Miami vs Dallas Part 2,3,4,5,& 6...

I just read how Dallas hasn't lost in Miami since their playoff defeat there four years ago. They have a lot of painful memories of that loss and still try to stick it to them. And their record against Miami since then has been very, very good. And basketball is a game of motivation and focus.

Dallas simply cares a lot about winning against Miami, to try to ease the pain of that defeat. So I can't help but think that it would have been a good bet to go with Dallas against Miami. And in general any team that gains supremacy over an opponent who handed them a bitter post-season loss, will consistently deliver victories against them. Being the better team, it is a matter of effort and focus. The painful memory will ensure both.

This is a formula that could be applied to the future.

Week #4 Thoughts

LSU seems like a Jenga tower ready to tip over. And no one has done it yet. They almost lost to Washington State. Now they almost lost to Mississippi State. Who will finally knock them off?

Cal was demolished on the road, despite being called out for their road-woes. Terrible coaching.

Michigan has now won two games that could go either way, so I'm glad to see Rich Rodriguez getting a little bit of luck on his side.

#6 Cal and #9 Miami were beaten thoroughly. Shows the value of preseason rankings. And interesting thing to study is to figure out what goes into pre-season rankings and what determines them? Specifically, how does a coach from Purdue figure out if Cal should be ranked 9th or 19th? Or a coach from UCLA determining the relative merit of a Big 10 team versus an SEC team who played no common opponents the last five years?

Its a huge crap shoot. And unfortunately, pre-season rankings actually carry a lot of weight.

I'd also like to study how and why teams with high early season rankings lose, how they lose, and what factors (likely recurring) lead to some teams being over-hyped. As there is no repercussion for ranking a team high that loses, and I'm sure that coaches tend to over-value teams they know and under-value teams they aren't familiar with or that get little to no national media exposure.

Lastly, I'm sure there is a significant amount of "clumping" or simply coaches asking other coaches what they are ranking other teams, and simply doing the same thing. For example, a coach from Navy won't rank a team #5 in the country that someone else has unranked. Or vice versa. So there is less extremes and less desire to have independent views or to "stick ones neck out" and appear wrong and out of touch. Its better to be wrong with everyone else than be right alone. Because when the reverse happens, being wrong alone and everyone else is easily right, you look like an idiot.

This is a great post and a topic for further exploration. The concept of recurring, systematic errors in preseason rankings that are then found to be fallible later in the season, and that certain factors and consistently over-valued. And the basis for this recurring error is there is no punishment for being wrong AND a desire by each coach to have his rankings resemble those of everyone else's.

There are certain unwritten rules of how far a team drops after a close loss, a major loss, and upset, a loss to a higher ranked team, etc. Those rules are followed. I bet that those are pretty predictable, in fact. Another interesting topic. I wonder if I could make a formula to predict a teams rank the following week based on whether they won or lost, at home or on the road, and the margin of victory. Awesome topic.

And lastly, this of course would represent an investment opportunity if certain trends were discovered in the ranking system that were exploitable.

Sports Betting Scandal Update!

I just read the following article on ESPN,  and I will summarize the main points for my lazy readers.

The article is alleging that former Toledo University football and basketball players were recruited into a point-shaving scheme by some local businessmen-turned-crooks.  The amounts bet were interesting and I've listed them below.  

The games involving Toledo

The indictment alleges Ghazi [Gary] Manni and Mitchell Karam used interstate telephone facilities to place bets knowing the games were fixed, including these Toledo basketball games:
• 11/20/05: $42,000 vs. South Carolina
• 11/27/05: $10,000 vs. SMU
• 12/3/05: $10,000 vs. Northern Illinois
• 12/17/05: $44,000 vs. St. Bonaventure
• 12/21/05: $21,000 vs. East Carolina
• 1/4/06: $10,000 vs. Kent State
• 1/7/06: $15,000 vs. Akron
• 1/15/06: $17,000 vs. Bowling Green
• 1/18/06: $21,000 vs. Miami [Ohio]
• 1/24/06: $40,000 vs. Northern Illinois
• 2/1/06: $40,000 vs. Western Michigan
• 2/4/06: $20,500 vs. Central Michigan
• 2/7/06: $20,000 vs. Kent State
• 2/18/06: $30,000 vs. Detroit Mercy
• 11/20/06: $25,000 vs. Va. Commonwealth
• 12/2/06: $21,000 vs. Vanderbilt
• 12/19/06: $21,000 vs. Detroit Mercy

