Quiz: Rushing Analytics

Target: 70% or higher to proceed.

Section 1: Multiple Choice (1 point each)

1. Why is yards per carry (YPC) considered a flawed metric?

  • A) It's too hard to calculate
  • B) It ignores game context and conflates O-line with RB performance
  • C) It only counts completed runs
  • D) NFL teams don't track it
Answer **B)** It ignores game context and conflates O-line with RB performance *Explanation:* YPC doesn't account for down, distance, score, or whether yards came from blocking vs. RB skill.

2. What is the typical EPA/carry for an average NFL rushing play?

  • A) Around +0.05
  • B) Around 0.00
  • C) Around -0.05
  • D) Around +0.15
Answer **C)** Around -0.05 *Explanation:* The average rushing play has negative expected value compared to passing, which averages around +0.05.

3. What does "success rate" measure for rushing attempts?

  • A) Touchdown rate
  • B) Percentage of runs that add positive EPA
  • C) Yards per game
  • D) Catch rate
Answer **B)** Percentage of runs that add positive EPA *Explanation:* Success rate is the percentage of plays with EPA > 0, measuring consistency of positive contributions.

4. Why do winning teams often have more rushing yards?

  • A) Running causes winning
  • B) Winning causes more rushing (clock management in leads)
  • C) Better RBs win more games
  • D) Defenses get tired
Answer **B)** Winning causes more rushing (clock management in leads) *Explanation:* Teams with leads run to kill clock, inflating rushing volume. Correlation isn't causation.

5. What do "yards before contact" (YBC) primarily measure?

  • A) RB speed
  • B) Offensive line and scheme performance
  • C) RB vision
  • D) Defensive weakness
Answer **B)** Offensive line and scheme performance *Explanation:* YBC reflects the yards created by blocking before the runner faces a defender.

6. Why has analytics led to devaluation of the RB position?

  • A) RBs are getting slower
  • B) Rushing is less efficient than passing and RB production is replaceable
  • C) Teams are running less
  • D) The rules changed against rushing
Answer **B)** Rushing is less efficient than passing and RB production is replaceable *Explanation:* Data shows passing is more efficient and the gap between elite and average RBs is smaller than at other positions.

7. What is "stuff rate" in rushing analytics?

  • A) Rate of first downs
  • B) Percentage of runs for 0 or negative yards
  • C) Fumble rate
  • D) Touchdown rate
Answer **B)** Percentage of runs for 0 or negative yards *Explanation:* Stuff rate measures how often the defense completely stops the run for no gain or a loss.

8. In what game situation does rushing become relatively more valuable?

  • A) 3rd and long when trailing
  • B) 1st and 10 in a tie game
  • C) Short yardage and goal line
  • D) Anytime the defense expects pass
Answer **C)** Short yardage and goal line *Explanation:* In short-yardage situations, the lower variance of rushing becomes advantageous.

9. Why is receiving ability particularly valuable for RBs?

  • A) It looks good on highlight reels
  • B) Short passes to RBs often have higher EPA than rushes
  • C) It helps the RB rest between carries
  • D) Receiving yards count double
Answer **B)** Short passes to RBs often have higher EPA than rushes *Explanation:* Passing is more efficient, and RB targets create mismatches against linebackers.

10. What does a high correlation between carries and EPA typically indicate?

  • A) Better backs get more carries
  • B) More carries always help
  • C) Nothing—volume and efficiency are usually negatively correlated
  • D) Teams should run more
Answer **C)** Nothing—volume and efficiency are usually negatively correlated *Explanation:* High-volume backs often have lower efficiency due to regression, fatigue, and predictability.

Section 2: True/False (1 point each)

11. An RB with 0.00 EPA per carry is performing at league average efficiency.

Answer **False** *Explanation:* Because average rushing EPA is negative (~-0.05), an RB with 0.00 EPA/carry is above average.

