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Your Guide to Tempo-Free Statistics


The college basketball season is underway. As is the case with any sport, we need a method of comparing one team to another, but college basketball presents a unique challenge. Because there are so many teams and so many contrasting styles of play, one can't look at things like points per game and say that because Team A scores more than Team B, team A is better offensively. The tempo at which teams play is a huge factor in how many points they score and allow, and there are statistics out there which remove tempo and allow us to analyze a team's play from a neutral perspective.

Perhaps the biggest site around for tempo-free statistics is http://kenpom.com/, commonly referred to as KenPom. KenPom is short for Ken Pomeroy, the man who came up with the site and runs it, so when you see someone's "Pomeroy Ranking" it's coming from that site. Kenpom is a site that is completely tempo-free. You won't see any per-game statistics on it, so don't bother looking. There's an excellent rundown on tempo-free statistics done by Pomeroy here.

Another excellent site is http://statsheet.com/. They carry tempo-free stats, per-game stats, stats for individuals and teams. They also allow you to select and compare players, look at former players stats, and do all sorts of fun stuff. For instance, if you wanted to compare Nate Robinson versus Isaiah Thomas in their freshmen years, you could do it.

So, let's move onto the stats themselves and what they mean.

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Offensive Rating (ORtg): A measure of a team or player's offensive efficiency, ORtg is how many points would be scored in 100 possessions. Or, if you move the decimal point a couple spaces, how many points are scored per possession. The Huskies put up an ORtg of 150 against Portland State, which is phenomenal. For comparison, the 2004/2005 team had an ORtg of 122.1 (4th in the nation), and last year's squad's was 112.1 (40th).

Defensive Rating (DRtg): Just like Offensive Rating, but with defense, it's how many points a team will give up in 100 possessions. Generally, below 100 is good, and below 90 is elite. Last year's Husky team was 8th in the nation at 88.3

Effective Field Goald Percentage (eFG%): Is calculated by the formula (FGM + 0.5*3PM) / FGA. Put simply: this takes into account that 3 pointers are worth more than two pointers. The saying goes "Making a third of your threes is as good as making half of your twos," which is what this stat is all about.

True Shooting Percentage (TS%): Formula: PTS / (2 * (FGA + 0.44 * FTA)). Like eFG%, TS% takes into account 3 pointers but it also incorporates free throws.

Offensive Rebounding Percentage (OR%): The percentage of rebounds available a player or team gathers that are on the offensive end. Formula: OR / (OR + DR). For a player, higher than 10% is good and for a team higher than 35% is good. Jon Brockman was 9th in the nation at 15.6% last season, and the Huskies as a team are always among the national leaders in this category posting national ranks of 3rd, 6th, 2nd, 8th and 4th over the past 5 years. After the first week of play we're sitting at #1 in the nation right now, but it's too early for that number to mean much.

Defensive Rebounding Percentage (DR%): Just like OR%, but with defensive rebounds.

Turnover Percentage (TORate): Formula: TO / Possessions. What percentage of the time a team or player turns the ball over.

Free Throw Rate (FTRate): Formula: FTM / FGA. A measure of a team or player's ability to score points at the free throw line.

Assist Rate (ARate): Formula: A / FGM. How often a team or player assists on the team's baskets.

Block Rate (Blk%): Formula: Blocked Shots / Opponent's 2PA. How often a team or player blocks shots. Omitting threes gives a truer measure because 3 pointers are rarely blocked, and because some teams shoot more threes than others, playing more of them would unjustly lower the %.

Steal Rate (Stl%): Formula: Steals / Defensive Possessions. How often a team or player comes up with steals.

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KenPom is a genius

All his stats are meaningful and a terrific measure of “real” player/team output.

I am going to run an experiment using his rankings, either this year or next. I’ll take his rankings, and starting with a $100 bankroll place $5 bets on 5 random games (every week) on his favorite. He’s proven to be effective, but I’d like to see if that can be applied to betting as well.

Good work, you’ve been a fine addition here cassino!

by B Money on Nov 18, 2009 4:41 PM PST via mobile reply actions  

One of the fun things he added to his site last year

Was score predictions. I imagine after a few more weeks go by and there’s more data, he’ll have those again this year.

by thecassino on Nov 18, 2009 5:05 PM PST up reply actions  

That's what i was intending on using...

I should’t have said rankings…

Also, I think it’s statsheet, but somebody uses the “four factors to winning”, I thinkt it would be fun to put that to the gambling test as well.

by B Money on Nov 18, 2009 5:19 PM PST via mobile up reply actions  

anyone track his predictions vs the actual outcome last year?

be interesting to see exactly how accurate his forcasts were.

by Bamer_ on Nov 19, 2009 1:20 PM PST up reply actions  

Vegas

Bookmakers aren’t trying to predict the score though, they’re trying to come up with a number that will get equal action on both sides of the line. Big difference.

by Bamer_ on Nov 20, 2009 2:16 AM PST up reply actions  

Anthony

You are really doing a great job….thanks for everything you are contributing…I and everyone that is reading really appreciates it.

by John Berkowitz on Nov 18, 2009 9:26 PM PST reply actions  

My head hurts

in a good way. These Statistics are amazing. Thanks for Cassino for all your help.

I feel really good about this years team and with Pondexter playing at a continued level of excellence we have a good shot to be great!

by bigdave967 on Nov 19, 2009 5:32 AM PST reply actions  

Great overview

Pomeroy is kind of like the Bill James of basketball.

by stupidquestions on Nov 20, 2009 7:57 PM PST reply actions  

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