Paper Draft - Final

  • View
    6

  • Download
    0

Embed Size (px)

DESCRIPTION

NFL Gambling Paper

Transcript

  • Washington University in St. Louis

    Olin Business School

    The NFL Gambling Market:Testing efficiency and the late

    season bias

    Author :Daniel Sear

    Supervisor :Dr. Dirk Nitzsche

    May 21, 2010

  • Abstract

    This paper analyzes the NFL gambling market for inefficiencies. Testing game datafrom 2006 to 2009 we find that betting on late season home underdogs can be prof-itable, representing a market inefficiency. Next we find that, unlike other recentresearch, the weather and climate in which the game is played does not represent amis-pricing. Finally, we develop both a Binary and OLS Base Model regression andfind that the Binary Base Model regression can be utilized out-of-sample to form aprofitable strategy on all games late in the season.

    ii

  • Acknowledgements

    I would like to thank Professor Dirk Nitzsche for his guidance through the con-struction of this paper. Also thanks to Brain Burke of AdvancedNFLStats.com forpointing me in the right direction on some interesting research. Finally, I would liketo thank Professor Richard Borghesi for his helpful clarifications on the finer pointsof his research.

    iii

  • Declaration

    I declare that this dissertation is the result of my own work and includes nothingwhich is the outcome of work done in collaboration. It is not substantially the sameas any which I have submitted for a degree, diploma, or other qualification at anyother university. Additionally, no part of this dissertation has already been, or iscurrently being, submitted for any such degree, diplmoa, or other qualification.

    (Daniel Sear)

    iv

  • Contents

    1 Introduction 71.1 NFL Background Information . . . . . . . . . . . . . . . . . . . . . . 71.2 Betting in the NFL . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81.3 Necessity for New Research . . . . . . . . . . . . . . . . . . . . . . . 10

    2 Literature Review 122.1 OLS Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122.2 Binary Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152.3 Other variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

    3 Analysis 223.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223.2 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233.3 Time variation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

    4 Results 284.1 Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284.2 Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374.3 In-sample predictability . . . . . . . . . . . . . . . . . . . . . . . . . 394.4 Out-of-sample predictability . . . . . . . . . . . . . . . . . . . . . . . 40

    5 Conclusion 44

    Appendices 47

    Bibliography 50

    v

  • List of Tables

    1.1 Illegal betting by sport in the United States . . . . . . . . . . . . . . 8

    3.1 Summary of Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

    4.1 NFL home team summary statistics by week . . . . . . . . . . . . . . 294.2 NFL home underdog summary statistics by week . . . . . . . . . . . 314.3 Persistence of biases in the NFL . . . . . . . . . . . . . . . . . . . . . 324.4 Weather effects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334.5 Nevada football betting . . . . . . . . . . . . . . . . . . . . . . . . . . 354.6 Success rates of simple betting rules in the NFL . . . . . . . . . . . . 364.7 NFL in-sample predictability . . . . . . . . . . . . . . . . . . . . . . . 394.8 NFL out-of-sample predictability using the base binary model . . . . 41

    1 Climate of NFL teams . . . . . . . . . . . . . . . . . . . . . . . . . . 48

    vi

  • Chapter 1

    Introduction

    Gambling has become an integral aspect of modern sports. A motivated person can

    place a bet on virtually anything; take the Super Bowl, for instance. Bets can be

    placed on every aspect of that game from simply the winner or loser to the coin toss

    (heads or tails), even the length of time it takes for the national anthem to be sung

    (an over/under). These bets not only drive interest in the sports on which wagering

    occurs, but they are huge business and attract over 300 billion dollars each year in

    the United States alone (see Table 1.1) and that is only illegal gambling. Due to

    the mass amounts of money that flows through this market each year, an inefficiency

    could result in large profits for a bettor if he can exploit the mis-pricing properly.

    This paper aims to determine if the market for NFL bets displays any biases that

    could be exploited or if it is an efficient market with regard to the variables we test.

