Add pressing & transitional play analysis for Arsenal 1-1 Man City (Sep 2025)

[zhub9006]

Pressing & Transitional Play Analysis — Arsenal 1-1 Man City (Sep 21, 2025)

This PR adds a practical Python script for analyzing pressing patterns and transitional moments, motivated by the tactical richness of this specific Premier League fixture.

Why This Match

Arsenal 1-1 Man City (Haaland 9', Martinelli 90+3') is an excellent case study for pressing/transitional analysis:

• City's record-low 32.8% possession under Guardiola shows how a compact low block can neutralize high pressing
• Halftime subs (Eze, Saka) visibly changed pressing geometry — great material for pre/post comparison
• Both transition goals (City's first-attack counter, Arsenal's 90+3 chip) perfectly illustrate the value of quantitative transition metrics

What's Added

New file: 08. Latest Work & Codes/pressing_transitional_analysis.py

The script includes four analysis functions:

1. ball_recovery_map() — Visualize where each team won the ball (high press zone vs counter outlet)
2. pressing_heatmap() — 2D density heatmaps from Statsbomb pressure events (pre/post subs)
3. transitional_sequence_map() — Annotated arrows tracing the two defining transitional moments
4. verticality_bar_chart() — Metric comparison across verticality & transition categories

Statsbomb Integration

The script references these Statsbomb Open Data fields directly relevant to pressing analysis:

• ball_recovery_place — positional pressing success
• pressure_place — where each team pressed
• Related events — chaining press → pass → carry sequences
• Timestamps — transition speed (<3 seconds from recovery to shot)

Usage

python 08. Latest Work & Codes/pressing_transitional_analysis.py

Generates 4 plots + text summary with all post-match observations.

Related Issue

Closes the community discussion about adding pressing/transitional analysis capabilities to the repo's event data notebooks.

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Data sources: BBC Sport live text, Arsenal.com match report (Sep 21, 2025), Metro, ESPN. Statsbomb Open Data.