Key Takeaways: Pace and Play Calling

One-page reference for Chapter 13 concepts


Pace Metrics

# Plays per game
plays_per_game = total_plays / games_played

# Seconds per play (within drives)
seconds_per_play = (prev_clock - current_clock).mean()

# Neutral pace (close games, early downs)
neutral_pace = neutral_plays / games

Pace Benchmarks

Tempo Plays/Game Seconds/Play
Fast 68-72 < 25
Average 62-65 26-29
Slow 56-60 > 30

Pass Rate Metrics

# Overall pass rate
pass_rate = passes / (passes + rushes)

# Neutral pass rate (key metric)
neutral_pass = neutral_passes / neutral_plays
# Neutral = 1st/2nd down, score ±7, WP 30-70%

# Early down pass rate
early_down_pass = early_passes / early_plays

League Pass Rate Context

Category Pass Rate
League Average ~58%
High-Pass Teams 62-68%
Run-Heavy Teams 50-55%

Pass vs Rush Efficiency

# Typical league values
pass_epa = +0.05  # Positive on average
rush_epa = -0.03  # Negative on average
pass_premium = pass_epa - rush_epa  # ~0.08

Key insight: Passing is more efficient, but has higher variance.


Game Script Effects

Score State Expected Pass Rate
Down 14+ 70-80%
Down 7-13 60-70%
Down 1-6 55-60%
Tied 50-55%
Up 1-6 50-55%
Up 7-13 45-50%
Up 14+ 35-45%

Fourth Down Decision Framework

# Expected value of going for it
ev_go = (conv_prob * ep_success) + ((1 - conv_prob) * ep_failure)

# Expected value of field goal
ev_fg = (fg_prob * 3) + ((1 - fg_prob) * ep_miss)

# Expected value of punt
ev_punt = -ep_at_opponent_position

Fourth Down Conversion Rates

Distance Conversion Probability
1 yard ~73%
2 yards ~63%
3 yards ~55%
4 yards ~48%
5 yards ~44%

Predictability Analysis

# Shannon entropy (higher = less predictable)
entropy = -p * log2(p) - (1-p) * log2(1-p)

# Maximum entropy = 1.0 (50/50 pass/run)
# Low entropy = predictable tendencies

Situational Pass Rates

Situation Typical Pass Rate
1st & 10 50-55%
2nd & Short 40-50%
2nd & Long 60-70%
3rd & Short 45-55%
3rd & Long 85-95%

Key Correlations

Relationship Correlation
Pass Rate vs Off EPA r ≈ 0.40-0.55
Pace vs EPA r ≈ 0.20-0.30
Neutral Pass Rate vs Wins r ≈ 0.35-0.45

Common Inefficiencies

  1. Too conservative on 4th down - Most teams punt too often
  2. Under-passing early - 1st down pass rates often too low
  3. Over-running when ahead - Leading teams run too much
  4. Predictable tendencies - Formation-based tells

Formation Tendency Analysis

# Pass rate by formation
formation_pass_rate = (
    plays.groupby('formation')
    .apply(lambda x: (x['play_type'] == 'pass').mean())
)

# Identify tell formations
tells = formation_pass_rate[
    (formation_pass_rate > 0.75) |
    (formation_pass_rate < 0.25)
]

Practical Applications

Use Case Best Metric
Offensive philosophy Neutral pass rate
Game planning Situational tendencies
Coaching evaluation 4th down decisions
Predictability Conditional entropy

Key Insights

  1. Neutral pass rate isolates true offensive philosophy
  2. Passing is more efficient but higher variance than rushing
  3. Game script explains most pass rate variation
  4. 4th down analytics identify conservative coaching
  5. Predictability can be measured and exploited

Preview: Chapter 14

Next: Situational Football - red zone, third downs, two-minute drills, and critical game situations.