Exercises: Schedule and Rest Analysis

Section 1: Bye Week Fundamentals

Exercise 1: Basic Bye Week Adjustment

Given Data: - Team A is coming off their bye week (Week 7 bye) - Team B played last week (normal rest) - Both teams normally get 6 days rest

Tasks: a) Calculate the base bye week adjustment for Team A b) What is the bye timing multiplier for a Week 7 bye? c) Calculate the total bye-adjusted point value for Team A d) If Team B's power rating is +2.0 and Team A's is +1.5, what is the adjusted spread?

Exercise 2: Late Bye Week Analysis

Scenario: - Week 13 game: Seahawks vs Cardinals - Seahawks coming off Week 12 bye (very late) - Cardinals had normal Week 6 bye (played last week normally)

Tasks: a) What timing multiplier applies to Seattle's bye? b) Calculate Seattle's total bye advantage in points c) How does this compare to a team with a Week 5 bye coming off rest? d) Why do late byes provide larger advantages?

Exercise 3: Both Teams Off Bye

Situation: Two division rivals meet in Week 10, both coming off their bye weeks.

Tasks: a) Calculate the bye week effect when both teams are rested b) Does the home team gain any schedule advantage? c) How should you adjust your model for this scenario? d) What other factors become more important when bye effects neutralize?

Section 2: Short Week Analysis

Exercise 4: Thursday Night Football Calculations

Game: Week 8 Thursday Night Football - Home team: Played Sunday (10 days ago - off bye) - Away team: Played Sunday (4 days ago - normal)

Tasks: a) Calculate the rest differential in days b) What is the standard TNF away team penalty? c) How does the home team's bye affect this calculation? d) Calculate the total schedule advantage for the home team

Exercise 5: Monday-to-Thursday Scenario

Critical Situation: - Away team played Monday Night Football in Week 7 - Now playing Thursday Night in Week 8 (away) - Home team played Sunday in Week 7

Tasks: a) How many days rest does each team have? b) Calculate the extreme short-rest penalty for the away team c) What is the total schedule adjustment? d) Should this game be considered a "trap" for the away team?

Exercise 6: Saturday Games

Scenario: Week 15 Saturday doubleheader - Game 1: Both teams played Sunday (6 days rest) - Game 2: Home team played Thursday (8 days), Away played Sunday (6 days)

Tasks: a) Calculate rest differentials for both games b) Convert rest differential to point adjustments c) Which game has a larger schedule-based advantage? d) How do Saturday games compare to Thursday games for competitive balance?

Section 3: Strength of Schedule

Exercise 7: SOS Calculation

Team X's Opponents' Records (first 8 weeks): | Week | Opponent | Record | |------|----------|--------| | 1 | Team A | 5-3 | | 2 | Team B | 3-5 | | 3 | Team C | 6-2 | | 4 | Team D | 4-4 | | 5 | Team E | 7-1 | | 6 | Team F | 2-6 | | 7 | Team G | 4-4 | | 8 | Team H | 5-3 |

Tasks: a) Calculate Team X's SOS using opponent win percentage b) Convert to point differential equivalent c) If Team X is 5-3, what might their "true" record be after SOS adjustment? d) How would you weight recent opponents more heavily?

Exercise 8: Future SOS Impact

Playoff Race Scenario: - Team Y (9-5) has remaining opponents with combined 30-18 record - Team Z (9-5) has remaining opponents with combined 18-30 record

Tasks: a) Calculate each team's remaining SOS b) Project expected wins for each team (assume 50% baseline) c) How much does SOS affect playoff probability? d) Which team should be favored to make playoffs?

Exercise 9: Retrospective SOS Adjustment

End-of-Season Analysis: - Team had 11-6 record - Opponents' final combined record: 120-168 (.417) - League average SOS would be .500

Tasks: a) Calculate the SOS differential from league average b) Estimate how many wins came from easy schedule c) What would be Team's SOS-adjusted win total? d) How does this affect playoff seeding evaluation?

