How often does an MLB hitter go over his hits line?

The call

player_id comes from search_players. The line moves between 0.5 and 1.5 hits; group by it before comparing over rates.

import requests
import pandas as pd

API_KEY = "YOUR_API_KEY"

resp = requests.post(
    "https://mcp.fastballapi.com/v1/get_prop_history",
    headers={"x-api-key": API_KEY},
    json={
        "player_id": "42403",
        "market": "batter_hits",
        "from_date": "2026-03-01",
        "to_date": "2026-10-31",
        "limit": 200,
    },
    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(games[["game_date", "line", "over_odds", "under_odds", "actual", "result"]].tail(6).to_string(index=False))
# Over rate at each line the books set.
print(games.groupby("line")["result"].value_counts(normalize=True).unstack(fill_value=0).round(3))

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 fastballapi

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": "42403",
  "player_name": "Bobby Witt Jr.",
  "market": "batter_hits",
  "stat": "hits",
  "bookmaker": null,
  "games": [
    {
      "game_id": "401814691",
      "game_date": "2026-03-27",
      "line": 1.5,
      "open_line": 1.5,
      "over_odds": 198,
      "under_odds": -270,
      "books": 5,
      "actual": 2,
      "result": "over",
      "margin": 0.5
    },
    {
      "game_id": "401814710",
      "game_date": "2026-03-28",
      "line": 1.5,
      "open_line": 1.5,
      "over_odds": 182,
      "under_odds": -244,
      "books": 5,
      "actual": 1,
      "result": "under",
      "margin": -0.5
    },
    {
      "game_id": "401814725",
      "game_date": "2026-03-29",
      "line": 1.5,
      "open_line": 1.5,
      "over_odds": 190,
      "under_odds": -256,
      "books": 5,
      "actual": 1,
      "result": "under",
      "margin": -0.5
    },
    {
      "game_id": "401814743",
      "game_date": "2026-03-30",
      "line": 1.5,
      "open_line": 1.5,
      "over_odds": 130,
      "under_odds": -175,
      "books": 4,
      "actual": 0,
      "result": "under",
      "margin": -1.5
    }
  ],
  "count": 137,
  "summary": {
    "games": 137,
    "graded": 136,
    "overs": 48,
    "unders": 88,
    "pushes": 0,
    "over_rate": 0.353,
    "avg_line": 1.3,
    "avg_actual": 1.1
  },
  "truncated": false,
  "next_from_date": null,
  "note": "1 of 137 games have no result yet (not played, or no box score or play-by-play of ours for the player)."
}

What to do next

• get_player_props (10 credits). Every sportsbook's hits line for a game.
• get_player_games (5 credits). His game-by-game batting line.

More guides

• Where do I get MLB pitch-by-pitch data for a model?
• How do I get a pitcher's pitch mix and whiff rate in Python?
• How do I build an MLB spray chart in Python?
• How do I find MLB teams that over- or underperformed their run differential?

The same guide for other sports

• PuckAPI: How do I compare NHL player prop lines across sportsbooks?
• EndzoneAPI: How do I compare NFL player prop lines across sportsbooks?
• StrikerAPI: How do I get anytime goalscorer odds and results for a player in Python?
• DunkAPI: How do I compare NBA player prop lines across sportsbooks?