Exercises: Situational Football

Exercise 1: Red Zone Calculation

A team had the following red zone results over a season:

Calculate: - Total red zone trips - TD rate - Points per trip - Overall scoring rate

Exercise 2: Third Down Analysis

A team's third down results by distance:

Calculate conversion rates for each distance category and overall. How does each compare to league average?

Exercise 3: Two-Minute Drill Evaluation

A team had 12 two-minute drives with these results:

Calculate the scoring rate and evaluate against league benchmarks.

Exercise 4: Late and Close Performance

A team's EPA in different game situations:

Calculate EPA per play for each and determine if the team performs better or worse in high-leverage situations.

Exercise 5: Goal Line Efficiency

A team's results from the 1-2 yard line:

Calculate TD rates by play type. Which is more efficient?

Exercise 6: Leverage Weighting

Calculate leverage-weighted EPA for these plays:

Compare to unweighted EPA.

Exercise 7: Red Zone Defense

A defense faced 58 red zone trips and allowed: - 30 touchdowns - 22 field goals - 6 stops (no score)

Calculate the defensive red zone TD rate and points per trip allowed.

Exercise 8: Third Down Defense

A defense's third down results:

Calculate conversion rate allowed for each distance. Identify strengths and weaknesses.

Exercise 9: Situational Comparison

Compare two teams' situational performance:

Which team is better situationally? Which might be overperforming their base efficiency?

Exercise 10: Clutch Analysis

A team's late/close performance over three seasons:

Does this team appear to have a "clutch" skill?

Exercise 11: Two-Minute EPA

A team's two-minute drive data:

Calculate average EPA per play and per drive.

Exercise 12: Situational Pass Rate

A team's pass rates by situation:

Which situations show the most pass rate adjustment? Is this appropriate?

Exercise 13: Red Zone Efficiency Trend

A team's red zone TD rate over five seasons:

Calculate the average and identify if there's a consistent pattern.

Exercise 14: Third Down Context

Analyze why a team might have these third down rates:

What's causing the poor overall rate despite good short-yardage performance?

Exercise 15: Points vs Touchdowns

Two teams with different red zone approaches:

Calculate TD rate and points per trip for each. Which approach is better?

Programming Exercises

Exercise 16: Red Zone Analyzer

Write a function to analyze red zone performance:

def analyze_red_zone(pbp: pd.DataFrame, team: str) -> dict:
    """
    Comprehensive red zone analysis.

    Returns:
    - trips
    - td_rate
    - points_per_trip
    - pass_rate_rz
    - epa_rz
    - by_yard_line (breakdowns by 1-5, 6-10, 11-20)
    """
    pass

Exercise 17: Third Down Calculator

Build a third down analysis function:

def analyze_third_downs(pbp: pd.DataFrame, team: str) -> pd.DataFrame:
    """
    Return DataFrame with third down stats by distance bucket.

    Columns: distance_bucket, attempts, conversions, rate, epa, pass_rate
    """
    pass

Exercise 18: Situational Comparison Tool

Create a function to compare situational vs overall performance:

def compare_situational(pbp: pd.DataFrame, team: str) -> dict:
    """
    Compare team's situational vs overall performance.

    Returns dict with:
    - overall_epa
    - red_zone_epa
    - third_down_epa
    - late_close_epa
    - two_min_epa
    - Each includes difference from overall
    """
    pass

Exercise 19: Clutch Tester

Write a function to test clutch consistency:

def test_clutch_consistency(
    pbp_by_year: dict,
    team: str
) -> dict:
    """
    Test whether clutch performance is consistent across years.

    Returns:
    - yearly_clutch_diff (list)
    - year_over_year_correlation
    - is_clutch_consistent (bool, if r > 0.3)
    """
    pass

Exercise 20: Situational Report Generator

Build a comprehensive situational report:

def generate_situational_report(
    pbp: pd.DataFrame,
    team: str,
    season: int
) -> str:
    """
    Generate text report covering all situational categories.

    Include:
    - Red zone summary
    - Third down breakdown
    - Two-minute evaluation
    - Late/close performance
    - Comparisons to league average
    - Strengths and weaknesses
    """
    pass

Challenge Exercises

Challenge 1: Expected Red Zone Touchdowns

Build a model to predict expected red zone touchdowns:

1. Calculate league-average TD rates by yard line
2. For each team, sum expected TDs based on their trips at each yard line
3. Compare expected to actual
4. Identify teams over/underperforming expectation

Challenge 2: Third Down Situation Difficulty

Create a difficulty-adjusted third down metric:

1. Model expected conversion rate by distance, field position, score
2. Calculate "conversions above expected" for each team
3. Identify teams that convert at higher rates than situation would suggest

Challenge 3: Late Game Win Probability Impact

Analyze which teams most impact late-game outcomes:

1. Filter to plays with WP between 30-70%
2. Calculate average WPA (win probability added) per play
3. Compare offense and defense
4. Identify teams that consistently swing games

Challenge 4: Situational Stability Analysis

Test which situational metrics are most stable year-to-year:

1. Load 3+ years of data
2. Calculate situational metrics for each team-year
3. Compute year-to-year correlations
4. Rank metrics by stability
5. Determine which are predictive vs random

Challenge 5: Complete Situational Dashboard

Build an interactive situational analysis tool:

1. Calculate all situational metrics for all teams
2. Create rankings for each category
3. Build composite situational score
4. Generate visualizations
5. Compare offense vs defense
6. Track trends over season

Solutions

Solutions are available in code/exercise-solutions.py