12. Rushing touchdowns are a reliable measure of RB quality.

Answer **False** *Explanation:* Rushing TDs heavily depend on team success, red zone opportunities, and scheme rather than RB skill.

13. Game script affects rushing statistics.

Answer **True** *Explanation:* Teams run more when leading (lower-value carries) and pass more when trailing.

14. Yards after contact (YAC) is more attributable to the RB than yards before contact.

Answer **True** *Explanation:* YAC reflects what the runner does after engaging defenders, while YBC reflects blocking.

15. Success rate and explosiveness are always positively correlated.

Answer **False** *Explanation:* Some backs are consistent grinders (high success, low explosives); others are boom-bust (explosive but inconsistent).

Section 3: Code Analysis (2 points each)

16. What does this code calculate?

rushes.query("rush_attempt == 1").groupby('rusher_player_name').agg(
    stuff_rate=('yards_gained', lambda x: (x <= 0).mean())
)
Answer The percentage of rushing attempts for each RB that resulted in 0 or fewer yards (stuff rate). This measures how often runners are stopped at or behind the line of scrimmage.

17. What's the issue with this rushing analysis?

rb_yards = rushes.groupby('rusher_player_name')['yards_gained'].sum()
best_rb = rb_yards.idxmax()
print(f"Best RB: {best_rb}")
Answer **Issues:** 1. Total yards doesn't measure efficiency 2. High volume doesn't indicate skill 3. Ignores carries (could be workhorse on bad team) 4. No context (game script, opponents) **Better approach:** 
# Include efficiency metrics
rb_stats = rushes.groupby('rusher_player_name').agg(
    yards=('yards_gained', 'sum'),
    carries=('rush_attempt', 'sum'),
    epa=('epa', 'mean'),
    success=('epa', lambda x: (x > 0).mean())
)

18. What does this code accomplish?

rushes['game_state'] = pd.cut(
    rushes['score_differential'],
    bins=[-100, -7, 7, 100],
    labels=['Behind', 'Close', 'Ahead']
)

context_stats = rushes.groupby(['rusher_player_name', 'game_state']).agg(
    carries=('rush_attempt', 'count'),
    epa=('epa', 'mean')
).unstack()
Answer This code: 1. Creates game state categories (behind by 7+, close game, ahead by 7+) 2. Groups rushing stats by RB and game state 3. Unstacks to create a comparison table 4. Allows analysis of how RBs perform in different game situations This reveals which RBs are efficient in competitive situations vs. garbage time.

Section 4: Short Answer (2 points each)

19. Explain why passing is generally more efficient than rushing.

Sample Answer Passing is more efficient because: 1. **Higher ceiling**: Pass plays can gain 20+ yards more frequently 2. **First down probability**: Passes can convert 3rd-and-long situations 3. **Rule advantages**: Modern rules protect receivers and quarterbacks 4. **Mismatch creation**: Spread formations create favorable matchups 5. **Lower variance penalty**: Incomplete passes (0 yards) are better than stuffed runs (negative yards in some cases) The efficiency gap is approximately 0.10 EPA per play (pass ~+0.05 vs rush ~-0.05).

20. How would you isolate a running back's performance from offensive line performance?

Sample Answer Approaches to isolation: 1. **Yards after contact**: Focus on YAC, which occurs after blocking ends 2. **Same-system comparison**: Compare multiple RBs sharing the same O-line 3. **Scheme control**: Compare performance within similar play types 4. **O-line adjusted metrics**: Control for team-level run blocking grades 5. **Career trajectory**: Track same RB across different teams/lines **Limitations**: Perfect isolation is impossible; there's always some confounding between RB and line performance.

21. What is "garbage time" and why does it matter for rushing evaluation?

Sample Answer **Garbage time** refers to late-game situations where the outcome is essentially decided (e.g., up by 21+ in the 4th quarter). **Why it matters:** 1. Teams run to kill clock, inflating volume stats 2. Defenders are in prevent mode, not trying hard 3. EPA is less meaningful (running out clock has different value) 4. RBs on winning teams accumulate "empty" yards 5. Rushing efficiency appears higher but isn't "real" **Solution**: Filter to competitive situations or adjust for game state when evaluating RBs.

