NFL2010

A dataframe containing all match results with 5 columns

datasets

We utilize the Bradley-Terry Model to estimate the abilities of teams using paired comparison data. For dynamic approximation of current rankings, we employ the Exponential Decayed Log-likelihood function, and we also apply the Lasso penalty for variance reduction and grouping. The main algorithm applies the Augmented Lagrangian Method described by Masarotto and Varin (2012) <doi:10.1214/12-AOAS581>.

Yunpeng Zhou

BTdecayLasso

Bradley-Terry Model with Exponential Time Decayed Log-Likelihood
and Adaptive Lasso

Jinfeng Xu

NFL2010 function

A dataframe containing all match results with 5 columns<dl>
<dt>home.team</dt>
<dd>Team who plays at home</dd><dt>away.team</dt>
<dd>Team who plays away</dd><dt>home.win</dt>
<dd>Take "1" if home team wins</dd><dt>away.win</dt>
<dd>Take "1" if away team wins</dd><dt>date</dt>
<dd>Number of days until now</dd>
</dl>

Format

The 2010 NFL Regular Season — NFL2010

A dataframe containing all match results with 5 columns<dl>
<dt>home.team</dt>
<dd>Team who plays at home</dd>

<dt>away.team</dt>
<dd>Team who plays away</dd>

<dt>home.win</dt>
<dd>Take "1" if home team wins</dd>

<dt>away.win</dt>
<dd>Take "1" if away team wins</dd>

<dt>date</dt>
<dd>Number of days until now</dd>


</dl>

NFL2010: The 2010 NFL Regular Season

Description

Usage

Arguments

Format