Why I Can't take picks from someone else- or give my picks away?

I was reading a stock market analysis paper today.  It was about Elliot Wave theory (my current subject of interest) and the writer seemed so asinine.  He was just parroting what he heard in a re-packaged form. 

It got me thinking about the value of original research and the herd mentality, which is a very powerful human instinct.  And I realized that if I searched long enough, I could fine people betting on both sides of any issue.  People predicting opposite outcomes.  And I realized that taking any advice from anyone meant that I was pre-filtering the advice.  

There is simply so much advice out there.  It is impossible to avoid.  And the over-abundance of advice and re-packaged advice and rumors and parrotings means that it is impossible to determine who the researchers are.  Who the people actually making the picks are.  

And even the people making the predictions aren't insulated from other people making picks.  They have reputations, friends, track records, histories, and critics.  It is one gigantic, incestuous loop.  

So much so, with so many reactions and counteractions, that no data I receive is untainted, is unbiased.  When people get more information, it rarely changes their view.  It simply makes them more certain.  They give less weight to contradicting data and more weight to affirmative data.  

We are all bodily creatures, unable to escape our brain, our chemical dependent hardware, swimming in a sea of chemicals and lights and sounds.  There are too many variables to filter out.  

The solution is to simply not take advice from anyone.  All I can do is take as pure of data as I can and never read a sports column or analysis column again.  Unfortunately that will likely never happen.  

So much of the valuable data out there comes in the form of John Hollinger's numbers, and insights that I pick up from reading articles.  Its all so confusing.  

Elliot Wave Theory Part Deuce

The attractiveness of Elliott Wave Analysis is : Three impulse wave forms and six corrective wave forms are conclusive. All we have to do is to identify which wave form is going to unfold in order to predict future market actions. This is a bold statement, needless to say, knowledge of market historical wave patterns and experiences in wave count are of paramount importance. 

I've had musings about the important of lag between bettors knowledge ofa  team and its actual skill.  Wave theory could replace all that.  Instead of analyzing the teams, I simply am analyzing the bettors.  Instead of watching the games, I'm watching the people watching the games.  This means that there is no team.  There is no game.  There is only a market of people watching the game.  This stuff could be truly ground breaking in nature.  

I really think this stuff is dead on and I need to analyze it stat.  This taps into the greatest weakness of the sports betting market that I've bemoaned repeatedly.  Namely, there is no historical data available.  As soon as the game happens the spread disappears and never comes back.  One has to record the spread or lose it forever.  Maybe if I wrote a casino I could get the answers from them.  Who knows?

Fibonacci sequence and Elliot Wave Theory

I just read an interesting article about the Fibonacci sequence and Elliot Wave Theory.  These are some very interesting subjects.  They may pertain to sports betting.

Here is a quote from Wikipedia:  "Elliott argued that because humans are themselves rhythmical, their activities and decisions could be predicted in rhythms, too. Critics argue that the Elliott wave principle is pseudoscientific and contradicts the efficient market hypothesis."

Now I couldn't agree more with Elliot's premise that human beings are rhythmical.  In fact that is basis of a lot of my observations and research so far.  That indicates to me that there may be some useful information in Elliots Wave Principle techniques.  Also, the criticism that it contradicts the efficient market hypothesis is easily discarded when applied to NBA betting.  I don't think anyone else is researching this so no one else takes it into account.  the efficient market hypothesis implies that everyone knows the information available and can take advantage of it.  

I've been reading about fractals in the Black Swan and have a limited knowledge of them.  Essentially, Elliots Wave theory finds graphs of stock market prices to be fractal in nature and similar patterns can be observed on any timescale.  

Applying what I learned in the Black Swan, scoring in the NBA is from mediocristan.  A player may score 1000 points in a season.  That would correspond to roughly 12 points a game for an 82 game season.  However, he will not play in all 82 games, score 1000 points in one night, and score 0 the rest of the season.  

Same applies to all statistics.  Cumulative totals increase fairly linearly.  

Another quote from Wikipedia:

"Elliott Wave analysts (or "Elliotticians") hold that it is not necessary to look at a price chart to judge where a market is in its wave pattern. Each wave has its own "signature" which often reflects the psychology of the moment. Understanding how and why the waves develop is key to the application of the Wave Principle; that understanding includes recognizing the characteristics described below.^[2]"

Interesting.  This material is really right up my alley.  It talks about how psychology affects behavior and motivation is a subset of psychology.  

Where do I go from here?

I need to get serious and rigorous in my hypothesizing and testing.  I have no database.  I have no knowledge of data-searching programs.  I have limited skills.  I have limited knowledge of NBA history and all the data I get is from secondary sources.  I can review blogs, websites, and watch videos all I want.  I have no primary source information.  There are many reasons why I will fail.  

I've studied football (both Pro and College) for several seasons and watched closely this year's NBA season.  I've been following point spreads closely for some time now.  So where do I go from here?  I have ideas that seem to be right.  I'm able (I think) to identify factors after the fact.  I need to make a database.  And I have no idea how to do that.  

Come to think of it, do I even need a statistical database?  The book Black Swan says that with more information I will be more confident in my picks but no less accurate.  Maybe I just need to keep observing and let my brain and its neural network do the work?

Lakers at SacTown

As I write this I this the Lakers are winning 86-72 at Sacramento.  They are only two point favorites on the road.  That seems a little silly to me.  Perhaps oddsmakers are thinking their motivation has wavered and they have lost focus.  

