team-analysis

Evaluates teams via standings, stats, division/conference rankings, season trends, and strength of schedule. Use when user asks how a team is doing, where they stand in the division, what their record

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Team Analysis

Default data tool: PuckAPI (puckapi-tool). Use get_standings for current standings and playoff positioning (2 credits), get_team_stats for offensive/defensive metrics (5 credits), list_teams to resolve team names and IDs (1 credit). For user's own team data CSV, skip the tool and work with the file directly.

You are an expert at evaluating teams in context -- standings, performance metrics, schedule difficulty, and trend interpretation. Your goal is to give the user a clear picture of where a team stands and why.

When to Use

  • "How are the [team] doing this season?"
  • "Where do the [team] stand in the [division/conference]?"
  • "What's [team]'s record?"
  • "Who's leading the [division/conference]?"
  • "How does [team A] compare to [team B]?"
  • "What's [team]'s goals-for / goals-against this season?"
  • "Which teams are in a playoff spot right now?"
  • "How hard has [team]'s schedule been?"

When NOT to Use

  • Individual player stats or performance -- see player-scouting
  • Goalie save percentage or goals-against average -- see goalie-analysis
  • Building model features from team stats -- see feature-engineering
  • Predicting a specific game outcome -- see game-preview

Commands Available

Command What It Does Credits
get_standings Current standings by division and conference, includes points, record, pointPct, goalDiff, corsiPct, fenwickPct 2
get_team_stats Team-level offensive and defensive stats for a season 5
list_teams All teams with IDs, cities, names -- use to resolve team identity 1

Commands That Do NOT Exist

Not Available Use Instead
get_power_rankings Derive from get_standings + get_team_stats
get_sos (strength of schedule) Compute from opponents' standings records manually
get_team_advanced_stats get_team_stats and get_standings already return corsiPct, fenwickPct, expectedGoalsFor and expectedGoalsAgainst (5v5). Read those; compute only PDO, which is not returned
get_team_trends Pull get_team_stats for multiple date ranges and compare
get_playoff_odds Not available; derive from standings + games remaining
get_conference_standings Use get_standings filtered by conference

Season Resolution

  • October through December: current calendar year is the season start (2025-26 season)
  • January through September: previous calendar year is the season start (2025-26 season, referenced as 2025)
  • "This season" = season currently in progress or most recently completed
  • "Last season" = one full season prior
  • NHL regular season: October to April. Playoffs: April to June.
  • Standings mid-season reflect games played to date, not projected final standings

Initial Assessment

Before querying, understand:

  1. Single team or comparison? One team snapshot vs. comparing multiple teams vs. full division/conference view.
  2. What metric matters? Points/record, goals for/against, special teams, head-to-head within division?
  3. What season? This season, last season, or multi-year trend?

How It Works

Step 1: Resolve the team(s)

If the team name is ambiguous (e.g., "the Leafs" vs. "Toronto"), use list_teams to confirm ID before pulling stats. This costs 1 credit (cheapest endpoint) and prevents silent wrong results.

Step 2: Choose the right query

User want Tool What to pull
Current standing / record get_standings Points, GP, W-L-OT, pointPct, goalDiff, conference rank
Offensive/defensive stats get_team_stats GF/G, GA/G, goalDiff, corsiPct, fenwickPct, xGF, xGA
Division or conference view get_standings All teams in division/conference
Team comparison get_team_stats for each Side-by-side stat table

Step 3: Read standings correctly

NHL standings require specific interpretation. Always apply these rules:

Points (PTS): Primary sort. 2 points for a win (including OT/SO), 1 point for an OT/SO loss.

Points percentage (pointPct): GP-adjusted metric. Use this for cross-team comparisons when teams have played different numbers of games. pointPct = PTS / (GP * 2).

Goal differential (goalDiff): Goals for minus goals against. A quick proxy for team quality beyond record.

Note: ROW (regulation + overtime wins) is used as a tiebreaker in official NHL standings but is not returned by the PuckAPI API. Use wins and pointPct for comparisons.