Section 5: Application (3 points each)

22. Design an analysis to determine if an RB is scheme-dependent or truly skilled.

Sample Answer **Analysis Design:** 1. **Multi-RB comparison within team**: - Compare all RBs in same system - If one RB significantly outperforms, suggests individual skill 2. **YAC analysis**: - Calculate yards after contact specifically - High YAC indicates individual ability beyond scheme 3. **Consistency across situations**: - Does RB excel regardless of play type? - Scheme-dependent backs may excel only in specific looks 4. **Career tracking**: - Follow RB across team/scheme changes - Consistent performance suggests skill over scheme 5. **Against stacked boxes**: - Performance when defense is keying on the run - Scheme-dependent backs struggle more **Limitation**: Sample sizes may be small, and confounding factors always exist.

23. A team is deciding between two RB contract options: (A) Proven starter, 250 carries/year, 4.2 YPC, or (B) Cheaper backup, 80 carries/year, 4.8 YPC. How would you analyze this decision?

Sample Answer **Analysis Framework:** 1. **Efficiency vs. Volume**: - Calculate EPA/carry for both - RB B's higher YPC may translate to better EPA 2. **Durability and sample size**: - 80 carries is small sample; could be variance - Can RB B sustain efficiency at 200+ carries? 3. **Receiving contribution**: - Which is better as receiver? - Pass-catching often differentiates value 4. **Situational performance**: - Short yardage, goal line capability - Third-down back potential 5. **Cost-benefit**: - Calculate EPA above replacement for each - Factor in salary difference - Rushing replacement is relatively cheap 6. **Risk assessment**: - Injury history - Age and career carries **Recommendation**: Unless RB A has significant receiving or situational advantages, the cheaper option (B) likely provides better value. The difference between 4.2 and 4.8 YPC may be noise or scheme, but the cost savings are real.

Section 6: Matching (1 point each)

Match the metric with what it primarily measures:

Metric Measures
24a. EPA/carry A. Run blocking quality
24b. YBC B. Running efficiency
24c. Success rate C. Big play ability
24d. Explosive run rate D. Consistency
Answers **24a. B** - EPA/carry: Running efficiency (value added per attempt) **24b. A** - YBC: Run blocking quality (yards before contact) **24c. D** - Success rate: Consistency (% of positive plays) **24d. C** - Explosive run rate: Big play ability (10+ yard runs)

Section 7: Critical Thinking (2 points)

25. An RB leads the league in rushing yards and touchdowns but has negative EPA/carry. How is this possible, and how would you evaluate this player?

Sample Answer **How it's possible:** 1. **High volume, low efficiency**: Many carries can produce yards but below-average per carry 2. **Touchdown opportunities**: Team red zone success ≠ RB skill 3. **Game script**: Lots of garbage time carries (wins accumulate low-value yards) 4. **O-line quality**: Bad blocking leads to low EPA despite RB effort **Evaluation approach:** 1. **Context analysis**: Filter to competitive situations 2. **Opportunity cost**: What would replacement RB produce with same carries? 3. **Receiving ability**: Is there value beyond rushing? 4. **Team contribution**: Does team win because of or despite RB? **Assessment**: Raw volume stats are misleading. This RB may be: - On a good team (inflated TDs) - Getting too many carries (hurting team) - A victim of bad blocking (not his fault) Need EPA, success rate, YAC, and game script context to properly evaluate.

Scoring

Section Points Your Score
Multiple Choice (1-10) 10 ___
True/False (11-15) 5 ___
Code Analysis (16-18) 6 ___
Short Answer (19-21) 6 ___
Application (22-23) 6 ___
Matching (24) 4 ___
Critical Thinking (25) 2 ___
Total 39 ___

Passing Score: 27/39 (70%)