Here is a direct link to the ranking table. As with my NFL, NCAAF, and MLB rankings, these update every morning with the latest game results and betting information. My source is Sportsdatabase.com.
Ranking Table Overview
Here is a description of the fields (you can also mouse over the column headings):
- LstWk - The team's ranking as of a week ago, with a corresponding sparkline that shows the day to day movement (mouse over for the actual numbers).
- GPF - Stands for "Generic Points Favored". It is what you would expect the team to be favored by against a league average team at a neutral site.
- oGPF - Stands for "Offensive Generic Points Favored". The component of a team's GPF that is attributable to offense (and pace).
- dGPF - Stands for "Defensive Generic Points Favored". The component of a team's GPF attributable to defense (and pace).
- GOU - Stands for "Generic Over/Under". It is what you would expect the betting over/under to be set at when playing a league average team.
- W-L - Team win-loss record (it is interesting to see where the betting market diverges from a simple win/loss ranking)
Some Initial Observations
- The Lakers - Note the rapid rise in their Generic Over/Under, corresponding to the hiring of Mike D'Antoni, a coach known for fast-paced, high scoring offenses. So far though, the Lakers' overall GPF ranking has not moved much, meaning that the market isn't convinced yet that D'Antoni's style will bring wins as well as scoring.
- The Bobcats - The market is playing "wait and see" with the Bobcats so far. It's going to take more than a 6-5 start to erase the memory of last season's historically bad 7-59 record.
The methodology went through some slight tweaks this year, mainly in how I weight prior games. Recent games are given more weight since I am trying to get the most up-to-date estimate of what the market thinks. The weight I use is as follows:
weight = 1 / (2 + days elapsed)
For example, today's games would be weighted at 1/2, yesterday's at 1/3, etc. The factor of 2 in the denominator was chosen so as to minimize the prediction error of future point spreads (backtested against prior NBA seasons).
Home field advantage is assumed to be worth 3.25 points. Teams playing back to back are assumed to be penalized 1.25 points in the point spread.
The market is assumed to treat each game outcome with 20% credibility. For example, if a team was favored by three points and instead won by 8 points, the revised point spread for a hypothetical rematch would be 4 points ( = 3 points + 0.20*(8-3) ). This revised spread is what is actually fed into my model. I add this adjustment because it improves the prediction error of future point spreads.
Now that the ranking table is up and running, I hope to relaunch The Ticker and Today's Games features soon.