Chapter 11: Key Takeaways

Quick Reference Summary

Possession quality matters more than possession quantity. Measure not just how much of the ball a team has, but what they do with it and where they do it.

Core Concepts

Possession Methods

Possession Sequence

A continuous period of team control, ending when: - Opposing team gains possession - Play stops (out of bounds, foul) - Goal is scored

Essential Metrics

Field Position

Possession Efficiency

Pressing Metrics

Typical Benchmarks

Possession Percentage

PPDA Thresholds

Field Position Benchmarks

Python Quick Reference

Calculate Possession

def calculate_possession(events_df, team_name):
    team_passes = events_df[
        (events_df['team'] == team_name) &
        (events_df['type'] == 'Pass') &
        (events_df['pass_outcome'].isna())
    ]
    total_passes = events_df[
        (events_df['type'] == 'Pass') &
        (events_df['pass_outcome'].isna())
    ]
    return len(team_passes) / len(total_passes)

Calculate PPDA

def calculate_ppda(events_df, pressing_team):
    opponent = get_opponent(events_df, pressing_team)

    opp_passes = events_df[
        (events_df['team'] == opponent) &
        (events_df['type'] == 'Pass') &
        (events_df['location'].apply(lambda x: x[0] < 40 if isinstance(x, list) else False))
    ]

    def_actions = events_df[
        (events_df['team'] == pressing_team) &
        (events_df['type'].isin(['Pressure', 'Tackle', 'Interception'])) &
        (events_df['location'].apply(lambda x: x[0] > 80 if isinstance(x, list) else False))
    ]

    return len(opp_passes) / len(def_actions) if len(def_actions) > 0 else float('inf')

Field Position

def field_position(events_df, team_name):
    team_events = events_df[
        (events_df['team'] == team_name) &
        (events_df['location'].notna())
    ]
    x_coords = [loc[0] for loc in team_events['location'] if isinstance(loc, list)]
    return np.mean(x_coords)

Key Formulas Reference Card

Territorial Index

$$TI = \frac{\bar{X}_{team} - \bar{X}_{opponent}}{120} + 0.5$$

Field Tilt

$$Tilt = \frac{Events_{x > 80}}{Total\_events}$$

PPDA

$$PPDA = \frac{Opponent\_passes\_in\_their\_def\_third}{Your\_def\_actions\_in\_their\_def\_third}$$

Possession Efficiency

$$Efficiency = \frac{xG}{N_{possessions}}$$

xT-Weighted Possession

$$xT\_Poss = \sum_{e} xT(x_e, y_e)$$

The Possession Paradox

Key Insight

More possession ≠ more wins

Evidence

• France won World Cup 2018 with 49% average possession
• Teams with 50-60% possession don't win more than those with 40-50%
• Efficiency (xG per possession) matters more than volume

Implications

1. Track possession quality, not just quantity
2. Measure efficiency (shots/xG per possession sequence)
3. Consider transition opportunities lost with high possession
4. Adapt possession targets to opponent and situation

Style Classifications

Common Mistakes to Avoid

1. Equating possession with dominance: Territory matters more than possession
2. Ignoring possession quality: Where > how much
3. Overlooking transitions: Value of counter-attacks when not possessing
4. Static analysis: Possession patterns change with game state
5. Context blindness: Score, opponent, and match importance affect optimal possession

Practical Workflow

1. Data Preparation

Load events → Filter by team → Extract locations

2. Basic Metrics

Calculate possession % → Field position → Zone control

3. Efficiency Analysis

Identify sequences → Calculate shots/xG per sequence → Compare

4. Pressing Metrics

Calculate PPDA → High turnovers → Counter-pressing rate

5. Visualization

Heatmaps → Zone control maps → Flow diagrams

Applications Summary

Next Chapter Preview

Part III: Player and Team Analysis extends these concepts to individual player contributions, beginning with defensive metrics that complement the attacking focus of possession analysis.