NFL receiving yards data for developers

Where receiving yards appear

Pick6 rows use the label Receiving Yards, abbreviated RecYds. Separate labels 1Q Receiving Yards and 1H Receiving Yards were also in captures on 2026-11-03. ESPN box scores use the key receivingYards in the receiving category. 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.

curl --fail-with-body "https://draftkingsapi.com/api/v1/pick6/projections?sport=NFL&stat=Receiving%20Yards&limit=25" \
  -H "Authorization: Bearer $DRAFTKINGS_API_KEY"

curl --fail-with-body "https://draftkingsapi.com/api/v1/stats/player-games?sport=NFL&season=2026&completed=true&limit=50" \
  -H "Authorization: Bearer $DRAFTKINGS_API_KEY"

Read several targets for one receiver

A single receiver can have many rows at different target_values, often with one-sided More selections. Group by entities[0].entity_id and sort by target to see the ladder the source offered at that capture.

from collections import defaultdict

ladder = defaultdict(list)
for row in rows:  # one page from /api/v1/pick6/projections
    if row["stale"] or row["is_paused"]:
        continue
    for entity in row["entities"]:
        ladder[entity["entity_id"]].append((
            row["target_value"],
            [(s["side"], s["standings_multiplier"]) for s in row["selections"]],
        ))

for entity_id, targets in ladder.items():
    print(entity_id, sorted(targets, key=lambda t: t[0]))

Pick6 rows carry standings multipliers such as 1.5x. A standings multiplier is not decimal odds, a probability or an established entry payout.

Read a receiving box score row

An NFL player can have one row per category in a game: receiving, rushing, passing, kicking and others. Your query cannot filter by category, so filter the returned rows yourself. Key the statistic by key, because labels such as YDS and TD repeat across categories.

def receiving_yards(row):
    if row["data"]["category"] != "receiving":
        return None
    for stat in row["data"]["stats"]:
        if stat["key"] == "receivingYards":
            return stat["numeric"]
    return None

Part-of-game labels do not mix

A box score holds a full-game total. 1Q Receiving Yards and 1H Receiving Yards targets measure part of a game, and the statistics API does not supply those splits. Do not compare them to receivingYards.

Identity between Pick6, DFS and ESPN

A Pick6 entity_id is a DraftKings identifier. In a bounded NFL check on 2026-11-03 it matched the DFS data.playerDkId for almost every name-matched player, so that join is worth testing. An ESPN athlete_id is separate, and no mapping to it is supplied. Build and review your own, using name, team and date.

DFS salary rows sit alongside this, but salary and FPPG are roster data. They are not comparable to a receiving yards target.

Sample limits for receiving models

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.

NFL season uses the starting year, so the 2026 season is season=2026. A valid season does not mean every game is stored. Read available and coverage in the response, and read the coverage report for the count.

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. Read prop model data before you plan a training set around it.

Check the recorded data

• Sources and status
• Measured coverage report
• Recorded Pick6 props

Related resources