How do I know a row is a goalie?

Require the served position to be G before rendering goalie-specific fields.

What if matches_counted is zero?

Render an unavailable sample state. Do not calculate or display zero rates.

Is a depth chart the same as a performance ranking?

No. It describes roster role or ordering, while the stat response describes recorded performance.

Can I add saves props?

Yes where the player-props response holds that market, but its line and freshness remain a separate panel.

Tutorial · 10 min · endpoints verified 2026-09-22

How to build an NHL goalie dashboard

Resolve the goalie and team first, then render position-specific rates only when the underlying box-score sample supports them.

API coverage and endpoint overview: Explore the NHL API

Why this is hard

Goalie rates can look complete while their sample is empty

The shared player-stat shape includes both skater and goalie fields. A goalie dashboard must gate its metrics on position and sample metadata rather than treating every nullable field as zero.

Save percentage and goals-against average are goalie-only fields.
A zero-game sample must not become a 0.000 performance rate.
Depth-chart order and season performance answer different questions.
Goalie headshots and team logos remain nullable media.

Path 1 · recommended

Have your AI agent build it

Use MCP to find the goalie and read player stats; use REST for depth-chart and optional prop context.

1. Connect the MCP server

Add the server in your MCP client and sign in with your Big Balls account. Your client registers itself and handles the token exchange — there is no key to copy.

MCP client configjson

{
  "mcpServers": {
    "bigballs-sports-data": {
      "url": "https://mcp.bigballsdata.com/mcp"
    }
  }
}

2. Tools your agent gets

find_players
Find canonical player IDs by name for use with player-stat tools.
get_player_stats
Per-player career or per-season totals and per-game rates.
get_coverage
Machine-readable map of what we hold and what we do not.

3. Ask for what you want

Paste this at your agent. It is written to make the model check coverage before it designs anything, which is what stops it inventing a field we do not serve.

Prompttext

Build an NHL goalie dashboard. Resolve a canonical goalie id and verify
position G before rendering goalie metrics. Use get_player_stats for save_pct,
gaa and workload fields, and inspect matches_counted before calculating rates.
Use initials when headshot_url is null and never guess a team logo URL.

What the agent cannot reach

MCP covers player identity and stats, but current depth-chart and saves-prop enrichment require REST calls.

Path 2 · hand-coded

Build it yourself

The dashboard begins with canonical identity and validates the goalie sample before displaying performance rates.

01
Resolve a canonical goalie
Search the player surface and require position G. Do not choose the first same-name result without team context.
Find the playerbash
```
curl -s "https://api.bigballsdata.com/v1/players?search=$NAME&sport=ice_hockey" \
  -H "Authorization: Bearer $BBS_API_KEY"
```
02
Fetch goalie aggregates and metadata
Read the shared player-stat response, then inspect position and matches_counted before showing goalie-only rates.
Fetch goalie statsbash
```
curl -s "https://api.bigballsdata.com/v1/players/$PLAYER_ID/stats?sport=ice_hockey" \
  -H "Authorization: Bearer $BBS_API_KEY"
```

Gate every rate on a real sample

Render unavailable when the player is not a goalie, when the sample count is zero, or when the specific metric is null.

Validate the goalie paneltypescript

const canRender = stats.data?.position === 'G' &&
  (stats.meta?.matches_counted ?? 0) > 0;

const savePct = canRender ? stats.data?.save_pct ?? null : null;
const gaa = canRender ? stats.data?.gaa ?? null : null;

Reference

Every endpoint this tutorial uses

All on the gateway at api.bigballsdata.com. Verified against production on 2026-09-22.

Method	Path	Returns	Why you need it	Plan
GET	/v1/players/:id/stats?sport=ice_hockey	Position-aware player totals and per-game rates with sample metadata	The core goalie performance panel. Read the goalie-stat guide.	Free
GET	/v1/teams/:id/depth-chart	Current team depth-chart context where populated	Optional roster-role context; not a replacement for performance stats.	Free

Pricing, honestly

The core goalie dashboard works on Free

Identity, player stats and current depth-chart context have Free entry points. Solo rolling form or projections are optional additions with separate availability rules.

Free goalie profile

texttext

GET /v1/players/:id/stats?sport=ice_hockey
GET /v1/teams/:id/depth-chart

Optional Solo models

texttext

GET /v1/players/:id/rolling-stats
GET /v1/players/:id/season-projection

Free supplies the core goalie aggregates.
A zero sample remains unavailable.
Solo models do not repair missing historical rows.
Saves props are a separate freshness-sensitive surface.

See the full plan ladder →

Other build guides

Known gaps

What the first dashboard leaves out

Keep role, performance and market data separate.

No inferred starter designation from one recent appearance.
No zero-filled save percentage for an empty sample.
No guessed headshot or crest when media is null.

Questions

How do I know a row is a goalie?: Require the served position to be G before rendering goalie-specific fields.
What if matches_counted is zero?: Render an unavailable sample state. Do not calculate or display zero rates.
Is a depth chart the same as a performance ranking?: No. It describes roster role or ordering, while the stat response describes recorded performance.
Can I add saves props?: Yes where the player-props response holds that market, but its line and freshness remain a separate panel.

Related APIs

Other APIs you can build with:

NHL API — Scores, xG, Props & Stats Free Ice Hockey API: Scores & Stats

Also on this sport

NHL Player Props API Injury Data API for Developers: Free

Stats reference

NHL Stats API

Build the goalie dashboard

Verify identity, position and sample before the first rate reaches the screen.