Dropping odds

A dropping odd is an outcome whose decimal price drops (shortens) meaningfully over time — e.g. a home win going from 2.50 to 2.10. A shorter price means a rising implied probability: money is coming in on that side. Since Pinnacle is the sharpest book, these moves often signal market information (injury, lineup, a steam move).

Why it’s a signal

Informed money: at Pinnacle a sharp drop reflects large/informed stakes, not noise.
Positive CLV: betting before the price shortens further beats the close (see true odds).
Live timing: in‑play, dropping odds react to match events within seconds.

Detecting them with apinn

Every /api/odds?full_history=1 call returns all snapshots of an event (each timestamped), with raw odds1/odds0/odds2 and devig todds1/0/2. Compare the opening (first snapshot) to the current value:

List live matches

curl "https://api.apinn.io/api/fixtures?sport_id=29&live=1" -H "X-API-Key: YOUR_KEY"

Fetch the odds history

curl "https://api.apinn.io/api/odds?event_id=1632003656&full_history=1&main_lines_only=1&market=moneyline" \
  -H "X-API-Key: YOUR_KEY"

Compute the drop per outcome

drop% = (open − current) / open × 100 — keep drops ≥ your threshold.

Python

import requests

BASE, H = "https://api.apinn.io", {"X-API-Key": "YOUR_KEY"}
THRESHOLD = 8      # minimum % drop
event_id = 1632003656

hist = requests.get(f"{BASE}/api/odds",
    params={"event_id": event_id, "full_history": 1,
            "main_lines_only": 1, "market": "moneyline"}, headers=H).json()

# snapshots sorted by timestamp ; open = first, current = last
snaps = sorted(hist, key=lambda r: r["timestamp"])
if snaps:
    open_, now = snaps[0], snaps[-1]
    for k, label in [("odds1", "home"), ("odds0", "draw"), ("odds2", "away")]:
        o, n = open_.get(k), now.get(k)
        if o and n:
            drop = (o - n) / o * 100
            if drop >= THRESHOLD:
                print(f"⬇ {label}: {o:.2f} → {n:.2f}  (−{drop:.1f}%)")

Prefer the todds fields (margin removed) for a cleaner signal: the drop then reflects the move in fair probability, not the vig.

Best practices

Bound the odds (e.g. 1.30–6.00): ignore noisy extremes.
Window: since the open (underlying move) or over the last N minutes (live reaction).
Real-time: for sub‑second, listen to the SSE stream instead of polling.
Inverse: rising odds (prices drifting out) signal money leaving a side.

Build it in one prompt

Don’t want to code? Paste our ready‑made prompt into Claude and it builds the dropping-odds monitor for you — see Build with Claude.

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Concepts

Dropping odds

Why it’s a signal

Detecting them with apinn

Best practices

Build it in one prompt

​Why it’s a signal

​Detecting them with apinn

​Best practices

​Build it in one prompt

Why it’s a signal

Detecting them with apinn

Best practices

Build it in one prompt