How often does a college basketball player go over his points line?
One row per game with a college player's points line, the price, what he scored and whether he went over. Purdue's Braden Smith went under in 22 of 35 last season.
Code verified October 13, 2026. One call to get_prop_history, 10 credits.
The call
league: ncaam selects men's college basketball. player_id comes from search_players with the same league. Books post college props for the bigger games, so a player's history covers the games that had a line.
import requests
import pandas as pd
API_KEY = "YOUR_API_KEY"
resp = requests.post(
"https://mcp.dunkapi.com/v1/get_prop_history",
headers={"x-api-key": API_KEY},
json={
"league": "ncaam",
"player_id": "5105854",
"market": "player_points",
"from_date": "2025-11-01",
"to_date": "2026-04-10",
"limit": 100,
},
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 far each result landed from the line: a steady miss in one direction is the pattern worth testing.
print(games["margin"].describe()[["mean", "50%", "std"]])
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.
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": "5105854",
"player_name": "Braden Smith",
"market": "player_points",
"stat": "points",
"bookmaker": null,
"games": [
{
"game_id": "401828553",
"game_date": "2025-11-04",
"line": 17.5,
"open_line": 17.5,
"over_odds": 100,
"under_odds": -133,
"books": 2,
"actual": 6,
"result": "under",
"margin": -11.5
},
{
"game_id": "401826869",
"game_date": "2025-11-07",
"line": 14.5,
"open_line": 14.5,
"over_odds": -114,
"under_odds": -114,
"books": 2,
"actual": 20,
"result": "over",
"margin": 5.5
},
{
"game_id": "401812262",
"game_date": "2025-11-13",
"line": 18.5,
"open_line": 18.5,
"over_odds": 100,
"under_odds": -130,
"books": 3,
"actual": 29,
"result": "over",
"margin": 10.5
},
{
"game_id": "401820598",
"game_date": "2025-11-16",
"line": 15.5,
"open_line": 15.5,
"over_odds": -122,
"under_odds": -106,
"books": 3,
"actual": 16,
"result": "over",
"margin": 0.5
}
],
"count": 35,
"summary": {
"games": 35,
"graded": 35,
"overs": 13,
"unders": 22,
"pushes": 0,
"over_rate": 0.371,
"avg_line": 15.4,
"avg_actual": 14
},
"truncated": false,
"next_from_date": null
}What to do next
- get_player_props (10 credits). Every sportsbook's line for a college game, with league ncaam.
- get_player_games (5 credits). The player's game log behind the line.
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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