How often does a college basketball player go over his rebounds line?
One row per game with a college player's rebounds line, the price, how many he grabbed and whether he went over. Duke's Cameron Boozer went over in 17 of 33 last season.
Code verified October 13, 2026. One call to get_prop_history, 10 credits.
The call
league: ncaam selects men's college basketball. Other college markets: points and assists. Pass bookmaker for one book's close instead of the median across books.
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": "5041935",
"market": "player_rebounds",
"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": "5041935",
"player_name": "Cameron Boozer",
"market": "player_rebounds",
"stat": "rebounds",
"bookmaker": null,
"games": [
{
"game_id": "401817230",
"game_date": "2025-11-11",
"line": 9.5,
"open_line": 9.5,
"over_odds": -130,
"under_odds": 100,
"books": 3,
"actual": 9,
"result": "under",
"margin": -0.5
},
{
"game_id": "401817231",
"game_date": "2025-11-14",
"line": 9.5,
"open_line": 9.5,
"over_odds": -120,
"under_odds": -108,
"books": 3,
"actual": 12,
"result": "over",
"margin": 2.5
},
{
"game_id": "401817232",
"game_date": "2025-11-18",
"line": 10.5,
"open_line": 10.5,
"over_odds": -135,
"under_odds": -114,
"books": 3,
"actual": 11,
"result": "over",
"margin": 0.5
},
{
"game_id": "401813377",
"game_date": "2025-11-21",
"line": 10.5,
"open_line": 10.5,
"over_odds": -112,
"under_odds": -115,
"books": 3,
"actual": 5,
"result": "under",
"margin": -5.5
}
],
"count": 33,
"summary": {
"games": 33,
"graded": 33,
"overs": 17,
"unders": 16,
"pushes": 0,
"over_rate": 0.515,
"avg_line": 10.1,
"avg_actual": 10.5
},
"truncated": false,
"next_from_date": null
}What to do next
- get_player_props (10 credits). Every sportsbook's rebounds line for the next college game.
- get_game (5 credits). The full box score of any game in the history.
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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