How often does an NFL quarterback go over his passing touchdowns line?
One row per game with a quarterback's passing touchdowns line, the price, how many he threw and whether he went over. Josh Allen went over in 10 of 18.
Code verified October 21, 2026. One call to get_prop_history, 10 credits.
The call
player_id is a GSIS id from search_players. Other markets include passing yards, completions, attempts, interceptions thrown, rushing yards and receptions. Receiving touchdowns have no market of their own; anytime touchdown counts rushing and receiving scores.
import requests
import pandas as pd
API_KEY = "YOUR_API_KEY"
resp = requests.post(
"https://mcp.endzoneapi.com/v1/get_prop_history",
headers={"x-api-key": API_KEY},
json={
"player_id": "00-0034857",
"market": "player_pass_tds",
"from_date": "2025-09-01",
"to_date": "2026-02-28",
},
timeout=60,
)
resp.raise_for_status()
data = resp.json()["data"]
games = pd.DataFrame(data["games"])
s = data["summary"]
print(data["player_name"], data["stat"], "|", s["overs"], "overs,", s["unders"], "unders, over rate", s["over_rate"])
print("average line", s["avg_line"], "average actual", s["avg_actual"])
print(games[["game_date", "open_line", "line", "actual", "result"]].tail(6).to_string(index=False))
# How many touchdowns he actually threw: a 1.5 line splits the games between 0-1 and 2 or more.
print(games["actual"].value_counts().sort_index())
# Over rate by the price on the over: do the books shade the line when they expect more touchdowns?
games["price"] = pd.cut(games["over_odds"], [-1000, -130, -105, 1000], labels=["-130 or shorter", "-129 to -105", "even or longer"])
print(games.groupby("price", observed=True)["result"].value_counts().unstack(fill_value=0))
Replace YOUR_API_KEY with a key from your dashboard. Python needs requests and pandas (pip install requests pandas). JavaScript runs on Node 18 or newer, or in the browser.
Or use the official client: pip install endzoneapi
What comes back
The data object of the response, trimmed to the first rows. Every field is real output from the run above.
{
"player_id": "00-0034857",
"player_name": "Josh Allen",
"market": "player_pass_tds",
"stat": "passing touchdowns",
"bookmaker": null,
"games": [
{
"game_id": "2025_01_BAL_BUF",
"game_date": "2025-09-07",
"line": 1.5,
"open_line": 1.5,
"over_odds": -122,
"under_odds": -105,
"books": 7,
"actual": 2,
"result": "over",
"margin": 0.5
},
{
"game_id": "2025_02_BUF_NYJ",
"game_date": "2025-09-14",
"line": 1.5,
"open_line": 1.5,
"over_odds": -110,
"under_odds": -118,
"books": 7,
"actual": 0,
"result": "under",
"margin": -1.5
},
{
"game_id": "2025_03_MIA_BUF",
"game_date": "2025-09-18",
"line": 1.5,
"open_line": 1.5,
"over_odds": -156,
"under_odds": 122,
"books": 7,
"actual": 3,
"result": "over",
"margin": 1.5
},
{
"game_id": "2025_04_NO_BUF",
"game_date": "2025-09-28",
"line": 1.5,
"open_line": 1.5,
"over_odds": -152,
"under_odds": 124,
"books": 7,
"actual": 2,
"result": "over",
"margin": 0.5
}
],
"count": 18,
"summary": {
"games": 18,
"graded": 18,
"overs": 10,
"unders": 8,
"pushes": 0,
"over_rate": 0.556,
"avg_line": 1.5,
"avg_actual": 1.6
},
"truncated": false,
"next_from_date": null
}The example player is Josh Allen. The record against the line, market by market, is on the Josh Allen prop history page.
What to do next
- get_player_props (10 credits). Every sportsbook's passing touchdowns line for the same player this week.
- get_player_stats (5 credits). Attempts, yards and passing touchdowns by week.
More guides
The same guide for other sports
The latest lines from every book are on the odds board. Today's props, with the best price on each side, are on the player props board. Rather ask Claude? 16 free Claude skills call these endpoints for you.
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