Improved NCAA Basketball Tournament Modeling via Point Spread and Team Strength Information

@article{Carlin1996ImprovedNB,
  title={Improved NCAA Basketball Tournament Modeling via Point Spread and Team Strength Information},
  author={Bradley P. Carlin},
  journal={The American Statistician},
  year={1996},
  volume={50},
  pages={39-43}
}
  • B. Carlin
  • Published 1996
  • Mathematics
  • The American Statistician
Abstract Several models for estimating the probability that a given team in an NCAA basketball tournament emerges as the regional champion were presented by Schwertman, Mc-Cready, and Howard. In this article we improve these probability models by taking advantage of external information concerning the relative strengths of the teams and the point spreads available at the start of the tournament for the first round games. The result is a collection of regional championship probabilities that are… 

Tables from this paper

Can the NCAA basketball tournament seeding be used to predict margin of victory

Abstract Following the announcement by the NCAA of the seeding and placement of men's basketball teams in the regional tournaments there is often much discussion among basketball afficionados of the

Comparing Team Selection and Seeding for the 2011 NCAA Men's Basketball Tournament

The men’s NCAA basketball tournament is a popular sporting event often referred to as “March Madness.” Each year the NCAA committee not only selects but also seeds the tournament teams. Invariably

The NCAA Basketball Tournament Selects Fan Favorites Over Parity

The rights to the annual NCAA men’s basketball tournament are the most valuable asset that the organization possesses. Revenues earned from the event account for about 80% of the organization’s

A logistic regression/Markov chain model for NCAA basketball

TLDR
Over the past 6 years, the combined logistic regression/Markov chain model has been significantly more successful than the other common methods such as tournament seedings, the AP and ESPN/USA Today polls, the RPI, and the Sagarin and Massey ratings.

Identifying and Evaluating Contrarian Strategies for NCAA Tournament Pools

The annual NCAA men’s basketball tournament inspires many individuals to wager money in office and online pools that require entrants to predict the outcome of every game prior to the tournament’s

A new approach to bracket prediction in the NCAA Men’s Basketball Tournament based on a dual-proportion likelihood

Abstract The widespread proliferation of and interest in bracket pools that accompany the National Collegiate Athletic Association Division I Men’s Basketball Tournament have created a need to

March Madness and the Office Pool

TLDR
This work considers the structure of single elimination tournaments, and shows how to efficiently calculate the mean and the variance of the number of correctly predicted wins (or more generally the total points earned in an office pool) for a given slate of predicted winners.

Team assignments and scheduling for the NCAA basketball tournament

TLDR
This paper describes the development of an integer program designed to optimize team assignments in the sense of minimizing the distance travelled by teams to game sites and the corresponding travel costs and demonstrates the usefulness of the model in both operational and strategic business decisions.

SEEDING IN THE NCAA MEN'S BASKETBALL TOURNAMENT: WHEN IS A HIGHER SEED BETTER?

A number of methods have been proposed for predicting game winners in the National Collegiate Athletic Association’s (NCAA) annual men’s college basketball championship tournament. Since 1985, more

A Simple and Effective Method to Predict Seeded Tournament Outcomes

Predicting the outcomes of sporting events has always been an attractive yet elusive endeavor. Much work has been done in previous decades to improve models that depend on specific team strengths,
...

References

SHOWING 1-10 OF 12 REFERENCES

Choice models for predicting divisional winners in major league baseball

TLDR
This work uses a generalized choice model for the probability of a team winning a particular game that allows for different strengths for each team, different home advantages, and strengths varying randomly with time to predict division winners of major league baseball.

On the Probability of Winning a Football Game

Abstract Based on the results of the 1981, 1983, and 1984 National Football League seasons, the distribution of the margin of victory over the point spread (defined as the number of points scored by

More Probability Models for the NCAA Regional Basketball Tournaments

Abstract In this department The American Statistician publishes articles, reviews, and notes of interest to teachers of the first mathematical statistics course and of applied statistics courses. The

Predictions for National Football League Games via Linear-Model Methodology

Abstract Results on mixed linear models were used to develop a procedure for predicting the outcomes of National Football League games. The predictions are based on the differences in score from past

Estimation with Selected Binomial Information or do you Really Believe that Dave Winfield is Batting .471

Abstract Often sports announcers, particularly in baseball, provide the listener with exaggerated information concerning a player's performance. For example, we may be told that Dave Winfield, a

The Cold Facts about the “Hot Hand” in Basketball

You're in a world all your own. It's hard to describe. But the basket seems to be so wide. No matter what you do, you know the ball is going to go in. –Purvis Short, of the NBA's Golden State

Did Shoeless Joe Jackson Throw the 1919 World Series

Abstract Joe Jackson and seven other White Sox were banned from major league baseball for throwing the 1919 World Series. This article examines the validity of Jackson's banishment with respect to

Teaching Bayesian Statistics Using Sampling Methods and MINITAB

TLDR
The use of Rubin's Sampling-Importance-Resampling (SIR) algorithm is illustrated to simulate posterior distributions for three inference problems and the use of MINITAB macros is presented to illustrate the ease of performing this simulation on standard statistical computer programs.