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CI Health Check & Quality Gate / Code, dbt & Live App Health Check (pull_request) Successful in 1m11s
CI Health Check & Quality Gate / Code, dbt & Live App Health Check (pull_request) Successful in 1m11s
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import plotly.express as px
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import streamlit as st
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from streamlit_echarts import st_echarts
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from utils.charts import AMBER, apply_arena_theme
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from utils.db import get_selected_season, query
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SEASON, SEASON_LABEL = get_selected_season()
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st.title(f":material/dashboard: League Pulse — {SEASON_LABEL}")
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# --- KPIs with delta vs prior season ---
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summary = query(
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"""
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SELECT count(*) AS total_games,
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sum(CASE WHEN is_overtime THEN 1 ELSE 0 END) AS ot_games,
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round(avg(total_points), 1) AS avg_pts,
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round(avg(point_differential), 1) AS avg_margin,
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round(100.0 * sum(CASE WHEN is_home_team_winner THEN 1 ELSE 0 END) / count(*), 1) AS home_win_pct,
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min(game_date) AS first_game,
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max(game_date) AS last_game
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FROM main_marts.fct_game_results
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WHERE season_key IN (SELECT season_key FROM main_marts.dim_seasons WHERE season_start_year = ?)
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""",
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[SEASON],
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)
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prior = query(
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"""
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SELECT round(avg(total_points), 1) AS avg_pts,
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round(avg(point_differential), 1) AS avg_margin,
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round(100.0 * sum(CASE WHEN is_home_team_winner THEN 1 ELSE 0 END) / count(*), 1) AS home_win_pct
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FROM main_marts.fct_game_results
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WHERE season_key IN (SELECT season_key FROM main_marts.dim_seasons WHERE season_start_year = ?)
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""",
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[SEASON - 1],
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)
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has_prior = not prior.empty and prior["avg_pts"][0] is not None
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c1, c2, c3, c4, c5 = st.columns(5)
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c1.metric("Total Games", f"{summary['total_games'][0]:,}")
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c2.metric(
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"Avg Points/Game",
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summary["avg_pts"][0],
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delta=f"{summary['avg_pts'][0] - prior['avg_pts'][0]:+.1f}" if has_prior else None,
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)
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c3.metric(
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"Avg Margin",
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summary["avg_margin"][0],
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delta=f"{summary['avg_margin'][0] - prior['avg_margin'][0]:+.1f}" if has_prior else None,
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)
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c4.metric(
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"Home Win %",
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f"{summary['home_win_pct'][0]}%",
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delta=f"{summary['home_win_pct'][0] - prior['home_win_pct'][0]:+.1f}%" if has_prior else None,
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)
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c5.metric("OT Games", f"{summary['ot_games'][0]:,}")
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st.caption(f"Season: {summary['first_game'][0]} → {summary['last_game'][0]} | Deltas vs prior season")
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# --- Row 2: Competitiveness donut + Top standings ---
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col1, col2 = st.columns(2)
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with col1:
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comp = query(
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"""
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SELECT game_competitiveness_tier AS tier, count(*) AS games
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FROM main_marts.fct_game_results
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WHERE season_key IN (SELECT season_key FROM main_marts.dim_seasons WHERE season_start_year = ?)
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GROUP BY tier ORDER BY games DESC
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""",
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[SEASON],
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)
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fig = px.pie(
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comp,
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names="tier",
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values="games",
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title="Game Competitiveness",
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hole=0.4,
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color_discrete_sequence=px.colors.qualitative.Set2,
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)
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fig.update_traces(textinfo="percent+label")
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apply_arena_theme(fig)
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st.plotly_chart(fig, width="stretch")
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with col2:
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standings = query(
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"""
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SELECT team, count(*) AS games,
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sum(CASE WHEN game_result = 'W' THEN 1 ELSE 0 END) AS wins,
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sum(CASE WHEN game_result = 'L' THEN 1 ELSE 0 END) AS losses,
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round(100.0 * sum(CASE WHEN game_result = 'W' THEN 1 ELSE 0 END) / count(*), 1) AS win_pct,
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round(avg(net_rating), 1) AS net_rtg
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FROM main_intermediate.int_team_performance
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WHERE season_start_year = ?
