- Fixed a CRAN comment about the package documentation.

The package title no longer begins with the word “Elo”.

Fixed one URL redirect

Added a reference to the help page and vignette for

`elo.glm()`

.

Breaking changes:

Restricted the version of R to >= 3.6.

Changed the impact of the

`group()`

formula special in`elo.run()`

. It now indicates when to update Elos. (#54)Removed

`elo.run2()`

, to be replaced by passing arguments to`elo.run()`

. A message is issued when the R backend is used.The

`[.elo.k()`

(new) and`[.elo.players.matrix()`

methods now drop any extra classes when`j=`

is specified.Changed a warning to an error in

`final.elos()`

when using`regressed=TRUE`

without regression after the last game.`elo.glm()`

,`elo.markovchain()`

,`elo.winpct()`

,`elo.colley()`

now emit NAs for running predictions on groups that haven’t been seen yet. (#56)

Other changes:

Added

`subset=`

argument to`auc()`

and`favored()`

.Added

`ignore.skipped=FALSE`

argument to`auc()`

,`favored()`

, and`mse()`

running methods.Added attributes to

`fitted.elo.running(..., running=TRUE)`

to indicate the group (i.e., model) from which the prediction arises.Added

`elo.run.multiteam()`

for when matchups consist of multiple teams. (#54)Improved documentation, including expanding from 1 to 3 vignettes

Fixed a bug with the

`as.data.frame()`

method for`elo.run()`

when`players()`

are involved. (#55)Changed how

`tournament`

is created (though the data didn’t actually change).Made some methods more explicit:

`length.elo.k()`

,`is.na.elo.k()`

,`[.elo.k()`

,`is.na.elo.players.matrix()`

Made one fix for R-devel related to subsetting a vector with a classed object.

- Fixed the “Date” in DESCRIPTION.

Added

`elo.colley()`

, with its corresponding helper functions.Allowed

`k()`

to take two arguments, to give differential updates to “team.A” and “team.B”. This has one user-visible effect:`as.data.frame.elo.run()`

now has one more column than it did before, and its column names have changed. (#45)Added

`elo.run2()`

, which allows for custom probabilities and updates, but by default returns the same as`elo.run()`

(except more slowly). (#47)Added a

`pkgdown`

site: https://eheinzen.github.io/elo/

Added the

`running=TRUE`

option to`elo.glm()`

. This gives an object of class`"elo.running"`

, with corresponding methods for`summary()`

,`fitted()`

,`predict()`

,`mse()`

,`auc()`

, and`favored()`

.Added

`weights=`

to`elo.glm()`

.Added support for

`adjust()`

in`elo.glm()`

to include adjustments in the logistic regression.Added a new inline function

`neutral()`

, to denote neutral field in`elo.glm()`

and`elo.markovchain()`

.Removed the

`rm.ties=`

argument from`elo.glm()`

. Ties will have to be removed instead with`subset=`

or before running the function altogether.Added

`elo.markovchain()`

, with corresponding methods for`summary()`

,`fitted()`

,`predict()`

,`mse()`

,`auc()`

, and`favored()`

. This also has the`running=TRUE`

option.Added

`elo.winpct()`

, with corresponding methods for`summary()`

,`fitted()`

,`predict()`

,`mse()`

,`auc()`

, and`favored()`

. This also has the`running=TRUE`

option.Added a function to denote margin of victory, for continuous modeling in

`elo.glm()`

,`elo.markovchain()`

, and`elo.winpct()`

:`mov()`

.

Added

`auc.elo.glm()`

. (#37)Made

`favored()`

S3 and added`favored.elo.glm()`

. (#38)Made

`mse()`

S3 and added`mse.elo.glm()`

. (#43)Added

`summary.elo.glm()`

.Added

`predict.elo.glm()`

.Added

`brier()`

as a synonym for`mse()`

.Added

`rank.teams()`

.

Fixed a bug with adding NAs back in to fitted values and residuals with

`na.exclude()`

in`elo.glm()`

and`elo.run()`

. (#39, #42)Fixed a bug with

`adjust()`

variables not getting subsetted correctly with`na.action`

in`model.frame()`

. (#40)Added

`is.na.elo.adjust()`

to test for NAs in the adjustment vector. (#41)

Widened the version dependency to R 3.3.0.

Allowed

`players()`

matrices in`elo.run()`

to find Elos of individual players playing at the same time.Added

`elo.glm()`

, a simple function to run logistic regressions on Elo setups.Fixed a bug in the

`favored()`

function (used in`summary.elo.run()`

). (#29)Exported and revamped the class structure of the specials allowed in formulas. (#30)

Allowed access to

`elo.model.frame()`

even when the package isn’t loaded. (#34)Allowed regression to different values for each team. (#35)

Fixed a bug with initial Elos and deep copying in C++. (#25)

Added an argument to

`regress()`

allowing users to stop regressing teams which have stopped playing. (#26)

This version is not backwards compatible!

Changed the signatures of

`elo.calc()`

and`elo.update()`

to match formula interface.Changed

`elo.calc()`

,`elo.update()`

, and`elo.prob()`

to S3 generics, and implemented formula methods. The default methods now include options to adjust Elos. (#3)`elo.run()`

:`elo.run()`

no longer accepts numeric values for`team.A`

.`elo.run()`

now accepts special functions`group()`

and`regress()`

. If the latter is used, the class of the returned object becomes`"elo.run.regressed"`

. (#11, #12, #19, #22)The

`$elos`

component of`"elo.run"`

objects has been completely reworked, and now uses 1-based indexing. Because of this, the`print.elo.run()`

method also had to be fixed. (#16)

Renamed

`last()`

to`final.elos()`

(#9).Changed

`tournament`

dataset.

The

`elo`

package now imports`pROC::auc()`

.`elo.prob()`

now accepts vectors of team names (like`elo.run()`

) as input. (#6)Documentation and the vignette have been updated.

Implemented

`elo.model.frame()`

. The output is a`data.frame`

with appropriately named columns.Implemented

`predict.elo.run()`

and`predict.elo.run.regressed()`

. (#2, #19)Added

`is.score()`

to test for “score-ness”.Implemented

`summary.elo.run()`

, along with helpers to calculate AUC and MSE (`auc()`

and`mse()`

). (#15)

- Fixed a spelling error in DESCRIPTION.

Made the title more succinct.

Elaborated the description of the package.

Tweak the internal

`"elo.run"`

object.Tweaked the README and vignette.

Submit first version of

`elo`

to CRAN.Issues and code can be found on GitHub: https://github.com/eheinzen/elo/