Warren Buffet

I continue to be fascinated by Warren Buffet and all he has accomplished.  He lives in Omaha, NE and has consistently outperformed the market.  Efficient market hypothesis claims that this should be impossible.

Yet he has done it.  Despite living away from New York, using just simple logic and trusting to his own opinions, he has succeeded.  And the one professional sports bettor I have read about, Haralobos Voulgaris, has done the same. 

They both isolated themselves from other people and trusted their own decisions and instincts.  They refined their skills and methods until they were able to consistently beat the average.

This next season of basketball I can do that for the NBA.  It is time for me to get an account at an online sports betting place and start placing bets and continuing to work on my theories.  I also need to get more formal and structured in general but I've been having trouble focusing lately.   

One theory of mine would be to track media-exposure to certain teams and correlate that to a rising or lowering pointspread.  

Another would be to create power-rankings based on the point spread for the NBA, and look then for differences in the spread.  Essentially, using past point-spreads to predict future point spreads.  And where there is a discrepancy, searching for the reason.  

Thats a very interesting concept.  

Patterns in a playoff series in the NBA

I really am convinced that there are patterns in an NBA playoff series.  That who wins which game, and how easily, can give you a lot of data as to how the series will go and who will ultimately win.  \

Unfortunately, I have no data.  I also think that I could write good articles on BR using literary teachers and stuff as examples.  Again, no time.  How the hell can I be unemployed and have no time?  I don't know.  

General Research Goals

My preliminary investigation for the Martingale Expectation system didn't reveal much good data.  Although it is still a small sample size (only the Eastern Conference in the 2008-2009 season) I already have seen streaks of length 9, 10, 11.  

Here is a graph of 1 game streaks.  The data is arranged with the team with the highest record on the left (the Cavaliers) and the worst record on the right (the Wizards).  This is the only interesting graph I've produced so far.  

Writing and Research Notes

I've crossed the 4,000 article reads on Bleacher Report and set a personal record with over 1,000 reads on a single article in Bleacher Report.  I've written nine articles overall.  

Also I'm almost at 100 comments received.  My most popular article was about how the Cavaliers wouldn't win the title and what a debacle it was!  So many people wrote negative things about it.  But it was good to read them and learn about how to write a more informative article.  I was a bit rushed because I wanted to go to sleep when I wrote it.  

I also think that no amount of data or theories can really change the minds of most people, especially ardent fans.  I'm not a big Cavs basher or anything or an ardent Lakers supporter, although I do follow both teams.  I just don't think that Cavs are that good this year, but I also haven't watched many of their games.  So who knows?

Also my data research is going well.  I've been analyzing point spreads and looking for trends.  And I've found a few but nothing spectacular.  

Cognitive Bias potentially discovered

I was thinking about the concept of upsets.  Of teams being either better or worse than their record.  Essentially, teams taking days off and giving up a game.  

As far as I know only really good or really bad teams take games off.  Everyone else is scrabbling for everything they can.

But I've never studied the playoffs and seeding to see how many lower-seed upsetting higher-seed situations there are.  The NBA is uniquely suited among the major sports to see how match-ups effect playoff results because of the linearity of scoring, and the seven game series format.  This allows for a LOT of basketball to be played between two teams in an effort to sort out who is the best.  

One of the problems with analyzing it is the seeding.  The NBA uses a 1 vs 8, 2 vs 7, 3vs 6, and 4 vs 5 seeding.  An alternative seeding could be 1 vs 2, 3 vs 4, 5 vs 6, and 7 vs 8 format.  This would let the 1 and 2 seeds duke it out right away, without risk of players getting injured while getting the scrubs out of the way.  The winner would likely face a moderate test in the 3 vs 4 winner, and then celebrate the title early as they beat the winner of the 5 vs 6 vs 7 vs 8 scrum.  

The last series would be akin to a victory lap.  

If we used that seeding, we'd have lots of instances of teams with very close records playing seven games series and we'd see what sort of strength there is to a W-L record, i.e. how accurately it predicts the outcome.  

Just a random thought I had about seeding.  

Also, when I research seeding upsets, check to see the expected wins and losses because of the disparity in homecourt advantage for the higher seeded team.  What I mean is that if two identical teams played, and one had home court advantage in a seven game series in the current format, what percentage of the time would they win.  And what percentage of the time does that actually happen.  

Initial Pac-10 research, potential Bias discovered,

Before I forget, the bias that I thought up today is thus: a college football team that plays a majority of its early-schedule games at home will suffer from Home Field Bias.  Essentially, this means that its stats will be inflated because it will have a disproportionate amount of games played at home.  Homefield advantage has been proven to pump up scoring, improve defense, and generally make the team look better than it actually will when it travels.

Now, on to the research results.  I looked at each team in the Pac ten and their points scored in away games and at home.  The results were not surprising, but still important.

For the season

Home team: 2589 points.   Away Team: 2245 points.

A difference of 344 points spread out over 45 games.  That makes it 7.64 points per game!  That is over one touchdown difference per game that you get for playing at home.  In the pros it is a mere three points.  

I also read in Stanford Wong's book Sharp Sports Betting that home field advantage decreases between division rivals.  It would also be interesting to look at inter-conference games.  Perhaps if I picked another conference, say the Mountain West Conference, and also compared the inter-conference games between the two, to look at home field advantage in another conference and also the difference in inter-conference games compared to in-conference games.  

Also, if the implications of this research are correct, then the younger the team, the bigger the discrepancy between homefield advantage and away disadvantage.  Also, my data may be skewed because of certain "neutral" games that are technically listed as home/away, like USC/UCLA.  These rivalry games may have stadiums that are split.  

Possibly maximized when a young team is a road favorite over a home team with more experienced players.