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  • 标题:Using betting market odds to measure the uncertainty of outcome in Major League Baseball.
  • 作者:Paul, Rodney J. ; Weinbach, Andrew P. ; Borghesi, Richard
  • 期刊名称:International Journal of Sport Finance
  • 印刷版ISSN:1558-6235
  • 出版年度:2009
  • 期号:November
  • 语种:English
  • 出版社:Fitness Information Technology Inc.
  • 摘要:Major League Baseball offers an interesting dilemma in terms of competitive balance. Schmidt and Berri (2001) show that the 1990s, using traditional measures of competitive balance based on win percentages, were the most competitive decade in the history of Major League Baseball. As Schmidt and Berri (2001) note, during the same timeframe, fans and the media believed that baseball became much less competitive. This apparent dichotomy begs the question of how the field of economic research on sports could be so different from public perception. If the 1990s were truly the most competitive decade in baseball, why did the fans and media not recognize this?
  • 关键词:Baseball;Baseball (Professional);Professional baseball;Sports associations;Sports betting;Uncertainty

Using betting market odds to measure the uncertainty of outcome in Major League Baseball.


Paul, Rodney J. ; Weinbach, Andrew P. ; Borghesi, Richard 等


Using Betting Market Odds to Measure the Uncertainty of Outcome in Major League Baseball

Major League Baseball offers an interesting dilemma in terms of competitive balance. Schmidt and Berri (2001) show that the 1990s, using traditional measures of competitive balance based on win percentages, were the most competitive decade in the history of Major League Baseball. As Schmidt and Berri (2001) note, during the same timeframe, fans and the media believed that baseball became much less competitive. This apparent dichotomy begs the question of how the field of economic research on sports could be so different from public perception. If the 1990s were truly the most competitive decade in baseball, why did the fans and media not recognize this?

One possible explanation is that economists are more acute observers of sporting events and that fans in general cannot sort out more competitive play from less competitive play. This explanation may be appealing to economists, especially when sitting around at the sports bar, but it does not offer insight into the source of this bias in judgment by fans and the media. Another possible explanation is that the term "competitive balance" means something different to the typical fans and media members who attend and watch countless baseball games. Their version of "competitive balance" may more closely resemble the term "uncertainty of outcome," a familiar term to economists that focuses on the doubt, or lack thereof, in the outcome of a sporting event. The economic definition of "competitive balance," on the other hand, uses win percentages of the teams or other ex-post figures (e.g., championships, division titles) to measure competitive balance within leagues on an annual basis. There are a wide range of studies in the economic literature on competitive balance in baseball and other sports. Excellent discussion on the topic is available in articles by Sanderson and Siegfried (2003) and Fort (2003) in a special issue of the Journal of Sports Economics.

Although the economic definition of competitive balance is quite useful, there are many reasons to consider that uncertainty of outcome measures may be much more useful and important. First, expectations of the uncertainty of outcome are formed ex-ante, when consumer (fan) decisions take place. These decisions include purchasing tickets to the game and watching the game on television. These choices by consumers are ultimately the most important factors to the league, teams, television networks, and advertisers, who are all attempting to maximize profits. Current measures of competitive balance may capture the desires of fans to see close games, but it can only do this after the games have actually been played.

Given the fact that understanding fan preferences would be advantageous before games are played, the question remains if there is a way to measure the uncertainty of outcome before games are actually played. Thankfully, there exists a market that estimates the uncertainty of outcome. This market is the betting market for Major League Baseball. Odds that exist on baseball games serve as a proxy for the uncertainty of outcome of games. The higher the average odds (in absolute value--as bettors must lay more than a dollar to win a dollar), the more certain the outcome of the game appears to be. The closer the odds are to even money propositions, however, the more uncertainty of outcome there is in baseball games. The use of betting lines to estimate the uncertainty of outcome in games is not new, as it was used in attendance studies of baseball (Knowles, Sherong, & Haupert, 1992; Rascher, 1999) and was directly suggested as a measure of uncertainty of outcome for soccer in Peel and Thomas (1988, 1992) and Forrest and Simmons (2002). Betting odds were found to be the superior measure of uncertainty of outcome, although it had little predictive power in forecasting attendance (nor did other uncertainty of outcome measures), in Premier League Football matches in Spain (Buraimo, Forrest, & Simmons, 2006).

