SportsInsights.com Article

ARTICLE # 4 - MLB (Results for 2003 & 2004 Baseball Seasons)

In previous articles SportsInsights.com studied the results of “fading” (or “going against”) the “Public” in the NBA and NCAA basketball.  We have also seen how “contrarian” approaches work well in other sports – and indeed – even in the financial markets.  In this article, we review Major League Baseball data over the past two seasons.  Once again, betting against the public is profitable.  The information on this site is for entertainment and educational purposes only.  Use of this information in violation of any federal, state, or local laws is prohibited.

ML Baseball Data

Our database for baseball covers almost 4,000 games over the past two seasons.  Our study included all MLB regular season games, as well as playoff games – but excluded spring training games.  We used rules similar to those used in previous articles to clean the data and ensure the integrity of the results. 

• Did not use data if Public % was 0% or 100%
• MLB data from 3/03 – 10/04 (3,998 games)

Baseball is a slightly different animal because it uses a “money line” for betting purposes – as opposed to a “point spread.”  As a result, results are presented in a few different ways.  First, we show the actual number of “units won or lost” over the past two seasons.  As an interesting comparison (and for those who are used to “point spread winning percentages”), we also converted our results to an “adjusted winning percentage.”

Public Betting Percentage

Table 1 shows the results of fading the public at various levels of “Public Betting Percentage.”  Results are quite good at every level of public “disfavor.”  Because of the differences in betting baseball (money line instead of point spread), we show the Number of Games for each “bucket” – as well as the Units Gained or Lost, Average Odds Received, the “Average Units Gained or Lost” Per Bet, and the Adjusted Winning Percentage.

Some interesting points to note:

• The maximum “number of units won” is at the 40% (or lower) threshold.  Note that these figures take into account a reasonable “vig.”
• Many experienced baseball bettors like to take the “underdogs” in baseball.  As usual, the public loves to take the winners (and thus, the favorites).  Fading the public leads to taking the “dogs” and receiving odds of +150 or more.  Note that this approach doesn’t win 50% of its wagers – but wins enough to make it a profitable proposition (given the odds received).
• If a bettor is interested in maximizing their “units won per bet (or game),” they might want to go to the 25% or 20% (and lower) threshold.
• The “Adjusted Winning %” gives us a number similar to winning percentage on “point spread lines” in other sports.  It is good for an “apples to apples comparison” on how “fading the public” works across various sports.  Note that “vig” is factored out so that you want to achieve at least a 52.4% winning percentage (as you do in all point spread lines).

  Table 1:  Public Betting Percentage and MLB

Line Moves and Public Betting Percentage

We studied how a “Line Move” in MLB impacted our results.  Table 2 shows the results for Line Moves – with Public % in the Opposite Direction of the Line Move.  As we have mentioned in previous articles, this approach is a proxy for determining where the “smart money” is going: by studying “Line Moves” in relation to “Public Betting Percentage.”

Using the “line move” in combination with “public betting percentage” reduces the number of games (and units won) – but improves significantly: the winning percentage, and units won per game.

Table 2:  Public Betting Percentage and Line Move (>=10) in Opposite Direction

Disclaimer

We do not guarantee that the trends and biases we’ve found will continue to exist.  It is impossible to predict the future.  Any serious academic research in the field of “market efficiencies” recognizes that inefficiencies may disappear over time.  Once inefficiencies are discovered, it is only a matter of time before the market corrects itself.  We do not guarantee our data is error-free.  However, we’ve tried our best to make sure every score and percentage is correct.