diff --git a/.Rbuildignore b/.Rbuildignore
index cace7fd..448bf13 100755
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -18,3 +18,4 @@ TODO
 \.xcf
 ^docs$
 ^\.github$
+.lintr$
diff --git a/.lintr b/.lintr
index 6525b6a..54ccdd4 100644
--- a/.lintr
+++ b/.lintr
@@ -1,6 +1,4 @@
 linters: linters_with_defaults(
     line_length_linter(100L)
   )
-exclusions: list(
-  "data-raw"
-)
+exclusions: list("data-raw")
diff --git a/DESCRIPTION b/DESCRIPTION
index 2933001..196efab 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -35,6 +35,7 @@ Language: en-US
 URL: https://github.com/gogonzo/sport
 LazyData: true
 RoxygenNote: 7.2.3
+Roxygen: list(markdown = TRUE)
 Suggests: 
   dplyr,
   knitr, 
diff --git a/R/data.R b/R/data.R
index 60acedd..2c100a4 100755
--- a/R/data.R
+++ b/R/data.R
@@ -1,21 +1,21 @@
 #' Heat results of Speedway Grand-Prix
 #'
 #' Actual dataset containing heats results of all Speedway Grand-Prix turnaments
-#' \code{gpheats}.
+#' `gpheats`.
 #'
 #' @format A data frame with >19000 rows and 11 variables:
 #' \describe{
-#'   \item{id}{event identifier}
-#'   \item{season}{year of Grand-Prix, 1995-now}
-#'   \item{date}{date of turnament}
-#'   \item{round}{round in season}
-#'   \item{name}{Turnament name}
-#'   \item{heat}{heat number, 1-23}
-#'   \item{field}{number of gate, 1-4}
-#'   \item{rider}{rider name, string}
-#'   \item{points}{paints gained, integer}
-#'   \item{position}{position at finish line, string}
-#'   \item{rank}{rank at finish line, integer}
+#'   - `id` - event identifier
+#'   - `season` - year of Grand-Prix, 1995-now
+#'   - `date` - date of turnament
+#'   - `round` - round in season
+#'   - `name` - Turnament name
+#'   - `heat` - heat number, 1-23
+#'   - `field` - number of gate, 1-4
+#'   - `rider` - rider name, string
+#'   - `points` - paints gained, integer
+#'   - `position` - position at finish line, string
+#'   - `rank` - rank at finish line, integer
 #' }
 #' @source internal
 #' @name gpheats
@@ -24,19 +24,19 @@ NULL
 #' Turnament results of Speedway Grand-Prix
 #'
 #' Actual dataset containing turnament results of all Speedway Grand-Prix events
-#' \code{gpsquads}
+#' `gpsquads`
 #'
 #' @format A data frame with >4000 rows and 9 variables:
 #' \describe{
-#'   \item{id}{event identifier}
-#'   \item{season}{year of Grand-Prix, 1995-now}
-#'   \item{date}{date of turnament}
-#'   \item{place}{stadium of event}
-#'   \item{round}{round in season}
-#'   \item{name}{Turnament name}
-#'   \item{rider}{rider names, 1-6}
-#'   \item{points}{points gained, integer}
-#'   \item{classification}{classification after an event}
+#'   - `id` - event identifier
+#'   - `season` - year of Grand-Prix, 1995-now
+#'   - `date` - date of turnament
+#'   - `place` - stadium of event
+#'   - `round` - round in season
+#'   - `name` - Turnament name
+#'   - `rider` - rider names, 1-6
+#'   - `points` - points gained, integer
+#'   - `classification` - classification after an event
 #' }
 #' @source internal
 #' @name gpsquads
diff --git a/R/output.R b/R/output.R
index 4730570..763ed93 100755
--- a/R/output.R
+++ b/R/output.R
@@ -10,20 +10,20 @@ NULL
 #' @param object of class rating
 #' @param ... optional arguments
 #' @return
-#' List with following elements \itemize{
-#' \item \code{formula} modeled formula.
-#' \item \code{method} type of algorithm used.
-#' \item \code{Overall Accuracy} named vector containing players ratings.
-#' \item \code{r} data.frame summarized players ratings and model winning probabilities. Probabilities are returned only in models with one variable (ratings) \itemize{
-#' \item \code{name} of a player
-#' \item \code{r} players ratings
-#' \item \code{rd} players ratings deviation
-#' \item \code{`Model probability`} mean predicted probability of winning the challenge by the player.
-#' \item \code{`True probability`} mean observed probability of winning the challenge by the player.
-#' \item \code{`Accuracy`} Accuracy of prediction.
-#' \item \code{`pairings`} number of pairwise occurrences.
-#' }
-#' }
+#' List with following elements:
+#' - `formula` modeled formula.
+#' - `method` type of algorithm used.
+#' - `Overall Accuracy` named vector containing players ratings.
+#' - `r` data.frame summarized players ratings and model winning probabilities.
+#'
+#' Probabilities are returned only in models with one variable (ratings):
+#'   - `name` of a player
+#'   - `r` players ratings
+#'   - `rd` players ratings deviation
+#'   - `Model probability` mean predicted probability of winning the challenge by the player.
+#'   - `True probability` mean observed probability of winning the challenge by the player.
+#'   - `Accuracy` Accuracy of prediction.
+#'   - `pairings` number of pairwise occurrences.
 #'
 #' @examples
 #' model <- glicko_run(
@@ -141,7 +141,7 @@ plot.rating <- function(x, n = 10, players, ...) {
     names(data)[1] <- variable
 