Researchers have previously addressed the question of market efficiency in the baseball betting market. Woodland and Woodland (1994) found a reverse favorite-long shot bias, where favorites were overbet. When correcting for the proper specification of a unit bet, however, as performed in Gandar, Zuber, Johnson, and Dare (2002), the reverse favorite-longshot bias was no longer found in general in the baseball market. If the betting market for Major League Baseball cannot reject the null hypothesis of efficient markets, then the odds give a good representation of the prediction of the outcome of a game. Therefore, the average odds would give an excellent measure of the uncertainty of outcome. If this measure of uncertainty of outcome reveals something different about market perceptions of baseball games compared to ex-post measures of competitive balance, it will help to explain the difference between the findings of Schmidt and Berri (2001) and the thoughts generally expressed on competitive balance by the baseball-watching public.

Efficient Markets and the Reverse Favorite-Longshot Bias in Baseball

Before proceeding to use baseball betting odds as a measure of the uncertainty of outcome, it is necessary to test whether the betting odds themselves represent an unbiased and optimal prediction of the outcome of the game. To do this, we test the betting market for Major League Baseball from 1990-2006 compared to the results expected under the efficient markets hypothesis. Data was taken from the Stardust sportsbook as compiled by www.thelogicalapproach.com.

In previous research on baseball betting markets, a reverse of the favorite-longshot bias was found in odds-based wagering markets. The bias was first noted by Woodland and Woodland for Major League Baseball (1994) and the National Hockey League (2001). In both of these leagues, Woodland and Woodland found that favorites were overbet and underdogs were underbet, the opposite result of what was seen in the horse racing studies (for review of the literature, see Sauer, 1998).

Gandar et al. (2002) and Gandar, Zuber, and Johnson (2004) corrected the studies of Woodland and Woodland in baseball and hockey, respectively, for the proper definition of a unit bet on the favorite and the underdog. In baseball (Gandar et al. 2002), the reverse favorite-longshot bias was no longer found to be significant, although in hockey (Gandar et al. 2004) the bias was still found to be significant, although less pronounced. Gandar et al. (2002) and Gandar et al. (2004) also noted that the bias is not strictly along the lines of favorite/longshot but also a bias in terms of whether the favorite is playing at home or on the road. In general, it appears that road favorites are significantly overbet in these markets.

Using the betting simulations test outlined in Woodland and Woodland (1994) and updated for the proper use of a unit bet by Gandar et al. (2002), we test the returns to simple strategies of betting the underdog (for the sample as a whole and for subsets of road underdogs and home underdogs) compared to the results expected under the efficient markets hypothesis. In addition, we use the distinction of slight (underdog odds of less than 1.60) and heavy (underdog odds of greater than or equal to 1.60) underdogs. Each grouping displays the number of observations, returns (assuming a one dollar bet), expected returns (assuming efficient markets), and z-statistics associated with the test that actual returns are equal to expected returns. Results are shown in Table 1.

In the overall results for the Major League Baseball gambling market from 19902006, results are similar to those found in previous seasons by Gandar et al. (2002), as the null hypothesis of efficient markets cannot be rejected for the sample as a whole. Groupings of slight and heavy underdogs in the overall sample also do not reveal rejections of the efficient markets hypothesis. Losses on underdogs are slightly lower than expected, although still negative for each grouping in the sample of all games. (1)

In relation to the home/road distinction noted by Gandar et al. (2002), road underdogs were not found to reject the null of efficient markets. For home underdogs, only heavy home underdogs were found to earn positive profits during this time frame, with a z-statistic that rejects the null hypothesis of efficient markets at the 10% level.

Overall, the odds appear to represent a good forecast of the outcome of baseball games. The efficient markets hypothesis could not be rejected for any of the overall samples from 1990-2006, with only the small subset of games with home underdogs managing to reject the null at a 10% level. Therefore, we will use the odds on baseball games as a measure of the uncertainty of outcome and an ex-ante measure of competitive balance.

The Baseball Betting Market and Uncertainty of Outcome

Given the results of the efficient markets tests in the previous section, where the null of efficient markets could not be rejected for the Major League Baseball gambling market, we will now proceed to use these odds as a measure of the uncertainty of outcome of baseball games. Betting odds are formed in a market, where bettors wager on either team against posted odds by sportsbooks. These bettors are likely to be part of the multitude of fans that follow this sport in North America and the world. Odds on baseball games are publicly available to all sports fans, not only gamblers, through publications such as the USA Today, local newspapers, and various websites on the internet.

