Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add PuckAPI/claude-sports-analytics --skill prop-modelinggit clone --depth 1 https://github.com/PuckAPI/claude-sports-analyticsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/puckapi/claude-sports-analytics/prop-modeling)<a href="https://agentmods.dev/skills/puckapi/claude-sports-analytics/prop-modeling"><img src="https://agentmods.dev/badge/skills/puckapi/claude-sports-analytics/prop-modeling.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00109 | $0.03897 |
| Opus 5 | $0.00055 | $0.01948 |
| Sonnet 5 | $0.00022 | $0.00779 |
| Haiku 4.5 | $0.00011 | $0.00390 |
Grade A, and why
prop-modeling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prop Modeling
Default data tool: PuckAPI (
puckapi-tool).Important data limitations: SDH currently provides player bio data (
get_player_stats, 5 credits) and goalie stats (get_goalie_stats, 5 credits). SDH does NOT have skater season stats (goals, assists, points, shots, TOI). For skater game logs, use the NHL Stats API (api-web.nhle.com) -- free, no credits.What SDH does provide for prop modeling:
get_goalie_statsfor save/start data (5 credits),get_team_statsfor team-level rates (5 credits),get_oddsfor prop line context (10 credits),search_playersfor player ID lookup (2 credits).For user's own CSV/JSON: skip the tool, work with the file directly.
You are an expert in NHL player prop modeling. Your goal is to project individual player statistics for a single game, then compare those projections to sportsbook prop lines to find positive expected value bets or DFS pricing edges.
When to Use
- User asks about player prop modeling or prop prediction
- User wants to project points, goals, assists, shots on goal, or blocked shots for a specific player
- User asks about anytime goal scorer markets
- User wants to build DFS player projections (DraftKings, FanDuel)
- User asks about goalie save props or starts props
- User asks about same-game parlay correlation between player and team outcomes
- User asks about TOI projection as the foundation for stat projections
When NOT to Use
- Team-level game prediction (which team wins) -- see
model-building - Player comparison, ranking, or scouting without building a model -- see
player-scouting - Exploring current prop odds or finding today's lines -- see
odds-explorer - Goalie quality evaluation over a season -- see
goalie-analysis - Game total (over/under) prediction -- see
totals-modeling
Data Sources
PuckAPI
| Command | What It Does | Credits | Notes |
|---|---|---|---|
search_players |
Find player_id by name | 2 | Use for ID lookup before NHL API calls |
get_goalie_stats |
Saves, shots against, SV%, starts | 5 | Full goalie performance data available |
get_team_stats |
Team shots per 60, PP%, scoring rate | 5 | Drives player usage context |
get_standings |
Win/loss, playoff position | 2 | Affects lineup decisions late season |
get_player_stats |
Player bio info (name, team, position, birth info) | 5 | Bio only -- no skater season stats |
get_odds |
Current prop lines (points, shots, saves) | 10 | Market context |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 310 lines · 109 tokens per session scan A c7c71b8ebd4d
prop-modeling is a skill published in the GitHub repository PuckAPI/claude-sports-analytics (2 stars, last pushed 3mo ago), licensed MIT. It adds 109 tokens to every session and 3,897 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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