The Kenpom Ranked Method
NCAAB Method Explanation and Tutorial Using Kenpom Ranking
I wanted to continue testing the method until I had some good confidence behind if it could be profitable or not. After 13 days and 39 placed ML wagers, with a betting unit size of 0.5 units (minus one bet) the method has profited 2.66 units. I feel comfortable enough at this point to put my name on the line and share how the method works, variables to include when looking for the pattern, and the impact of how time will change the method. To begin, it is important to understand what Kenpom is and how it can be used.
What is Kenpom?
Kenpom is a college basketball ranking system created by Ken Pomeroy that takes into account multiple statistical factors including offensive and defensive efficiency, tempo, and luck among other factors. The system is used by oddsmakers and pollsters alike to decide rankings and odds of college basketball games, and is used by me every year to create my March Madness bracket. Because Ken has his own system of ranking, it does not correspond directly to NCAAB rankings. This mismatch of information allows us to trust Ken and believe that his rankings are better than others, giving us an edge at some sportsbooks. Kenpom rankings update daily until March Madness begins and include an update time showing how many games this season have been included for statistical analysis. In the past 10 years, Ken has placed the National Champion in his top 3, and 5 out of 10 times placed the champion as number one before the tournament began. I have good faith in Ken and his rankings, which is why I began to search for a pattern among his rankings.
Finding the Method
I wanted to search for a pattern based on the rankings that Ken gave rather than finding some correlation without causation, and naturally I turned first to betting teams money line that had a higher ranking than their opponent. This had a decent success rate, but that was because heavy betting favorites had a high success rate but a low profit margin. The method was very tedious, betting sometimes 70 games a day just to see minimal margins, then when a single loss occurred, margins on up to 10 low profit games all flushed away at once.
This is what led me to betting the spread on sportsbook underdogs if they had a higher Kenpom ranking than their opponent. I found that this method had some success going even or a little better than even in most cases, but I noticed that the bets that were winning weren’t just underdogs covering their spread, but underdogs straight up winning against their lower Kenpom ranked opponents.
Which brings us to the current method, betting the money line of a sportsbook underdog who is higher ranked on Kenpom. This allows for our method to have an even record of wins and losses, but because underdog ML bets almost always give + odds were able to make a profit off of an even day.
Variables to Consider
I have been blindly following the method to see what variables may be affected and what adjustments can be made to make the method more successful. In my analysis, here’s some things to look out for:
Injuries: Seems pretty reasonable, if the underdog team has an injured player(s) then it makes sense their Kenpom ranking would be higher than their opponent if the player is a difference maker. Injuries on the favored team can also lead to line changes, which has not caused a significant change to the method as we are gambling the underdog.
Large stat differences: Teams can be shot up or down the Kenpom rankings based on a single statistic that is measured. For example, (as of today) North Florida has an offensive efficiency ranking of 79th, tempo ranking of 60th, a luck ranking of 40th, and a strength of schedule ranking of 47th. Would you guess this team is ranked on Kenpom at 171st? This is because their defensive efficiency is ranked 305th. I suggest to stay away from matchups where either team has a large margin between their stat rankings either boosting them up or down the rank.
Rank disparity: It’s important to note that rank disparity higher and lower in the rankings can affect the lines and win percentages. It is much more common for two teams ranked in the bottom 300 teams, 50 spots apart to have closer lines and a more even head to head record. Compare this to the current best ranked team in the country Auburn (7-0) losing to the 51st ranked Villanova (5-4). Sure this is a totally possible matchup with totally possible outcomes (though Villanova would never be favored to Auburn here) but if you’re picking which teams to tail that meet the method rather than every team that meets the method, use an eye test. This method can be fantastic at helping you sift through days of 70+ games and finding some line value.
How the Method Will Change
Its currently December 4th upon finalizing this article, and we are only 7-10 games in the season for each team. Ken Pomeroy is an experienced college basketball analyst and ranker, paying close attention to all 300+ teams each season and offseason. It’s very possible Ken’s rankings will begin to coincide with oddsmakers and other pollsters later in the season, as more eyes watch games closer to March Madness. In this case, the method could begin the falter. In it’s current state I am confident in backing the method behind the first month of college basketball, as underdog wins are more frequent and odds have disparity from site to site (you’ll even notice this trend slightly occur in the spreadsheet above). I plan on posting an update to the method and its success come March, until then I will be blindly tailing and tracking my wins and losses to analyze later in the year.
Thank you for reading, I hope that you can use this method to find success in your college basketball bets. Let me know any data you may find and what variables you consider when betting to possibly be mentioned in my next breakdown of the method.
I am also an NBA, College Football, and NFL gambler among other sports. Check out other articles and twice a week writeups at my Substack
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Great article very informative
It's too simplistic. It will never show a decent profit by the end of the year. Not trying to be negative, but I've been betting successfully on basketball, for many years. In order to win, you have to find something that the oddsmakers can't factor into setting their numbers. The vast amount of the public always loses. Just a fact.