When it comes time to fill out your bracket for the 2008 tourney, youíll have access to a mountain of statistics. If youíre so inclined, you could mull over the value of everything from seeding, conference affiliation and coaching experience to pre-tourney momentum, offensive output, margin of victory and much more. In the tourney database Iíve been building since 1990, I track over 40 separate attributes. With so much data available, itís easy for me to lose sight of which statistics really matter in determining the teams to advance in my bracket.


Thatís why I developed PASE, or Performance Against Seed Expectations. As many readers already know, PASE compares the total number of wins that teams with given attributes attain to the number their seeding indicates that they should achieve. PASE is calculated by tallying the positive or negative differences between actual and expected wins at each seed position. The total of these differences is divided by the number of appearances to arrive at an average number of games the teams either over- or underperform per tourney. In short, PASE provides a way to measure the relative impact of team attributes on tourney performance.


While PASE is a useful tool for analyzing the key indicators of tourney advancement, itís only really effective if applied to the right statistics. While Iíve been working for years on ways to become a better ďbracketeer,Ē a group of statistical gurus have been working on methods to get a more accurate reflection of the strengths and weaknesses of basketball teams in actual game play. If youíre not familiar with the work of Ken Pomeroy, you really owe it to yourself to visit and investigate the concept of tempo-free game-play stats.


The philosophy is simple. Ken and other tempo-free pioneers like Dean Oliver and John Gasaway contend that raw numbers like points scored and allowed per game are only meaningful in the context of the number of a times a team possesses the ball or defends against a possession. In other words, the most accurate way to gauge a teamís offensive or defensive ability is to analyze its efficiency in scoring or preventing scores. Consider this: which team is better offensivelyóa UCLA team that has 60 possessions in a game and scores 70 points, or a Kansas team that has 80 possessions and gets 80 points? Sure, the Jayhawks score more points, but they get an average of only one point per possession while the Bruins score an average of 1.16 points.


Tempo-free statisticians have devised basic formulas to calculate four key numbers:

See the full article by becoming a member today!