Playoff cut line: NHL top 3 in each division qualify automatically; wildcard spots go to next 2 best records per conference regardless of division. A team can be 4th in their division but still make playoffs via wildcard.

Step 4: Compute simple SOS (optional)

If the user asks about schedule difficulty:

  1. Pull opponents' current points percentage (P%) using get_standings
  2. Average opponents' P% = raw SOS estimate
  3. Note: past SOS and future SOS can diverge significantly mid-season

Step 5: Identify trends

For trend questions ("they've been hot lately"), pull get_team_stats for two windows -- full season and last N games -- and compare goalsForPerGame, goalsAgainstPerGame, corsiPct, and fenwickPct. Flag meaningful divergence.

Data Source

PuckAPI (default): Use puckapi-tool endpoints above.

Your own data: If user provides standings or stats CSV:

  1. Verify required columns: team, gp, wins, losses, ot_losses, points for standings; gf, ga for stats
  2. Compute derived metrics yourself: P% = PTS / (GP*2), GF/G = GF/GP
  3. Compute derived metrics: goalDiff = GF - GA, pointPct = PTS / (GP * 2)
  4. Credits are not consumed when working with user's own data

Credit Usage

Operation Credits Notes
Full standings (one call) 2 All teams, all divisions
Team stats (one team, one season) 5 Per query
Team list / ID resolution 1 One-time cost per session
Two-team comparison 10 One get_team_stats call per team
Full division comparison (8 teams) 40 One call per team for stats

Cost note: Standings are 2 credits for the full league snapshot. Pull stats per-team only when needed -- don't pull all 32 teams if the user wants one division.

Anti-patterns

Rationalization Why It's Wrong Do This Instead
"Points are enough to compare teams" Teams may have played different numbers of games mid-season Use P% (points percentage) for fair comparison
"Wins = wins, goal diff is a detail" Goal differential and points percentage reveal team quality beyond win-loss record Always report goalDiff and pointPct alongside points for standings questions
"I'll pull team stats and derive standings" Stats don't include standings context (division rank, wildcard position) Pull get_standings directly; don't reconstruct what the API provides
"The team is 8th -- they missed the playoffs" NHL has wildcard; 4th-in-division can still qualify Always check conference-wide wildcard standings before calling a team eliminated
"SOS is too complex, I'll skip it" Schedule difficulty materially affects record interpretation At minimum, note whether the team has played an above/below average schedule

Output Format

Single team snapshot

[Team] -- [Season]
Record: [W-L-OT] | Points: [N] (pointPct: .XXX) | Goal Diff: [+/-N]
Division rank: [N]th in [Division] | Conference rank: [N]th in [Conference]
Playoff position: [In/Out/On bubble -- wildcard [N]]

Offense: [GF/G] goals/game ([Rank]th in league) | xGF: [N]
Defense: [GA/G] goals allowed/game ([Rank]th in league) | xGA: [N]
Corsi%: [N]% | Fenwick%: [N]%

Division standings table

[Division] Standings -- [Date]
Rank | Team | GP | W | L | OT | PTS | P% | Goal Diff
1.   | ...
...
-- Playoff line --
4.   | ...

Team comparison

            [Team A]    [Team B]
Record      W-L-OT      W-L-OT
Points      N (P%)      N (P%)
Goal Diff   +/-N        +/-N
GF/G        N           N
GA/G        N           N
Corsi%      N%          N%
Fenwick%    N%          N%
xGF         N           N
xGA         N           N

What to Do Next

What You Found Next Action Skill
Team looks interesting, want to preview their next game Pull matchup context, odds, trends game-preview
Want to build model features from team stats Encode GF/G, GA/G, SOS as features feature-engineering
Want to know key players driving the stats Break down by player player-scouting
Want goalie stats contributing to GA/G Goalie-specific analysis goalie-analysis
Team has a favorable schedule ahead, want to find betting edges Compare model vs market edge-detection