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GROUP BY team ORDER BY win_pct DESC LIMIT 8
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""",
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[SEASON],
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)
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st.subheader(":material/emoji_events: Top Teams")
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st.dataframe(
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standings,
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column_config={
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"win_pct": st.column_config.ProgressColumn(
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"Win%", min_value=0, max_value=100, format="%.1f%%"
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),
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},
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hide_index=True,
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width="stretch",
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)
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# --- Row 3: Weekly scoring trend ---
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weekly = query(
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"""
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SELECT date_trunc('week', game_date)::date::varchar AS week,
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count(*) AS games,
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round(avg(total_points), 1) AS avg_pts,
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round(avg(point_differential), 1) AS avg_margin
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FROM main_marts.fct_game_results
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WHERE season_key IN (SELECT season_key FROM main_marts.dim_seasons WHERE season_start_year = ?)
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GROUP BY week ORDER BY week
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""",
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[SEASON],
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)
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fig_weekly = px.area(
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weekly,
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x="week",
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y="avg_pts",
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title="Weekly Scoring Trend",
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color_discrete_sequence=[AMBER],
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)
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fig_weekly.update_layout(xaxis_title="Week", yaxis_title="Avg Total Points")
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apply_arena_theme(fig_weekly, height=350)
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st.plotly_chart(fig_weekly, width="stretch")
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# --- Row 4: Calendar heatmap + Season highlights ---
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col1, col2 = st.columns([2, 1])
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with col1:
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cal_data = query(
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"""
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SELECT game_date::varchar AS day, count(*) AS games
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FROM main_marts.fct_game_results
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WHERE season_key IN (SELECT season_key FROM main_marts.dim_seasons WHERE season_start_year = ?)
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GROUP BY game_date ORDER BY game_date
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""",
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[SEASON],
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)
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if not cal_data.empty:
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cal_list = cal_data.values.tolist()
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cal_option = {
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"tooltip": {"position": "top", "formatter": "{c0} games on {b0}"},
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"visualMap": {
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"min": 0,
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"max": int(cal_data["games"].max()),
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"calculable": True,
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"orient": "horizontal",
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"left": "center",
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"top": "top",
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"inRange": {"color": ["#151D2A", "#9be9a8", "#40c463", "#30a14e", "#10B981"]},
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},
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"calendar": {
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"range": [cal_list[0][0][:7], cal_list[-1][0][:7]],
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"cellSize": ["auto", 15],
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},
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"series": [{"type": "heatmap", "coordinateSystem": "calendar", "data": cal_list}],
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}
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st_echarts(options=cal_option, height="200px")
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with col2:
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st.subheader(":material/local_fire_department: Top Performances")
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highlights = query(
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"""
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SELECT player_name AS player, team,
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game_date::date::varchar AS date, points AS pts,
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assists AS ast, total_rebounds AS reb
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FROM main_intermediate.int_player_performance
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WHERE season_start_year = ?
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ORDER BY points DESC LIMIT 5
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""",
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[SEASON],
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)
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st.dataframe(highlights, hide_index=True, width="stretch")
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# --- Row 5: Recent games ---
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st.subheader("Recent Games")
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games = query(
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"""
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SELECT g.game_date, ht.team_abbr AS home, vt.team_abbr AS away,
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g.home_points, g.visitor_points, wt.team_abbr AS winner,
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g.point_differential AS margin, g.game_competitiveness_tier AS type
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FROM main_marts.fct_game_results g
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LEFT JOIN main_marts.dim_teams ht ON g.home_team_key = ht.team_key
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LEFT JOIN main_marts.dim_teams vt ON g.visitor_team_key = vt.team_key
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LEFT JOIN main_marts.dim_teams wt ON g.winning_team_key = wt.team_key
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WHERE g.season_key IN (SELECT season_key FROM main_marts.dim_seasons WHERE season_start_year = ?)
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ORDER BY g.game_date DESC LIMIT 25
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""",
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[SEASON],
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)
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st.dataframe(games, hide_index=True, width="stretch")
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