This is a good amount of money.  I'd be very curious to know their winning percentage for that run of games .  The article is interesting as much for what it mentioned as for what it didn't mention.  It didn't mention how many of those bets they won.  But they did bet on roughly 17 games, averaging around $30,000 per game.  If they won 80% of their games, they would have made a profit of roughly $300,000.  Thats a nice profit!

Its too bad the article doesn't go into details of games won or lost.  But I think that if the players are trying to lose a game on purpose then that is definitely possible to win 80% of one's bets.  

Thoughts on the data I collected on pointspreads

Well I've been mulling the data over in my head for a few days, looking for patterns and causes of said patterns.  The Cavaliers went 53-33 against the spread through the first round of the playoffs.  Detroit went only 40%, or 34-52.  Orlando went 51-35 over the season.  The Wizards went 35-51 for the season.  But the Celtics went 44-42, or .51 for the season.  

What can I conclude from this?  A theory of mine is developing for the NBA regular season.  Take a look at the 1) expectations for a team for the season and 2) their effort level.  

That seems to account for most of the variability in spread-covering percentages for each team.  

Essentially, if a team is expected to be very good and they are very good, and they try at the same level of effort as before, they will go roughly fifty percent.  

But if a team exceeds expectations, then when?  Well they are likely to cover more than their share of spreads.  If a team drops below expectations, they will do less.  

The Cavs tried really hard and got a high level of effort from each player.  Thus they covered more spreads.  Orlando also (seemingly) tried hard this season.  The Pistons?  They didn't try hard at all.  And they failed to cover the spreads because they had an established identity as a hard-working team. 

Interesting that these patterns for season-long betting emerge.  Other research points would include how long into the season do winning percentages and records solidify?  I mean how long into the season, if a team has a record of say, .400, will they finish the season with roughly that record?  Ten games?  Twenty?  Or forty?  

And once that record is roughly locked in, do the betting lines reflect the point spread from the start of the seasons's expectations?  Because what matters is how quickly and accurately the lines can reflect changes.

What I've read about NFL or NCAA football, and NBA basketball, indicates that once people know how good a team is they are very good at predicting point spreads and who will win.  So what matters is when their is a change in a teams skill level whoever can identify it fast enough, and accurately, stands to make the most money.  It doesn't matter if they get better or worse, what matters is accurately detecting change.  And being able to disregard statistical noise.  

Further Advice from Warren Buffet

I've spent the last thirty minutes reading articles about Warren Buffet, his investment philosophy, and some quotes from him.

This includes reading his Wikipedia page, and various articles about the man.  

To summarize he believes the main skills in picking a stock correctly are correctly valuing the company (either above or below current appraisals) and being detached from the opinions of others, which will influence your thinking.  

The following six paragraphs are all from the article cited above:

"[It] comes about from having an investment philosophy grounded in the idea that a stock is a piece of a business. If you look at it that way, there's no reason to get excited whether some analyst is recommending it or the company is splitting the shares two-for-one, or whatever. The only way to drive the extraneous thoughts out of your mind is to have a philosophy. And for us that philosophy comes from Benjamin Graham and The Intelligent Investor, especially chapters 8 and 20. It's not very complicated stuff."

"It doesn't make any difference what other people think of a stock. What matters is whether you know enough to evaluate the business," he opined.

You should be able to write down on a yellow sheet of paper, 'I'm buying General Motors at $22, and GM has [566] million shares for a total market value of $13 billion, and GM is worth a lot more than $13 billion because _______________." And if you can't finish that sentence, then you don't buy the stock.

