MLB Betting: American League Team Money Report

Combined National and American League Play Against reports through four weeks are now at 16-12 making 13.65 units per five units wagered. Let't try to keep things going with this week's report on the American League.

To see the individual recommendations for last week’s National and American League team reports, check out the American League Team money Report released last Tuesday. 

The tables shown below show last week’s top-5 American League Ranks and the the updated Top-5 through games of June 17, 2012. 

Net Money Won American League Through games June 11, 2012

Net Money Won American League Through games June 17, 2012

Based on this week’s current report, only Baltimore remains in an over extended performance situation. There are several times during the course of the season, where the elite winning teams can perform at unsustainable levels. The weaker teams can go into short winning streaks as well, but get into ‘overbought’ territory far more quickly and become ‘fade plays’ more often than winning teams in these situations. 

This type of analysis is similar to overbought and oversold readings used in technical analyses of the stock market, commodities, and currency trading. Relative Strength measures are the most commonly used statistic in the financial markets and are a solid starting point for identifying money making opportunities. This is akin to what this report is identifying with teams reaching unsustainable (overbought) conditions. 

When looking at a stock chart of Apple Computer that has moving averages of the price action plotted over top the actual price, the distance between the current price levels and the slower moving averages can become large enough to generate overbought signals and oversold signals. The same can be said with MLB teams. Given the 162 game marathon season, it is analogous to having a stock chart with 162 days of price action.

For example, if you were to plot a team’s batting average for each game and then plot a 3-game and 14-game moving average it would clearly show when these extremes in performance occur. Take your favorite and plot the team batting average and a 3-day and 14-day moving average and then add a space below the plotted point when the the team won or lost. I think you will see that when the batting average becomes ‘stretched’ from the moving averages, it sets up fade and play-on opportunities. Then add in ERA, WHIP, and build a large database and you will have the beginnings of the neural network type of simulator.

For this week, I am recommending to fade the Yankees Tuesday and Wednesday against the Braves and then in their three game set against the Mets beginning Friday. Thursday is a day off for the Yankees to travel from Atlanta back to the Bronx.