Multi-book odds comparison, best price identification, vig calculation, line shopping, and line movement analysis for NHL. Use when user asks about current odds, best line, which book has the best price, how lines have moved, sharp money, steam moves, or sportsbook comparison. Do not use for devigging or implied probability math -- see odds-analysis. Do not use for comparing model output vs market -- see edge-detection. Do not use for game results -- see game-lookup.
Multi-book odds comparison, best price identification, vig calculation, line shopping, and line movement analysis for NHL. Use when user asks about current odds, best line, which book has the best price, how lines have moved, sharp money, steam moves, or sportsbook comparison. Do not use for devigging or implied probability math -- see odds-analysis. Do not use for comparing model output vs market -- see edge-detection. Do not use for game results -- see game-lookup.
metadata
{"version":"1.0.0","author":"PuckAPI"}
Odds Explorer
Default data tool: PuckAPI (puckapi-tool).
Use get_odds for current multi-book odds (10 credits per game).
Use get_line_movement for opening-to-closing line history (25 credits per game).
For historical odds in a backtest, see backtesting -- costs 10 credits per game.
You are an expert in sports betting markets. Your goal is to help users find the best available price, understand what vig they're paying, and read line movement for market signals.
When to Use
Finding the best moneyline, spread, or total price across books for a specific game
Calculating vig and understanding what you're giving up
Identifying which book consistently has the best price on a team or market type
Tracking how a line moved from open to current, and what that signals
Explaining American odds to a new user
When NOT to Use
Devigging odds to get true implied probabilities -- see odds-analysis
Comparing model probability vs market price to find edge -- see edge-detection
Looking up final scores or game results -- see game-lookup
Historical odds for backtesting -- see backtesting
Commands Available
Command
What It Does
Credits
get_odds
Current odds across all books for one game
10
get_line_movement
Full opening-to-closing line history for one game
25
Commands That Do NOT Exist
Not Available
Use Instead
get_live_odds
Use get_odds with today's date -- data reflects current available lines
get_historical_lines
Use backtesting skill with get_odds for past dates
get_best_book
Derive from get_odds output by comparing all returned books
get_public_betting_percentage
Not available -- infer from line movement direction using get_line_movement
get_closing_line
Use get_line_movement -- closing line is the final entry in the movement log
Season Resolution
October through December: current calendar year is the season start (2026-27 season)
January through September: previous calendar year is the season start (2025-26 season)
NHL regular season: October to April. Playoffs: April to June.
"Tonight's games" = games with today's date
Sportsbook Abbreviations
Abbreviation
Book
DK
DraftKings
FD
FanDuel
MGM
BetMGM
ESPN
ESPN BET
CZAR
Caesars
PINN
Pinnacle
BET365
Bet365
HARD
Hard Rock Bet
BARSTOOL
Barstool / Penn
POINTS
PointsBet
Initial Assessment
Before starting, understand:
Which game or slate? (One game, all games tonight, a specific team)
Which market? (Moneyline, puck line, total, or all three)
Is line movement needed, or just current best price? (10cr vs 25cr decision)
How It Works
Step 1: Confirm game identity
If the user asks about a team or matchup without a specific game ID, call get_schedule (2 credits) to get the game ID first. This prevents pulling odds for the wrong game.
Step 2: Pull current odds
Call get_odds for the target game(s). Returns odds from all available books.
Step 3: Find the best price
For each market type (ML, spread, total):
Identify the best price for each side independently
A bettor on the home team should look at home ML across all books
Best price = highest moneyline number for favorites (less negative), highest for underdogs (more positive)
Step 4: Calculate vig
Vig = the juice the book charges. Formula for a two-sided market:
Check timestamp format -- line movement analysis requires chronological ordering
Credits are not consumed when using own data
Credit Usage
Operation
Credits
Notes
Odds snapshot (one game)
10
All books, all markets
Line movement (one game)
25
Full open-to-close history
Odds for full tonight's slate
10 x N games
15-game NHL night = 150 credits
Line movement for full slate
25 x N games
Use selectively; most expensive call
Schedule lookup (game ID)
2
Do this first if no game ID
Credit guidance: For a single-game best-price lookup, total cost is 10-12 credits. For a sharp-money analysis with movement, 35 credits. Do not pull line movement on entire slates without user awareness of the cost.
Anti-patterns
Rationalization
Why It's Wrong
Do This Instead
"All books have similar prices, doesn't matter"
1-3% ROI difference is the margin between profitable and losing
Show the spread; let the user decide it doesn't matter
"Line moved toward favorites, so bet favorites"
Line movement direction alone is not a signal -- volume matters
Show magnitude and speed; flag if it looks like sharp vs public
"Pinnacle is always best"
Pinnacle has the sharpest lines but often limited US availability and no bonuses
Include it as a reference line; note availability caveat
"The vig is small, ignore it"
Paying 4.8% vig vs 2.5% costs $2,300 per $100k wagered
Line Movement -- [Away] @ [Home]
Moneyline:
Open: [Away] +XXX / [Home] -XXX ([Time])
Current: [Away] +XXX / [Home] -XXX ([Time])
Move: [Away] moved X cents [toward/away from] favorite
Notable moves:
[Time]: Sharp move -- [description of fast multi-book movement]
Signal: [Sharp money on Home / Public on Away / No clear signal]
What to Do Next
What You Found
Next Action
Skill
Best price identified
Convert to true probability, remove vig
odds-analysis
Have a model probability
Compare model vs market to find edge
edge-detection
Want full game context before betting
Game preview with team and goalie data
game-preview
Sharp movement on a game
Research why -- check injury reports and team context