    1.1 NFL Background Information

    The National Football League was formed in 1920 and has risen from small beginnings

    to become the highest attended American sport by a wide distance.1(MacCambridge,

    2005) The league consists of 32 teams organized into two conferences each with four

    divisions of four teams. Following a four week preseason, teams play 16 regular season

    games over a 17 week season, allowing one bye week per team per season. The bye

    week generally comes between week 4 and week 10 of the regular season. The regular

    season currently begins the Thursday evening after Labor Day (the first Monday

    in September) and ends the last week of December. Games are played primarily

    on Sunday with a weekly primetime game on Monday (the famous Monday Night

    Football), however as the season progresses weekly games are added on Thursday

    and Saturday. Six teams from each conference make the playoffs which consists of

    four rounds: the Wild Card, Divisional, Conference Championship, and Super Bowl.

    1The average attendance for an NFL game is 67,509.

    Sear 7

  • 1.2. BETTING IN THE NFL CHAPTER 1. INTRODUCTION

    Table 1.1: Illegal betting by sport in the United States

    League/Event Total Wagers ($)

    National Football League 80 100 billionSuper Bowl 6 10 billion

    College Football 60 70 billionCollege Basketball 50 billion

    NCAA Basketball Tournament 6 12 billionNational Basketball Association 35 40 billionMajor League Baseball 30 40 billionHockey, Golf, NASCAR, Boxing, and Other Sports 1 3 billionSoccer Nominal

    Total 268 325 billion

    Notes: This table shows the estimated amount of illegal gambling conducted in theUnited States each year by league or event. The information comes from a studydone by CNBC and does not factor in any legal gambling conducted in casinos orother authorized sports books.

    The Super Bowl falls in the first week of February the following year of a season (so

    the 2009 seasons Super Bowl was played in February 2010).

    The NFL has a hard salary cap and revenue sharing which fosters parity

    between teams.2 It also allows smaller market teams such as the Green Bay Packers to

    be on level footing with big market teams like the New York Giants. The NFLs main

    demographic is males, around the age of 16-49. This is also the main demographic of

    sports bettors which helps to explain the extreme volume of wagering that is centered

    around the NFL.

    1.2 Betting in the NFL

    In standard American football betting (both legal and illegal) a point spread system

    is used. In this system a spread is set for the weekends games early in the week,

    normally Monday. Bets are taken up until kickoff when the betting ends and the

    2A hard cap is one that a team cannot exceed. In contrast, the NBA has a soft cap whichmeans a team must pay a fine for any salary that is over the cap, but they can still have a payrollexceeding the cap. Revenue sharing means that most revenues the league generates are pooledtogether and distributed evenly among the 32 teams. For instance, the NFL signs television rightscontracts and gives the Dallas Cowboys 1/32nd of the money, the Chicago Bears 1/32nd of themoney and so on.

    Sear 8

  • 1.2. BETTING IN THE NFL CHAPTER 1. INTRODUCTION

    closing line is established. An example of a line would be Chicago minus five at

    Minnesota. This would mean that Chicago is expected to beat Minnesota by five

    points. If a bettor believes one team is undervalued compared to their opponent

    they bet on that team with a book maker (bookie). In this case, if Chicago outscores

    Minnesota by more than five points, bets on Chicago win. If Minnesota loses by four

    points or less (including scenarios where they win outright), bets on Minnesota win.

    Finally, if Chicago wins by exactly five points a push is declared and the money is

    simply returned to the bettor.3

    In point spread betting the bookie acts much like a stock exchange specialist.

    The bookie, like the stock exchange specialist, charges a fee for setting up sellers and

    buyers (in this case bettors wagering on both sides of the line). The bookie makes

    money in two ways. First, for each wager a bookie pays out $10 in winnings for

    each bet of $11. This means that if in the previous example a bet was placed on

    Chicago for $11 and Chicago won by seven points the bettor would be given $21 by

    the bookie, not $22; this is known as the vigorish, or vig.4 Second, the bets that

    lose are collected by the bookie and what is not given to other bettors in winnings is

    their profit.

    Like the stock exchange specialist, a bookie would like to avoid ending up in

    a naked position. Therefore, if many bettors are wagering on one side of a bet the

    bookie will adjust the line to encourage betting on the other side. For example, if

    there are many bets placed on Chicago