	5.91%
`event_141`	≥ 98.6%	6.38%
`event_126`	≥ 98.6%	5.52%
`event_17`	≥ 98.6%	3.65%
`event_15`	≥ 98.6%	3.18%
`event_125`	≥ 98.6%	2.57%
`event_239`	≥ 98.6%	1.93%
`event_138`	≥ 98.6%	1.85%
`event_139`	≥ 98.6%	1.09%
`event_135`	≥ 98.6%	0.77%
`event_130`	≥ 98.6%	0.71%
`event_134`	≥ 98.6%	0.69%
`event_203`	81.1%
`event_173`	68.1%
`event_21`	66.1%
`event_194`	62.3%
`event_117`	43.0%
`event_48`, `event_132`, `event_122`, `event_199`, `event_168`	100%	rare (1–124 firings)

Events vs EA's named fields¶

A live check on 2026-10-02 (59 player rows, 10 league matches) compared the decoded stats with EA's own named fields:

passesmade was usually passesCompleted + event_153: EA's named field includes offside passes, event_215 does not.
On 4 of the 59 rows the named fields were far higher than the events (for example passesmade 99 against 11 completed-pass events, with assists and shots also higher). The cause is unknown; the event buckets may not cover the whole match for some players. Treat EA's named fields as authoritative for totals, and the events as a breakdown.

Found something new? Contribute it to the research project, with the evidence, and open an issue here to get it decoded.