Chapter 39 Quiz: The Sports Betting Industry

Instructions: Answer all 25 questions. This quiz is worth 100 points. You have 60 minutes. A calculator is permitted; no notes or internet access. For multiple choice, select the single best answer.

Section 1: Multiple Choice (10 questions, 3 points each = 30 points)

Question 1. Gross Gaming Revenue (GGR) is defined as:

(A) Total wagers received by the sportsbook

(B) Total wagers received minus total payouts to winners

(C) Total wagers received minus operating costs

(D) Net profit after all expenses including taxes

Question 2. Which bet type typically carries the highest hold percentage for the sportsbook?

(A) Straight bets on the point spread at -110

(B) Moneyline bets on NFL games

(C) Same-game parlays (SGPs)

(D) Player prop bets

Question 3. A white-label sportsbook operator:

(A) Builds all technology in-house and licenses it to other operators

(B) Uses a B2B provider's platform branded as its own, typically paying 20--40% of revenue

(C) Operates exclusively in unregulated markets without a license

(D) Focuses on providing data feeds to other sportsbooks

Question 4. During the US sports betting expansion phase (2019--2023), Customer Acquisition Costs (CAC) for major operators ranged from:

(A) $50 to $100 per new depositing customer

(B) $100 to $200 per new depositing customer

(C) $300 to $1,000+ per new depositing customer

(D) $2,000 to $5,000 per new depositing customer

Question 5. In the context of sportsbook risk management, a "balanced book" refers to a situation where:

(A) The sportsbook has equal handle (total wagers) on both sides of a market

(B) The sportsbook has roughly equal liability on all outcomes, guaranteeing a profit equal to the overround

(C) The sportsbook offers the same odds as all competitors

(D) The sportsbook's total payout potential equals its total handle

Question 6. Which of the following is the primary function of geolocation compliance technology in US sports betting?

(A) Preventing underage users from creating accounts

(B) Verifying that bettors are physically located within a state where the operator is licensed

(C) Tracking bettor behavior for responsible gambling purposes

(D) Preventing multiple accounts from the same household

Question 7. The Value at Risk (VaR) measure used by sportsbook risk teams is borrowed from:

(A) Sports analytics and sabermetrics

(B) Insurance and actuarial science

(C) Financial portfolio risk management

(D) Quality control and manufacturing

Question 8. A sportsbook trader notices that a known sharp bettor has placed a $10,000 bet on Team A at -3. The trader should:

(A) Immediately void the bet because sharp bettors are not allowed

(B) Consider the sharp action as informational and potentially move the line toward -3.5 or -4

(C) Ignore the bet because sharp bettors represent a small fraction of handle

(D) Match the bet by placing $10,000 on Team B at another sportsbook

Question 9. KYC (Know Your Customer) requirements in sports betting include all of the following EXCEPT:

(A) Verifying the customer's full legal name and date of birth

(B) Screening against government sanctions lists and PEP databases

(C) Requiring customers to demonstrate profitability before placing bets

(D) Government-issued ID verification using automated document scanning

Question 10. The trend among large US sportsbook operators regarding their technology stack is:

(A) Moving from proprietary to B2B platforms to reduce costs

(B) Investing in building proprietary in-house technology for greater control and differentiation

(C) Outsourcing all technology to offshore development teams

(D) Using open-source betting platforms to minimize licensing costs

Section 2: True/False (5 questions, 3 points each = 15 points)

Write "True" or "False." Full credit requires correct identification only.

Question 11. True or False: The majority of betting markets at a modern sportsbook are priced algorithmically, with human traders focused primarily on major markets and exception handling.

Question 12. True or False: A sportsbook with a perfectly balanced book makes a profit equal to the total handle multiplied by the hold percentage, regardless of the event outcome.

Question 13. True or False: Anti-Money Laundering (AML) monitoring in sports betting only requires checking customer identities at account creation.

Question 14. True or False: FanDuel and DraftKings together account for approximately 60--70% of the US sports betting market.

Question 15. True or False: A sportsbook's bet placement system must validate and confirm or reject a bet within approximately 2 seconds to meet industry standards.

Section 3: Fill in the Blank (3 questions, 4 points each = 12 points)

Question 16. The formula for hold percentage is: Hold % = __________ / Handle x 100.

Question 17. The process by which a sportsbook verifies that a bettor is physically located within a licensed jurisdiction at the time of each bet is called __________ compliance.

Question 18. The ratio of Customer Lifetime Value to Customer Acquisition Cost, ideally greater than __________, is the key metric for determining whether a sportsbook's customer economics are sustainably profitable.

Section 4: Short Answer (3 questions, 5 points each = 15 points)

Answer each question in 3-5 sentences.

Question 19. Explain why sportsbooks aggressively market parlays and same-game parlays to recreational bettors, despite these products being worse for the bettor than straight bets.

