[line-win-probability] Win Probability Chart

[MarkusNeusinger]

Description

A win probability chart shows how each team's probability of winning evolves over the course of a game. The line starts at ~50% and fluctuates based on scoring events, reaching 100% or 0% at game end. Used across all major sports.

Applications

• Visualizing game momentum shifts and critical plays
• Identifying turning points in close games
• Sports broadcasting and journalism
• Evaluating team performance under pressure

Data

• game_time (numeric) — elapsed time or play number
• win_probability (numeric) — probability of home team winning (0 to 1)
• event (categorical, optional) — scoring events for annotation
• Size: 50-300 data points per game

Notes

• Y-axis from 0% to 100%, with 50% baseline highlighted
• Fill area above/below 50% with team colors
• Annotate key scoring events that caused probability swings
• Show final score in corner

[claude]

✅ Spec ID: line-win-probability

Rationale: A line chart showing win probability over game time with filled areas and event annotations — a well-established sports analytics visualization distinct from existing line/area specs.

Add label approved to begin generation.

[github-actions]

✅ Specification Ready: line-win-probability

PR: #4443

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specification.md

line-win-probability: Win Probability Chart

Description

A win probability chart shows how each team's likelihood of winning evolves over the course of a game. The line starts near 50% and fluctuates based on scoring events, ultimately reaching 100% or 0% at game end. The area above and below the 50% baseline is filled with team colors to convey momentum at a glance. This visualization is widely used across major sports for post-game analysis and live broadcasting.

Applications

• Visualizing game momentum shifts and identifying critical turning points in close contests
• Sports broadcasting overlays showing real-time win probability during live games
• Post-game journalism and analysis highlighting the most impactful plays
• Evaluating team resilience and performance under pressure across a season

Data

• game_time (numeric) - Elapsed time in minutes or play/event number from start to end of game
• win_probability (numeric) - Probability of the home team winning, ranging from 0 to 1
• event (categorical, optional) - Labels for key scoring events or plays to annotate on the chart
• Size: 50-300 data points per game
• Example: An NFL game with play-by-play win probability from a model, annotated with touchdowns and field goals

Notes

• Y-axis should range from 0% to 100% with a prominent horizontal reference line at 50%
• Fill the area above 50% with the home team color and below 50% with the away team color
• Annotate key scoring events (touchdowns, goals, runs) that caused significant probability swings
• Display the final score in a corner annotation or subtitle
• X-axis represents game progression (time or play number) with appropriate period/quarter markers

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Next: Add approved label to merge this specification to main.

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🤖 spec-create workflow

[github-actions]

🚀 Specification Merged!

Specification: line-win-probability
PR: #4443 (merged)

The specification is now in main and synced to PostgreSQL.

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Next: Add generate:{library} labels to start generating implementations.

Available libraries: matplotlib, seaborn, plotly, bokeh, altair, plotnine, pygal, highcharts, letsplot

Or use workflow dispatch for bulk operations.

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🤖 spec-create workflow