## 2013 Pac-12 women's basketball preview statistics framework

Jayne Kamin-Oncea-US PRESSWIRE

Each year before conference play begins, I like to take stock of where each team stands statistically so I'm ready for what's ahead. In advance of sharing all those numbers, the following is just a primer for what all those statistics are.

For the purposes of these previews, I'm going to use the following statistics (some of which are readily available around the web, some of which are numbers I just personally like using):

• Four Factors statistics: These are the numbers that describe the bread and butter of basketball; to win games, good teams tend to shoot well, rebound well, and control the ball well. Free throw shooting is also important, but it's not uncommon for very good teams to not get more free throw attempts than their opponent. The "Team Facs" metric is a weighted metric that just adds all of those together to offer a single number to look at, but the individual factors help us understand strengths and weaknesses. Click here for more.
• Strength of schedule: The strength of the opponents a team has played, which is particularly valuable when looking at non-conference rankings. Those can be found for every NCAA Division I program at RealTimeRPI.com.
• Pace: This is an estimate of the number of possessions per game a team plays or how "fast" a team is. There are a few ways to get to this number - for these college numbers, I'm using the one at Sports-Reference.com.
• Points per possession: This is a "bottom line" statistic: does a team score when they have the ball?
• MEV/possession: This is different than PPP: How much value does a team squeeze out of each possession? The difference is subtle conceptually, but very different mathematically: this takes everything a team does, weights it, and measures its value. The best way to think of MEV vs PPP/Team Facs is the old John Wooden line: "Never mistake activity for achievement." Why, one might ask, do we then look at an activity metric? On occasion, that activity can add up to wins. Particularly when we're looking at teams with poor records, it might speak to subtleties that make them better - or closer to being better - than their record suggests. Click here for more on MEV.
• Adjusted synergy: This is a junk stat that I enjoy using to estimate the quality of a team's ball movement. Bear in mind, that it's a descriptive and not at all explanatory metric - a team can win without picking up many assists if they create a lot of points of turnovers or have a dominant one-on-one player. But it's an interesting way to look at a team's style of play. Click here for more.
• Upset wins/losses: In a framework for figuring out the biggest upset of the 2011-12 season last year, I mentioned the Omni Rankings website which has a two-pronged metric for determining what is an upset and what isn't. For reference here, I'll just list the games for each team that have been designated an upset there.

Click here for more about the various statistics we have used around Swish Appeal.

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