Observing the betting odds for baseball games may shed some insight into the findings of Schmidt and Berri (2001) and the related comments of the media and fans. Although Schmidt and Berri found Major League Baseball to be quite competitive during the 1990s, fans and the media thought otherwise. Fans in general perceived baseball as becoming much less competitive during this time frame. What they actually could have been implying, however, is that the level of uncertainty of outcome has lessened during this time frame.

If the uncertainty of outcome of baseball games has changed during the 1990s (and beyond), this will likely be captured in the betting market odds. Games where there are big underdogs have a low level of uncertainty of outcome. Games where the odds are closer to even money imply a greater level of uncertainty of outcome. The use of odds as a measure of uncertainty of outcome has been used before in English Soccer (Peel & Thomas, 1988, 1992; Forrest & Simmons, 2002).

It is important to note that betting odds as a measure of uncertainty of outcome has distinct advantages over measures of competitive balance above and beyond the obvious advantages of being known before the game is played. Although win-loss percentages, championships, and division or conference titles are all formed in a binary manner (a team either wins or loses, wins a title or does not), betting odds offers a measure of the strength of a favorite along a continuous spectrum. A team that is a--400 favorite is much more likely to win a game than a -200 favorite. With competitive balance figures, a win is simply a win. With betting market odds as a measure of uncertainty of outcome, the relative magnitude of the favorite offers insight into the game not available in the typical measures of competitive balance.

For instance, it is possible that two seasons may have similar levels in standard deviation of win percentage and GINI coefficients but could have very different levels of average betting odds. As an extreme hypothetical example, a league where the home team always wins by a large margin may appear to be quite competitive through traditional measures of competitive balance, but the betting market odds as a measure of uncertainty of outcome will show the games are not expected to be close, as average odds on the favorite will be much higher.

[FIGURE 1 OMITTED]

To illustrate how the uncertainty of outcome, as measured by the betting market odds, has changed over the course of our sample, consider Figure 1. This figure plots the average favorite odds (in absolute value terms) for each season from 1990-2006. The figure shows the odds in the American League (AL) and in the National League (NL).

As can be seen in Figure 1, the odds on both AL and NL games steadily increased during the 1990s. Both AL and NL odds rose from the low 130s (for odds on the favorite) to slightly above 150, representing an increase of more than 10% during the decade. These odds spiked even higher in the early 2000s, with AL odds reaching an average of nearly 170 and NL odds reaching a peak of around 150. In the mid-2000s, however, these odds have settled back into the low 150s for the AL and low 140s/high 130s for the NL.

Assuming these odds represent the expectations of bettors and fans concerning the outcome of baseball games, it can be seen that they became increasingly confident in the certainty of outcome of baseball games in terms of the favorite. Competitive balance measures do not bear out these findings, as noted in Schmidt and Berri (2001). For comparison purposes to the previous figure, the standard deviation of win percentage and the GINI coefficient on win percentage are shown for both the AL and the NL in Figure 2.

Although stable early in the 1990s, spikes occurred in the standard deviation of win percentage and the GINI coefficient in the NL and AL at slightly different times in the mid-1990s before immediately settling back into the levels seen in the early 1990s. By the end of the 1990s, however, a major increase in the standard deviation of win percentage and GINI coefficients occurred and continued into the early 2000s. The AL, with the Red Sox and Yankees rivalry as the driving force, saw the biggest increases (meaning less competitive balance), but the NL increased as well. By the mid-2000s, however, the levels of the standard deviation of win percentage and GINI coefficients dropped to the level of the late-1990s in the AL and below the lows of the early 1990s in the NL.

[FIGURE 2 OMITTED]

Although the ex-post measures of competitive balance were reasonably stable in the 1990s and were shown as historic lows in these averages by Schmidt and Berri (2001), the average odds on baseball games steadily increased. As an example, comparing 1997 (before the decrease in competitive balance at the end of the decade noted in Schmidt and Berri (2001)) to 1991 (the within-decade lows in the odds) reveals that the standard deviation of win percentage in the AL (increase of 1.9%) and NL (decrease of 4.6%) changed very little. The change in the average odds, however, increased by a much greater margin in both the AL (increase of 8.2%) and the NL (increase of 12.0%). How could this have happened? Given the findings of market efficiency, odds are unbiased forecasts of outcomes of games; therefore, it shows that baseball games on an individual game level became more certain in terms of the outcome during this time frame, while the actual win-loss percentages at the end of the season revealed little change. If the individual games are expected to have more certain outcomes (stronger favorites), it is not surprising that the public and the media express their concerns that baseball is less competitive than it used to be, even though the aggregated actual win-loss percentages may not have changed by any substantial margin.