Section 4: Travel Effects

Exercise 10: Cross-Country Travel

Game: Bills at Chargers (4:25 PM ET start) - Buffalo is Eastern timezone - Los Angeles is Pacific timezone - Distance: ~2,400 miles

Tasks: a) Calculate timezone difference b) Apply travel adjustment formula c) Does game time affect the adjustment? d) Calculate total travel impact on the spread

Exercise 11: West-to-East Travel

Scenario: 49ers at Panthers (1:00 PM ET kickoff) - San Francisco: Pacific timezone - Charlotte: Eastern timezone - Early start for West Coast team

Tasks: a) What is the base timezone adjustment? b) Apply the West-to-East directional penalty c) How does the 1:00 PM ET start compound the issue? d) Calculate total travel/time adjustment

Exercise 12: Divisional Travel Comparison

Compare two divisional games: - Game A: Chiefs at Raiders (same division, 2 TZ difference) - Game B: Cowboys at Eagles (same division, 0 TZ difference)

Tasks: a) Calculate travel adjustment for each game b) How does divisional familiarity offset travel? c) Which game has a larger schedule component to HFA? d) Why might travel effects be reduced for rivals?

Section 5: Combined Schedule Factors

Exercise 13: Complete Schedule Adjustment

Week 14 Game: Ravens at Broncos

Context: - Ravens played Sunday (normal 7 days rest) - Broncos off bye (Week 13 bye - late) - Denver: Mountain timezone, Baltimore: Eastern - Game is Sunday Night Football - Temperature forecast: 25°F

Tasks: a) Calculate bye week adjustment for Denver b) Calculate rest differential c) Add travel adjustment (2 timezone difference, East-to-West) d) Add primetime adjustment e) Calculate total schedule-based advantage for Denver

Exercise 14: Thursday Night Special

Thanksgiving Day Game: - Lions (home) played Sunday - Bears (away) played Monday Night

Tasks: a) Calculate rest for each team b) Apply TNF/holiday adjustment c) Is there additional dome advantage? d) Calculate total schedule impact e) How significant is this compared to normal HFA?

Exercise 15: Season Finale Scenario

Week 18: Playoff implications - Team A (home): Clinched playoff spot, likely to rest starters - Team B (away): Must win for playoffs - Both played Sunday, normal rest - Travel: 1 timezone

Tasks: a) Calculate base schedule adjustments b) How does motivation factor in? c) Should you adjust for potential rest? d) What's the "true" spread given all factors?

Section 6: International Games

Exercise 16: London Game Analysis

NFL London Game: - Jaguars (designated home) vs Falcons - Both teams traveling from US - Game at 9:30 AM ET (2:30 PM local)

Tasks: a) Calculate travel penalty for each team b) How does "home" designation work for HFA? c) Apply time difference adjustment d) What is the net schedule impact?

Exercise 17: Mexico City Game

NFL Mexico City: - Chiefs (designated home) vs Chargers - Chiefs: 1-hour flight, Chargers: 3-hour flight - Altitude: 7,350 feet - Monday Night game

Tasks: a) Calculate travel differential b) Apply altitude adjustment c) How does the "home" team benefit? d) Calculate total adjustments vs normal KC home game

Section 7: Model Building

Exercise 18: Schedule Impact Model

Build a complete schedule adjustment model:

Required inputs: - Home team rest days - Away team rest days - Home off bye (Y/N) - Away off bye (Y/N) - Timezone difference - Travel direction (E→W, W→E, N/S) - Game type (Sunday, TNF, MNF)

Tasks: a) Write pseudocode for the complete adjustment function b) What are reasonable bounds for total adjustment? c) How would you weight each component? d) How would you validate this model?

