Read an NBA player's game log

1. Resolve the current season

curl -sS --compressed \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  'https://api.stat-api.com/api/v1/nba/seasons?limit=200'

2. Page the season's games

Collect every game so each stat line can be joined back to its game.

curl -sS --compressed \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  'https://api.stat-api.com/api/v1/nba/games?season_id=2025'

3. Index games by id

index_by builds an id-to-game map for the join.

const game_by_id = new Map<number, NBAGame>()
for (const row of games) game_by_id.set(row.id, row)

4. Borrow a player from one game's box score

One stat line gives a valid player_id to build the log from.

curl -sS --compressed \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  'https://api.stat-api.com/api/v1/nba/game_player_stats?game_id=1&limit=1'

5. Page that player's game log

game_player_stats accepts player_id as a standalone filter — page every appearance.

curl -sS --compressed \
  -H 'Authorization: Bearer YOUR_API_KEY' \
  'https://api.stat-api.com/api/v1/nba/game_player_stats?player_id=1'

6. Print the game log

Each row joins game_id back to its game_time through the index; the stat column is the sport's headline number.

console.log("NBA game log (points)")
console.log(["game_time", "pts"].join('\t'))
for (const row of gamelog) {
  console.log([String(game_by_id.get(row.game_id)?.game_time ?? row.game_id), String(row.pts ?? '')].join('\t'))
}