NBA points props data for developers

Two datasets, two meanings

NBA points data lives in two places here. Pick6 rows hold a target and standings multipliers. The statistics API holds what a player recorded, from ESPN. Neither one contains the other, and neither is a sportsbook price.

As of 2026-11-03, native sportsbook scopes cover New York NFL, NHL, college basketball and college football game lines and New York NHL Shots on Goal, points, assists, saves, goalscorers, power-play points and first-period shots. Read snapshots and streamed changes through the sportsbook endpoints. ESPN-attributed DraftKings moneyline, spread and total observations are also available across eight leagues. Current scope inventory is listed at /api/v1/sportsbook/scopes.

Read the Points rows

Filter on stat=Points, and expect several rows per athlete. Check stale before you treat any row as current, since NBA captures are not always fresh.

curl --fail-with-body "https://draftkingsapi.com/api/v1/pick6/projections?sport=NBA&stat=Points&limit=25" \
  -H "Authorization: Bearer $DRAFTKINGS_API_KEY"

Read points from a box score

Each ESPN row holds a stats array. Find the entry with key equal to points and read numeric. Values such as field goals display as 1-3 and have a null numeric, so they stay display-only.

def points(row):
    for stat in row["data"]["stats"]:
        if stat["key"] == "points" and stat["scope"] == "game":
            return stat["numeric"]  # None when no scalar exists
    return None

Rows also report did_not_play and starter. A missing points value on a did-not-play row is not a zero. Treat it as no game for that player.

Why the two do not join by themselves

Pick6 identifies an athlete with entity_id. ESPN uses athlete_id. No mapping between them is supplied, and the API does not infer one from names. If you match on names, you own that matching and its errors.

1. Build a table of entity_id, athlete_id, the matched name, and how you verified it.
2. Require an exact name match within the same team and game date.
3. Send ambiguous names to manual review instead of guessing.

Games have the same split. Pick6 event IDs differ from ESPN event IDs, so match games on date and teams after you have reviewed them.

What this sample can and cannot show

Independent ESPN statistics cover NBA, NFL and NHL as limited retained game samples, not full seasons. As of 2026-11-03 those samples were captured after the games were played, so they do not show what was known at game time.

Recording began around 2026-11-03. Retained history is short, and it is not a complete opening-to-close archive. It does not contain seasons of past lines, and there is no public graded-results endpoint.

A recorded NBA Points row and a later box score can give you an honest small sample to inspect. They cannot support a hit rate presented as a long-run edge. For that sample, report the count and the date range next to any number, and read the coverage report first.

There is also no public grading endpoint, so compare target and result yourself, and make your own rules for pushes, inactive players and in-game rows.

Live scores are a separate clock

live_stat_value on a Pick6 row is the source's in-game statistic at capture, stamped by live_stat_updated_at. It can change after the row was captured, and it is not a final box score. Use completed games from the statistics API for finished values: add completed=true.

curl --fail-with-body "https://draftkingsapi.com/api/v1/stats/player-games?sport=NBA&season=2027&completed=true&limit=50" \
  -H "Authorization: Bearer $DRAFTKINGS_API_KEY"

Check the recorded data

• Sources and status
• Measured coverage report
• Recorded line moves

Related resources