College basketball over-under bets are the combined points scored between both of the teams playing in a selected game. There are also options to bet on how. During the season, college basketball teams averaged about 70 possessions per game. Gonzaga was one of the faster teams, as they averaged 74 possessions. Over/Unders, or totals, are another typical college basketball bet. Betting over/under means deciding if both teams will combine to score more or less than. OUTRIGHT BETTING BDO DARTS LAKESIDE

To adjust for strength of schedule, Pomeroy uses the least squares method. This is also the basic idea behind linear regression, the data science technique most often used to find the correlation between two variables. For a visual primer on regression, click here. This least squares method also drives the team rankings on the Sports Reference sites.

The difference in the rating between two teams gives a prediction for a future game. To perform this calculation, the computer changes the ratings for all teams until the ratings meet a criteria. This criteria is that these ratings minimize the error between the prediction from the ratings and actual game results.

Pomeroy takes it one step further as he considers offense and defense for each college basketball team. Instead of variables, his code changes variables to minimize the error to the efficiency by points per possession in games. Since these variables get solved for simultaneously, the offensive rating for Gonzaga depends on other offensive and defensive ratings.

In his calculations, Pomeroy puts more weight on recent games. After performing these least squares calculation, you get the offensive and defensive rankings on kenpom. These two numbers get combined into his team rankings. Making a prediction With offensive and defensive ratings based on points per possession, we can now make predictions for games. First, consider what the offensive and defensive ratings mean. For example, if Gonzaga has a rating of points per possessions, then they are expected to score points per possessions against an average college basketball defense.

As another example, Michigan State might have a defensive rating of 90 points per possessions. Better defenses have lower ratings. This is the same method I use with yards per play and success rate in football predictions at The Power Rank. Gonzaga is predicted to score points per possessions against Michigan State. If you scale this efficiency to 70 possessions for a game, this implies Gonzaga will score You can do same calculation for the other matchup.

This implies Based on these hypothetical numbers, Gonzaga would be predicted to win by 0. While I have assumed 70 possessions in this game, you could assume a different number, especially if Gonzaga plays faster than average. With this method, there is clear freedom to adjust for pace. Do matchups matter?

During the season, West Virginia was an elite offensive rebounding team. In contrast, Texas was an awful at defensive rebounding, worst in the Big When West Virginia plays Texas, do they have an edge due to this matchup? Can we use this to make a better prediction? Jordan Sperber of Hoop Vision has done excellent work on matchups. Four factors Dean Oliver was a pioneer in basketball analytics. In , he first published his book Basketball on Paper that laid the groundwork for future work in basketball analytics.

In the book, he wondered what factors made an offense great. Shooting is an obvious asset, but what else matters? The most simple measure of shooting is field goal percentage, or field goals made divided by field goal attempts. A better formula for shooting gives the offense more credit for a three point shot. The second factor is offensive rebounding, as the offense keeps a possession alive with an offensive rebound.

Total offensive rebounds is not a good measure though, as this depends on the shooting accuracy of the opponent. Instead, consider the offensive rebounding rate, or the fraction of rebounds the offense gets on that end of the court. The third factors is turnovers. To measure turnovers, consider turnover rate, or turnovers divided by possessions as estimated from the box score. The final factor is getting to the foul line.

To measuring getting to the foul line, one metric is free throw attempts divided by field goal attempts. This definition includes the ability to make free throws in addition to getting to the foul line. This process assigns a weight to each of the four factors. Based on this regression analysis, which of the four factors is the most important? Shooting is the most important of the four factors, not any kind of surprise. Offensive rebounding and turnovers have about the same importance but less than shooting.

The least important factor is getting to the foul line. In , Jordan Sperber wondered whether a team that excelled in one of the four factors would have an advantage over an opponent weak in the opposing factor. To study this, Sperber isolated games in which teams had extremes in rebounding. With both elite and awful units, there are four types of games: an elite offense versus an elite defense an elite offense versus an awful defense an awful offense versus an elite defense an awful offense versus an awful defense.

Sperber isolated games with these matchups and asked how well adjusted offensive and defensive efficiency can make a prediction in each game, as discussed in the previous section. He compared this prediction with the actual efficiency in the game. For example, his data set had games with an elite offensive rebounding team versus an awful defensive rebounding team.

In looking at the efficiency prediction versus what actually game efficiency, the average difference was less than a point per possessions. The prediction based on offensive and defensive efficiency was able to explain the outcome of these games.

Here is the main result from his study: Sperber found the same predictive accuracy in all four types of matchups. He repeated the study on the other three factors and found the same result. The efficiency prediction was equally accurate in each of the four types of matchups. Here is the take home message: team level matchups in the four factors do not help in predicting the outcome of a college basketball game.

Show More Bet on College Basketball Odds Two years removed from the first-ever canceled tournament and one year removed from the first-ever tournament played entirely in one state, college basketball betting returned in November and has been more exciting than ever. James Madison is ineligible for the CAA Tournament and therefore effectively ineligible for the tournament as well. Will Scott Drew and Baylor become the first repeat champion in 15 years and just the eighth in college basketball history?

Both teams have been among the favorites in college basketball national championship odds , but several teams could cut down the nets in New Orleans. And you can bet on every game at the best online sportsbook!

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Bettors wager on the total either being over or under a certain amount. However, that does not mean that this is a bet that you should make on a hunch or without considering the teams involved. The projected number of points is decided after analyzing how many points each team has been scoring and allowing during the season and by considering matchups and recent play. Look for teams that one-way or another have been playing consistently.

If the clubs have met recently or do so annually, study past performances. It also helps if you can determine if the point spread is accurate. As such, gamblers will find lesser competition in the under bets, especially for the lowest total during a day. In the long run, this translates to better gambling odds and improved profitability. The NCAA basketball betting scene livens up with the total bets offered by various bookmakers.

NCAA games tend to be relatively low scoring due to the presence of a vast cross section of college basketball teams, unlike the professional NBA league. College games totals can be accurately projected only by studying the gaming styles and approaches of the two teams. Simply learning the points conceded and the points earned is not very helpful in college basketball games. The entire tournament involves more than 64 different college teams and literally, hundreds of games are played out.

The NCAA basketball season presents plenty of opportunities for bookmakers to win money and place successful bets. Some bookmakers like to extrapolate the total score for the game by analyzing the total points scored by and against the team in previous encounters. There are several online agencies that keep track of past scores of teams.

In case the gambler risks an equal amount of money on over and under bets, he will be assured of making a return no matter what the consequence. While betting on basketball totals, the number can range between a lowly to a massive plus for more professional league games. Bookmakers often like to align the money line totals by 1. Other Popular Basketball Articles:.

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