Question 20. Describe the concept of "correlated exposure" in sportsbook risk management and explain why it is dangerous.

Question 21. Explain why understanding sportsbook economics gives a bettor a strategic advantage, using at least two specific examples from Chapter 39.

Section 5: Code Analysis (2 questions, 6 points each = 12 points)

Question 22. Examine the following code that calculates sportsbook hold percentage:

def calculate_hold(odds_side_a: int, odds_side_b: int) -> float:
    """Calculate hold percentage from American odds."""
    if odds_side_a > 0:
        implied_a = 100 / (odds_side_a + 100)
    else:
        implied_a = odds_side_a / (odds_side_a - 100)

    if odds_side_b > 0:
        implied_b = 100 / (odds_side_b + 100)
    else:
        implied_b = odds_side_b / (odds_side_b - 100)

    hold = (implied_a + implied_b - 1) * 100
    return hold

(a) This code contains a bug in the negative odds implied probability calculation. Identify the error and explain why it produces incorrect results.

(b) Write the corrected version of the function.

def calculate_hold(odds_side_a: int, odds_side_b: int) -> float:
    """Calculate hold percentage from American odds."""
    if odds_side_a > 0:
        implied_a = 100 / (odds_side_a + 100)
    else:
        implied_a = abs(odds_side_a) / (abs(odds_side_a) + 100)

    if odds_side_b > 0:
        implied_b = 100 / (odds_side_b + 100)
    else:
        implied_b = abs(odds_side_b) / (abs(odds_side_b) + 100)

    total_implied = implied_a + implied_b
    overround = total_implied - 1.0
    hold_pct = (overround / total_implied) * 100
    return hold_pct

Question 23. Examine the following code that computes Customer Lifetime Value:

import numpy as np

def compute_ltv(
    monthly_ggr: float,
    retention_rate: float,
    discount_rate: float,
    months: int,
) -> float:
    """Compute customer lifetime value over a given horizon."""
    ltv = 0.0
    for t in range(months):
        ggr_t = monthly_ggr * (retention_rate ** t)
        discount_factor = (1 + discount_rate) ** t
        ltv += ggr_t / discount_factor
    return ltv

(a) Identify a problem with how the first month is handled. Does t = 0 correctly represent the first month of the customer relationship?

(b) If retention_rate = 0.90, what is the effective retention probability in month 1 (t=0)? Is this the intended behavior?

(c) Write a corrected version that starts from t=1 and properly handles the first month.

def compute_ltv(
    monthly_ggr: float,
    retention_rate: float,
    discount_rate: float,
    months: int,
) -> float:
    """Compute customer lifetime value over a given horizon.

    Starts from t=1, where retention_rate^t represents the probability
    the customer is still active in month t.
    """
    ltv = 0.0
    for t in range(1, months + 1):
        survival_prob = retention_rate ** t
        discount_factor = (1 + discount_rate) ** t
        ltv += (monthly_ggr * survival_prob) / discount_factor
    return ltv

Section 6: Applied Problems (2 questions, 8 points each = 16 points)

Question 24. A sportsbook offers the following odds on Super Bowl futures (market as of Week 1):

Total handle: $10,000,000

(a) (2 points) If Kansas City wins the Super Bowl, calculate the sportsbook's net profit or loss (handle collected minus payouts).

(b) (2 points) If "another team" (from the combined bucket) wins at average odds of +2500, and $180,000 was bet on that specific winner, calculate the net profit or loss.

(c) (2 points) Calculate the implied probability of each listed team based on the odds offered. What is the total market percentage?

(d) (2 points) Explain why the total market percentage for a futures market is typically much higher (15--30%+ overround) than for a standard two-outcome market (4--5% overround).

Question 25. You are evaluating a career opportunity at a mid-size US sportsbook. They offer two positions:

Position A: Trader (NFL) - Base salary: $95,000 - Annual bonus target: 15% of base - Career progression: Senior Trader in 3 years, Head of Trading in 6--8 years - Required skills: Deep NFL knowledge, statistical literacy, fast decision-making under pressure

Position B: Data Scientist (Pricing Models) - Base salary: $130,000 - Annual bonus target: 10% of base - Career progression: Senior DS in 2--3 years, Lead in 4--5 years - Required skills: Python, ML frameworks, statistics, SQL, some domain knowledge

(a) (2 points) Calculate the total expected first-year compensation for each position (base + bonus target).

(b) (2 points) Using the salary ranges from Section 39.4, project the expected compensation for each position after 5 years (assuming you are at the Senior level).

(c) (2 points) Based on the career paths described in Chapter 39, which position is likely to have a higher compensation ceiling at the 10-year mark? Justify your answer.

(d) (2 points) Beyond compensation, identify two non-salary factors that should influence this decision, and explain how they differ between the roles.

Scoring Summary

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