Exercise 19: Historical Analysis

Using this historical data:

Season	Bye Team Win%	Bye Team ATS%	Avg Margin
2019	57%	54%	+2.1
2020	55%	52%	+1.8
2021	58%	55%	+2.4
2022	54%	51%	+1.6
2023	56%	53%	+2.0

Tasks: a) Calculate average bye week advantage across seasons b) Is the ATS advantage statistically significant? c) What does the margin data suggest about market pricing? d) How would you use this to adjust your predictions?

Exercise 20: Complete Game Prediction

Week 10 Matchup: Packers at Bears

Given Information: - Packers (5-3): Coming off Week 9 bye, played Week 8 in London - Bears (3-5): Played Sunday in Week 9 - Lambeau: Cold weather expected (35°F), division rivalry - Sunday Night Football - Power ratings: GB +3.2, CHI -1.5

Wait - this is at Bears (Soldier Field): - Bears (home) played Sunday - Packers (away) off bye, played in London Week 8

Tasks: a) Calculate all schedule components: - Bye week adjustment for Green Bay - Any post-London penalty? - Travel adjustment (minimal - 1 timezone) - Primetime factor - Divisional reduction

b) Sum total schedule impact

c) Combine with: - Power rating differential (3.2 - (-1.5) = 4.7 for GB) - Standard away team adjustment - Weather (dome team GB vs cold-weather CHI - wait, neither is dome)

d) Calculate final predicted spread

e) If market has CHI +3.5, is there value?

Answer Key Guidance

Exercise 1:

a) Base bye = +1.2 points b) Week 7 = Standard timing, multiplier = 1.0 c) Total = 1.2 × 1.0 = 1.2 points d) Spread = (2.0 - 1.5) - 2.3 (HFA) - 1.2 (bye) = -3.0 (Team B favored by 3)

Exercise 4:

a) Rest: Home 10 days, Away 4 days = +6 day differential b) Standard TNF away penalty: -1.5 points c) Home off bye adds +1.2 points d) Total: 1.5 + 1.2 = 2.7 points advantage to home

Exercise 7:

a) Combined: 36-28 = .563 win%, SOS = +0.063 above .500 b) Point differential: +0.063 × 32 (rough conversion) = +2.0 points per game harder c) SOS-adjusted: Could add ~1 win to expected total d) Weight recent by recency factor (e.g., double weight last 4 games)

Exercise 13:

a) Bye: +1.2 × 1.2 (late) = +1.44 b) Rest: 13 days vs 7 days = +0.9 points c) Travel: 2 TZ × 0.2 = +0.4 (but E→W less penalty) d) Primetime: +0.3 e) Total: ~3.0 points schedule advantage for Denver

Exercise 18:

Pseudocode structure:

def schedule_adjustment(home_rest, away_rest, home_bye, away_bye,
                        tz_diff, direction, game_type):
    adj = 0

    # Bye effects
    if home_bye: adj += 1.2 * bye_timing_multiplier(week)
    if away_bye: adj -= 1.2 * bye_timing_multiplier(week)

    # Rest differential
    rest_diff = home_rest - away_rest
    adj += rest_diff * 0.15

    # TNF penalty
    if game_type == 'TNF' and away_rest <= 4:
        adj += 1.5
        if away_rest == 3: adj += 1.5  # Mon→Thu

    # Travel
    adj += tz_diff * 0.2
    if direction == 'W→E': adj += 0.15

    return max(-4.0, min(4.0, adj))

Additional Practice Problems

For extra practice, analyze these scenarios:

Double-bye week: What happens when a team has an extra rest due to opponent bye?
Season-opening games: How do you handle Week 1 when there's no recent game data?
Rescheduled games: How do COVID-era rescheduling or weather postponements affect your model?
Back-to-back road games: Calculate cumulative fatigue for a team playing away games in consecutive weeks
Home stand advantage: Does 3+ consecutive home games provide additional benefit?

These exercises reinforce the key concepts from Chapter 26 on schedule and rest analysis in NFL prediction models.