The key is not to be seduced by crazy ideas, but instead just stick to the fundamentals year after year. Academia doesn't get too interested in us -- we're too simple. What would the professors do? A great many of the formulas [they use to analyze securities and markets] are dead wrong. They exist purely to give the intellectual class something to do. We don't do anything just exercise our intellectual proclivity for mathematical formulas.

Instead, if you are a true investor, you should shop for stocks the same way you shop for anything else: Look for sale prices, and never regard falling prices as inherently bad news. Instead, falling prices create the opportunity to buy even more of something that was already worth owning.

In that single sentence Buffett captured the difference between investing and speculating: An investor, like Buffett, wants the price of a stock to fall below the value of its underlying business so he can buy even more and hold for as long as possible.

********

So to summarize, one wants teams to perform poorly, to have their "stock drop" below their true levels. 

Smart man, a lot to learn from him.

Reading a Book about Day Trading

I've been reading a book about day trading and its really gotten me thinking about sports betting as a market, the spread as a "price", etc.  

I also had a very intriguing conversation with my Dad and we happened upon a great idea.  

Essentially my theory (which is not backed up with data yet) is that a team won't cover the point spread for ever.  A team might under-perform a long time if everyone is quitting or they are disorganized (applies more to football).  Now a team in college basketball might win 30 in a row (Memphis 2007-2008) but I can be damn sure they didn't cover the spread thirty games in a row.  

Because the spread relates to expectations instead of skill, the spread will grow and grow (what kind of growth?  interesting question) until it surpasses even the best performance of a good team having its luckiest night.  The Patriots went 16-0 bit didn't go 16-0 against the spread.  

So essentially, a Martingale style system betting against a team to cover the spread could very well make consistent money long term because of the impossibility of a long, long losing streak.  A team might go 30-0 but they won't cover the spread nearly that many times.  And the advantage of the Martingale system is that it doesn't require you to win more than you lose, it merely requires that you win before you run out of money.

Now even ten iterations of the Martingale system (starting on a ten dollar bet ) exceeds $1,000.  That is a pretty steep climb.  But I would love to see what the chances are of a team pulling off a ten game spread-beating run. 

I tried the Martingale system in roulette when I was younger.  Obviously, my results were mixed.  

But the Martingale system applied in a human-expectation system will have a natural counter built in because its humans who make the spread and they will over-expect.  Turning the behavior of bettors against themselves.  

Likewise, with enough statistical data, one could wait for a three or four game covering streak to start betting against that team to cover as a means of decreasing instances bet and decreasing the preceding "tail" of a run.  

Predicting the Winner and the Loser

I just realized that is sports betting, one often tries to determine who will win.  In fact, for as long as I can remember, my Dad and I would always try to guess the winner of a game.

But that is the same as predicting the loser.  Except we never thought of it that way.  If one can figure out what makes teams lose, what makes them collapse, fall apart, and have struggles and internal tension, one can just as easily figure out the winners.  

Its a cognitive bias.  

I've always focused on the winner of game; what one has to do to win and then trying to figure out how to identifiy which team has more of those traits.  

But identifying teams that have collapsed, don't give a shit, aren't trying to win, etc., and doing it faster than everyone else, can lead to major gains and plays.  

I hope OSU beats Michigan State

I really hope Ohio State beats Michigan State this week. It will solidify their position as a top team. This in turn will have them as rated closer to Penn State, which will make the point spread closer.

Which will make it easier for Penn State to cover the point spread against OSU. Which they should do. Easily. Make no mistake: Penn State is the best team in the Big Ten by a big margin. Simply look at the scores they have been putting up. That is what a top team does. And OSU, Michigan, etc., don't have the offense to keep up with them.

Compared to the OU-Texas game, OU put up 35 points on a good Texas team, but once their linebacker when out with an ACL injury they couldn't hold Texas, which scored 45.

But who in the Big Ten will challenge Penn State? No one that I can see. They beat a good Illinois team which has played a very tough schedule.

Anyways my hope is that Ohio State wins to set up an easy pick for Penn State. Don't forget OSU's quarterback was playing highschoolers a year ago.

Cognitive Biases: Thinking Ohio State is a top team despite their narrow wins and pathetic scores.