The odds, therefore, give a useful measure of how uncertainty of outcome has differed from the ex-post measures of competitive balance in Major League Baseball. The betting market-based odds provide a measure of the uncertainty of outcome, which has increased during this time frame. The uncertainty of outcome measure affects the ex-ante level of competitive balance in the minds of fans and the media, explaining why these entities may not believe that baseball is as competitive as it appeared through traditional measures of competitive balance. Although ex-post measures of competitive balance showed that baseball was extremely competitive during the 1990s, the uncertainty of outcome steadily increased, leading casual observers (e.g., media, fans) to state, with good reason, that baseball had become less competitive.

Conclusions

In an attempt to explain the difference between public and economist perceptions about competitive balance in Major League Baseball, the difference between the ex-ante formed uncertainty of outcome and competitive balance, as measured ex-post by win percentages, was explored. A way to measure the uncertainty of outcome was suggested to be the average favorite odds formed in the betting market for Major League Baseball. The average odds represent the ex-ante expectations of bettors and fans of the outcome of upcoming games. The higher the odds, the more certain fans are of the outcome of the game. The closer the odds to even money propositions, the more uncertainty of outcome there is in games.

The baseball betting market was originally thought to have a reverse favorite-long-shot bias (Woodland & Woodland, 1994). This bias implies that favorites are overbet, which, for the case of uncertainty of outcomes, means that fans believe the league is less competitive than actual game results reveal. This bias was shown to be a byproduct of an improper measuring of a unit bet by Gandar et al. (2002), and a general reverse favorite-longshot bias was shown not to exist, implying more faith in the efficiency of this market. When the efficient markets hypothesis cannot be rejected, the odds can be taken as an optimal and unbiased predictor of the outcome of the game.

For the sample studied in this paper, 1990-2006, which includes seasons immediately after the data set used in the studies of Woodland and Woodland (1994) and Gandar et al. (2002), the reverse favorite-longshot bias was not shown to exist for the sample as a whole, even with the proper accounting of a unit bet. The only subset where the null of efficient markets could be rejected at the 10% level was for the small group of heavy home underdogs. Therefore, because the efficient markets hypothesis could not be rejected, we use the gambling market odds for baseball as a measure of the expected uncertainty of outcome in baseball games.

These findings help to explain the difference between public thoughts of competitive balance (likely "uncertainty of outcome" in their minds) and actual competitive balance as noted by Schmidt and Berri (2001). Schmidt and Berri (2001) showed the 1990s to be the most competitive decade in baseball history but pointed out that media and the fans did not believe this to be the case. In observing the betting market odds in relation to this timeframe, it can be seen that betting market participants believed the league to be less competitive. Odds on the favorite increased in both the American League and the National League during these years.

By measuring the uncertainty of outcome through betting market odds, the remarks of the fans and the media can be reconciled to the findings of competitive balance as found by the ex-post measures using win percentages. Non-economists felt baseball was becoming less competitive, and their beliefs are borne out by the betting market odds, as odds on the favorite steadily increased during the 1990s. Therefore, within the realm of recent history (which is likely most important in the minds of most observers), baseball was becoming "less competitive" as the individual game odds were rising in the direction of the favorites. Even though the competitive balance measures of economists did show that the 1990s were the most competitive in history through ex-post measures, these ex-post measures do not capture all of the information that betting market odds reveal. With expectations of individual game outcomes becoming more certain, as evidenced by the uncertainty of outcome, it is not surprising the media and fans believed competitive balance was a problem in Major League Baseball in the 1990s and beyond.

The betting market odds as a measure of uncertainty of outcome may ultimately be useful to Major League Baseball and to economists who study the league because financial decisions of fans are ex-ante in nature, rather than ex-post. These financial decisions (e.g., including the purchasing of tickets, viewing of televised games, buying of licensed merchandise) are more likely to be based on pre-game fan perception concerning the uncertainty of outcome, rather than ex-post measures of competitive balance.

