🔒 ML algorithm to analyze basketball data

[civic root]

Hey all! I have about 5755 rows of data in my database used in my API and returns this for example:

{
    "id": "141cac7f-c0dd-4cfd-b609-110b569e92a5",
    "matchId": 40189,
    "team": "away_team",
    "playerId": 28422,
    "action": "DEFENSIVE_REBOUND",
    "quarter": 4,
    "time": "0:00",
    "teamId": 661,
    "bteamPoints": 65,
    "ateamPoints": 62
  },

Above is an example response based off the data from a basketball match between two teams, this is for a single play-by-play event in a match. Now I want to use an ML algorithm to train a model to be able to use this dataset and predict trends in teams whether the team is aggressive or defensive based on the actions. Any suggestions?

[fluid maple]

@civic root

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[civic root]

Also I did a stats table for each of the 15 games based on the 11 teams and I have this now:

{ "dataId": 1, "matchId": 40092, "teamId": 654, "total3PtsMade": 6, "total3PtsMissed": 10, "total2PtsMade": 10, "total2PtsMissed": 9, "totalTeamPts": 68, "overTime": false, "totalFreeThrowsMade": 10, "totalFreeThrowsMissed": 9, "teamName": "Kawasaki Brave Thunders", "2PtEfficiency": 52.63, "total3PtsAttempts": 16, "3PtEfficiency": 37.5, "totalFieldGoalsAttempts": 35, "freeThrowEfficiency": 52.63, "totalFreeThrowAttempts": 19, "totalFieldGoalsMade": 16, "total2PtsAttempts": 19 },

{ "dataId": 2, "matchId": 40092, "teamId": 667, "total3PtsMade": 5, "total3PtsMissed": 6, "total2PtsMade": 9, "total2PtsMissed": 13, "totalTeamPts": 76, "overTime": false, "totalFreeThrowsMade": 6, "totalFreeThrowsMissed": 7, "teamName": "Toyota Alvark", "2PtEfficiency": 40.91, "total3PtsAttempts": 14, "3PtEfficiency": 35.71, "totalFieldGoalsAttempts": 36, "freeThrowEfficiency": 46.15, "totalFreeThrowAttempts": 13, "totalFieldGoalsMade": 14, "total2PtsAttempts": 22 },

The above is stats for 1 game between teams "home team" and "away team"

[fluid maple]

@civic root

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