Player Stats & Profiles

This vignette covers pulling career stats for individual players and season-level statistics for all players on a team. Player IDs come from the team roster endpoints.

---

Setup

from slapyshot import NHLClient
import polars as pl

client = NHLClient()

# Get a player ID from a roster
teams = client.teams.get_all_teams()
team_id = teams.filter(pl.col("name") == "Avalanche")["id"][0]

roster = client.teams.get_team_roster(team_id)
player_id = roster.filter(
    pl.col("full_name").str.contains("MacKinnon")
)["id"][0]

---

Player Profile

get_player_profile() returns career statistics broken down by season. One row per season-team combination.

profile = client.players.get_player_profile(player_id)
print(profile)

Columns returned: player_id, full_name, primary_position, season_year, season_type, team_id, team_name, games_played, goals, assists, points, plus_minus, shots, penalty_minutes

Regular season career stats only

reg_season = profile.filter(pl.col("season_type") == "REG")
print(reg_season.sort("season_year", descending=True))

Most recent season

latest = (
    profile
    .filter(pl.col("season_type") == "REG")
    .sort("season_year", descending=True)
    .head(1)
)
print(latest)

Career totals

career_totals = (
    profile
    .filter(pl.col("season_type") == "REG")
    .select(["goals", "assists", "points", "games_played", "shots"])
    .sum()
)
print(career_totals)

Points per season (chart-ready)

points_by_year = (
    profile
    .filter(pl.col("season_type") == "REG")
    .select(["season_year", "points", "goals", "assists"])
    .sort("season_year")
)
print(points_by_year)

---

Team Season Stats

get_player_season_stats() returns stats for every player on a specific team for a given season. One row per player — useful for leaderboards and team comparisons.

stats = client.players.get_player_season_stats(
    season_year=2025,
    season_type="REG",
    team_id=team_id,
)
print(stats)

Columns returned: team_id, team_name, player_id, full_name, primary_position, games_played, goals, assists, points, plus_minus, shots, penalty_minutes

season_year is the starting year

The 2025-26 season uses season_year=2025. The 2024-25 season uses season_year=2024.

Team scoring leaderboard

leaderboard = (
    stats
    .sort("points", descending=True)
    .select(["full_name", "primary_position", "goals", "assists", "points"])
)
print(leaderboard)

20-goal scorers

goal_scorers = stats.filter(pl.col("goals") >= 20)
print(goal_scorers.sort("goals", descending=True))

Plus/minus leaders

plus_minus = (
    stats
    .sort("plus_minus", descending=True)
    .select(["full_name", "primary_position", "plus_minus", "points"])
)
print(plus_minus)

Points per game (minimum 20 games played)

ppg = (
    stats
    .filter(pl.col("games_played") >= 20)
    .with_columns(
        (pl.col("points") / pl.col("games_played")).alias("points_per_game")
    )
    .sort("points_per_game", descending=True)
    .select(["full_name", "games_played", "points", "points_per_game"])
)
print(ppg)

Compare two teams

Pull stats for both teams and stack them to compare:

teams = client.teams.get_all_teams()

avs_id = teams.filter(pl.col("name") == "Avalanche")["id"][0]
blues_id = teams.filter(pl.col("name") == "Blues")["id"][0]

avs_stats = client.players.get_player_season_stats(2025, "REG", avs_id)
blues_stats = client.players.get_player_season_stats(2025, "REG", blues_id)

combined = pl.concat([avs_stats, blues_stats])
print(combined.sort("points", descending=True).head(20))

---

Typical Workflow

graph LR
    A[get_all_teams] -->|team_id| B[get_team_roster]
    B -->|player_id| C[get_player_profile]
    A -->|team_id| D[get_player_season_stats]

Player IDs are permanent

SportRadar player IDs never change. Once you find a player's ID, you can hardcode it or store it in a config rather than looking it up every time.