# Prediction of the margin of victory only from team rankings for regular season games in NCAA men's basketball

## TL;DR

This study evaluates how well team rankings alone can predict the margin of victory in NCAA men's basketball regular season games, extending previous models to a broader ranking range and exploring alternative methods.

## Contribution

It demonstrates that simple quadratic models remain effective across a wider ranking spectrum and shows that semi- or non-parametric methods can improve prediction accuracy.

## Key findings

- Quadratic models perform well for rankings up to 351.
- Semi- and non-parametric methods yield better predictions.
- Models are still valid beyond the top 16 rankings.

## Abstract

The main objective of this paper is to investigate the extent to which the margin of victory can be predicted solely by the rankings of the opposing teams in NCAA Division I men's basketball games. Several past studies have modeled this relationship for the games played during the March Madness tournament, and this work aims at verifying if the models advocated in these papers still perform well for regular season games. Indeed, most previous articles have shown that a simple quadratic regression model provides fairly accurate predictions of the margin of victory when team rankings only range from 1 to 16. Does that still hold true when team rankings can go as high as 351? Do the model assumptions hold? Can we find semi- or non-parametric methods that yield even better results (i.e. predicted margins of victory that more closely resemble actual results)? The analyses presented in this paper suggest that the answer is "yes" on all three counts!