Thursday, 30 May 2019

Rationale Thinking

Most of my systems have sound logical reasoning behind them, including the Totals system mentioned yesterday for Major League Baseball. 

The system takes advantage of the fact that most punters have preconceived, and fortunately for us, incorrect ideas about what total might represent a good bet.

To use extremes to make the point, a total set at 14 would appear to the average punter as a high number, triggering the instinctive and quite natural response that "the value must be on Unders", while a total set at 5 would prompt the opposite reaction.

My thought process, as was the case with NBA totals, was that in some scenarios, a high total is value for an Overs bet, and likewise a low total offers value on the Unders. 

Note the "some scenarios". A blind backing of Unders below, or Overs above, any number won't work. Those scenarios included various factors such as the rules for each league, and the number of at-bats per game. 

This was the a priori (as philosophers and betting skeptics refer to it) behind this idea.

The important thing is that there was a logical reason why this system should work, and as it has turned out, as least so far, it does. 

Will the market correct? As with other ideas I've shared, it should, but it often takes its time in doing so.

Look at my College Football (Small Road Dogs) 50/50 system (left) which has had a winning record for 18 seasons straight.

It could be luck of course, as skeptics might have it.

Or.... Or it might just be that favourites are over-rated by the average college football bettor. Surely not. Everyone knows home advantage is worth three points. Maybe not always.  

But at what point does even the biggest skeptic become a convert? If 18 years doesn't do it, then probably 25 years wouldn't. I'm skeptical by nature myself, but I'm also open to a logical idea supported by years of evidence.

A Lucky A Day raises the possibility that the Totals System might be the result of data mining. To me, data mining is an exercise that produces systems such as:
Back the Home Favourite in an American League game when the pitcher lost last time out, the visiting team won their last game but gave up two runs or more in the third, the temperature was 73F or hotter, and the game is being played on a Thursday afternoon. 
(Incidentally, the day of the week can be significant, not because the result is impacted, but because the markets change, as has often been noted on betting forums regarding weekend horse racing).

Here's an actual example of a nonsense 'finding':
99 pitches or more, or the price was 162-plus, and they are 0-7 SU. Maybe. 

To me, this kind of thing (I hesitate to call them systems), is the result of data mining, but I'd argue that it's not data mining when there is rationale involved, rationale defined as:
a set of reasons or a logical basis for a course of action or a particular belief.
In this case, I have a theory about where and why totals markets might be inefficient and then see if the results show that to be the case. So far, they tend to do just that, especially if A Lucky A Day's 1 in 10,000 estimate is accurate!

Remember too that we're not looking for wins, but profits. We are looking for inefficiencies in the market. Find value, and the profits will come.   

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