References

Buraimo, B., Forrest, D., & Simmons, R. (2006). Outcome uncertainty measures: How closely do they predict a close game? In J. Albert & R. Koning (Eds.), Statistical thinking in sports (pp. 167-178). Boca Raton, FL: Chapman & Hall.

Forrest, D., & Simmons, R. (2002). Outcome uncertainty and attendance demand in sport: The case of English soccer. The Statistician, 51, 229-241.

Fort, R. (2003). Thinking (some more) about competitive balance. Journal of Sports Economics, 4(4), 280-283.

Gandar, J., Zuber, R., Johnson, R. S., & Dare, W. (2002). Re-examining the betting market on Major League Baseball games: Is there a reverse favorite-longshot bias? Applied Economics, 34, 1309-1317.

Gandar, J., Zuber, R., & Johnson, R. S. (2004). A reexamination of the efficiency of the betting market on National Hockey League games. Journal of Sports Economics, 5(2), 152-168.

Knowles, G., Sherony, K., and Haupert, M. (1992). The demand for Major League Baseball: A test of the uncertainty of outcome hypothesis. American Economist, 36, 72-80.

Peel, D. A., & Thomas, D. A. (1988). Outcome uncertainty and the demand for football. Scottish Journal of Political Economy, 35, 242-249.

Peel, D. A., & Thomas, D. A. (1992). The demand for football: Some evidence on outcome uncertainty. Empirical Economics, 17, 323-331.

Rascher, D. (1999). A test of the optimal positive production network externality in Major League Baseball. In J. Fizel, E. Gustafson, & L. Hadley (Eds.) Sports economics: Current research (pp. 27-48). Westport, CT: Praeger Publishers.

Sanderson, A. R., & Siegfried, J. J. (2003). Thinking about competitive balance. Journal of Sports Economics, 4(4), 255-279.

Sauer, R. D. (1998). The economics of wagering markets. Journal of Economic Literature, 36(4), 2021-2064.

Schmidt, M. B., & Berri, D. J. (2001). Competitive balance and attendance: The case of Major League Baseball. Journal of Sports Economics, 2(2), 145-167.

Woodland, L. M., & Woodland, B. M. (1994). Market efficiency and the favorite-longshot bias: The baseball betting market. Journal of Finance, 49(1), 269-280.

Woodland, L. M., & Woodland, B. M. (2001). Market efficiency and profitable wagering in the National Hockey League: Can bettors score on longshots? Southern Economic Journal, 67(4), 983-995.

Endnotes

(1) The results for 1990-2006 are similar to those found in the 1978-1989 sample used by Gandar, Zuber, Johnson, and Dare (2002) in that the win percentages of underdogs are slightly higher (although not statistically significant) than the returns implied by efficiency. Given the z-tests are dependent upon sample size, larger samples may still reveal significant results if future baseball results are similar to current and past results.

Rodney J. Paul [1], Andrew P. Weinbach [2], Richard Borghesi [3], and Mark Wilson [1]

[1] St. Bonaventure University

[2] Coastal Carolina University

[3] University of South Florida--Sarasota

Rodney J. Paul is a professor of economics. His research interests include the economics and finance of sports, market efficiency, and time-series macroeconomics.

Andrew P. Weinbach is an assistant professor of economics in the Wall College of Business Administration. His research interests include the determinants of consumer demand for sports and entertainment products and financial markets.

Richard Borghesi is a professor of finance. His research interests include corporate finance, corruption, market efficiency, and prediction markets.

Mark Wilson is an assistant professor of economics. His research interests include sports economics and the economics of crime.
Table 1: Betting Simulations Testing Efficient Markets in the Baseball
Gambling Market 1990-2006

              N      Returns    Expected   Z-Statistic
                                Returns

All Underdogs 1990-2006

All         35974    -0.0096    -0.0187      1.4772
Slight      28611    -0.0102    -0.0189      1.3433
Heavy        7363    -0.0074    -0.0175      0.6322

Road Underdogs 1990-2006

All         25284    -0.0010    -0.0184      1.1303
Slight      19228    -0.0069    -0.0187      1.4566
Heavy        6056    -0.0197    -0.0175      -0.1226

Home Underdogs 1990-2006

All         10690    -0.0087    -0.0194      1.5076
Slight       9383    -0.0168    -0.0196      0.2492
Heavy        1307     0.0496    -0.0173     1.7831 *

Note: * denotes rejection of the null hypothesis of efficient markets
at the 10% level.
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