However, two nights ago the Lakers nearly lost to the Clippers after blowing a big lead.  The only thing better for tonight would have been if they'd lost to the Clippers.  Then they would have been very focused and vengeful.  

As it is they will still likely blowout the Kings.  The question is why was the spread so low?  

I think it was because of their near defeat to the Clippers.  But remember the lag factor.  By the time everyone has profiled the Lakers as losing focus, they have switched gears and become focused and wary.  By the time everyone thinks they are focused and playing hard, they will be slipping back into mediocre habits.  And so the pendulum swings, back and forth, back and forth.

The important lesson is that one needs to anticipate.  A close loss to a bad team will spur greater effort the next time a bad team is played.  A dominant win over a bad team will encourage less effort and focus the next time it is played.  There is the back and forth between expectations and effort.  Strong effort yields results and overkill which encourages less effort.  Rarely do players play hard for no reason.  A series of dominant wins will usually provoke less effort from the top team, steadily dropping until a bad loss wakes them up and spurs greater effort.  

Too predictable?

I just read an article on Truehoop, found here, stating the Spurs were all business and getting ready for Oklahoma City.  If you hadn't heard, Manu Ginobili is out for the rest of the season with an ankle stress fracture.  

When a player goes down with injury on a sports team, it focuses everyone else.  They are all aware of how they have to step up and perform.  Media and friends say they have lost the season and can't compete anymore.  But when Manu goes down, there are still talented professional NBA-level players ready to take his place.  Its not that bad!

So it was a surprise to notice that the Spurs were only two point favorites against Oklahoma City tonight.  Oklahoma, the third worst team in the Western Conference!  I mean lets get serious here.  The Spurs lose Ginobili and they are only two point favorites?

Add this to the fact that the Spurs already lost once in OKC this year.  The result is the Spurs won by ten.  There is a pattern here with one supporting factor.   Team loses a key player to a surprise injury and focus and step up their game.  Supporting fact is the Spurs already lost once to Oklahoma and went through that embarassment once.  Fool me once, shame on you.  Fool me twice, ..... don't get fooled again. 

Especially consider that the Spurs were blown out at Cleveland and Tim Duncan had a horrible game.  I don't know how often he has back to back bad games, but he is a proven winner so it is doubtful.  Champions can bounce back from a bad performance.  

Another interesting thing to notice and observe in the coming days is the duration of their overachieving versus the spread.  There is a human limit to over-exertion and human tendencies to relax (as already discussed).  How long will the Spurs over-achieve?  Two games?  Three I'd assume at most before they return to their ways.  

CIA Analyses

I've spent more time reading the CIA book on the Psychology of Intelligence Analysis.  Its basically a how-to on how to dissect complex analytical problems where you have incomplete information and have to make inferences.  

Some of the key concepts translate to sports analysis as well.  There are several different areas of sports betting.  Lets take the NBA as the cornerstone for betting opportunties.  

You can bet on regular season games, who will win the Championship from the start of the season, and bet on playoff series, up to the championship.  

Edit: I never finished this post and will publish as is.  The CIA Intelligence Analysis book is old hat.  

Thoughts on Spurs-Cavs game

The Cavs dominated the whole game today.  From start to finish it was never close and never really out of control.  I read in the game notes that LeBron arrived to the stadium three hours ahead of tip-off to prepare, which is what he does to prepare for big games.  He scored 28 in the first half and 38 overall.  Interestingly this is coming after a close loss to the Wizards (a rivalry game) and a blow-out loss at the Orlando Magic (playoff competitor).  

So the team came out focused, fired-up, etc.  The spread was six points and they won by twenty.  Easily won by twenty.  They are also the best home team in the league at this point.  Games like this are definitely predictable.  

It would be great to get information about if/when LeBron shows up three hours early to games.  What their winning percentage is?

Thoughts on the Final Four

I was watching UNC beat down on Villanova last night and appreciated how strong UNC's defense is.  They had so much size on their perimeter players that they completely clogged the lane and they completely flustered them into forcing up perimenter shots.  And of course, rushed perimeter shots rarely go in.  

It also got me thinking about some of the stats I see used for the pros being translated down to college basketball.  Does anyone measure defensive efficiency and offensive efficiency?  It seems like college basketball, with its diversity of players, fast turnover of players, etc., really can make it difficult to stay on top of like the pros.  

Also, college players only play forty minutes a game and roughly 35 games a season, so thats much fewer minutes that they play and it can muck up the statistical analysis because of a much smaller sample size.  

I should re-read the book on handicapping college basketball.  College basketball could definitely be an area of lucrative investment opportunities.  It would require sharper observation skills, but there is also more opportunity for players to quit if they have less to play for.  

Defensive rotations might be practiced less later in the season, etc., etc., etc. 

Also I heard the announcers discussing how UNC remembered their humiliating Final Four defeat last year and wanted to make sure they started strong in the Final Four.  I think that may have played a role in their focus and seriousness because they were definitely focused.   

Quick Update

Last night Denver hosted the Clippers.  In my Bleacher Report article on the Clippers, I predicted the Clippers would get blown out by the Nuggets.  They did, losing by sixteen points.  Also, the spread was fifteen points, so Denver covered despite a huge spread.  This prediction was made on the basis of the Clippers being a recent opponent of the Nuggets; the Clippers having no motivation for the game; and the Nuggets trying to maintain a high seed.  

Prediction Total:  10-6