     data <- data[order(data$r, decreasing = TRUE), ][1:n, ]
-    data[[variable]] <- reorder(data[[variable]], nrow(data):1)
+    data[[variable]] <- reorder(data[[variable]], rev(seq_len(nrow(data))))
     ggplot(data, aes(x = .data[[variable]], y = .data$r)) +
       ggtitle("Actual ratings") +
       geom_linerange(
diff --git a/R/predict.R b/R/predict.R
index cf2ab1b..0ec5614 100755
--- a/R/predict.R
+++ b/R/predict.R
@@ -13,7 +13,7 @@
 #' predict(glicko, gpheats[17:20, ])
 #' @export
 predict.rating <- function(object, newdata, ...) {
-  if (missing(newdata)) stop("newdata is requested to predict", call. = F)
+  if (missing(newdata)) stop("newdata is requested to predict", call. = FALSE)
   method <- attr(object, "method")
   formula <- attr(object, "formula")
   all_vars <- all.vars(formula)
@@ -89,8 +89,8 @@ predict.rating <- function(object, newdata, ...) {
     )
   }
 
-  P <- model$pairs # data.table
-  P <- P[, Y := ifelse(P > .5, 1, ifelse(P == .5, .5, 0))]
+  pairs <- model$pairs # data.table
+  pairs <- pairs[, Y := ifelse(P > .5, 1, ifelse(P == .5, .5, 0))]
 
-  return(P)
+  return(pairs)
 }
diff --git a/R/rating_run.R b/R/rating_run.R
index a31cf0c..8d54140 100755
--- a/R/rating_run.R
+++ b/R/rating_run.R
@@ -7,38 +7,38 @@ NULL
 #'
 #' Apply rating algorithm
 #' @param formula formula which specifies the model. RHS Allows only player
-#' rating parameter and it should be specified in following manner:
+#' rating parameter and it should be specified in following manner:\cr
 #'
-#' \code{rank | id ~ player(name)}.
-#' \itemize{
-#'   \item {rank} player position in event.
-#'   \item {id} event identifier in which pairwise comparison is assessed.
-#'   \item {player(name)} name of the contestant. In this case \code{player(name)}
+#' `rank | id ~ player(name)`.
+#' - `rank` player position in event.
+#' - `id` event identifier in which pairwise comparison is assessed.
+#' - `player(name)` name of the contestant. In this case `player(name)`
 #'     helps algorithm point name of the column where player names are stored.
-#' }
-#' Users can also specify formula in in different way:
-#'  \code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
+#'
+#' Users can also specify formula in in different way:\cr
+#'
+#'  `rank | id ~ player(name|team)`. Which means that players are playing in teams,
 #'  and results are observed for teams not for players. For more see vignette.
 #'
-#' @param method one of \code{c("glicko", "glicko2", "bbt", "dbl")}
+#' @param method one of `c("glicko", "glicko2", "bbt", "dbl")`
 #'
 #' @param data data.frame which contains columns specified in formula, and
-#'  optional columns defined by \code{lambda}, \code{weight}.
+#'  optional columns defined by `lambda`, `weight`.
 #'
 #' @param r named vector of initial players ratings estimates. If not specified
-#' then \code{r} will be created automatically for parameters specified in \code{formula}
-#' with initial value \code{init_r}.
+#' then `r` will be created automatically for parameters specified in `formula`
+#' with initial value `init_r`.
 #'
 #' @param rd rd named vector of initial rating deviation estimates. If not specified
-#' then \code{rd} will be created automatically for parameters specified in \code{formula}
-#' with initial value \code{init_rd}.
+#' then `rd` will be created automatically for parameters specified in `formula`
+#' with initial value `init_rd`.
 #'
 #' @param sigma (only for glicko2) named vector of initial players ratings
-#' estimates. If not specified then \code{sigma} will be created automatically for
-#' parameters specified in \code{formula} with initial value \code{init_sigma}.
+#' estimates. If not specified then `sigma` will be created automatically for
+#' parameters specified in `formula` with initial value `init_sigma`.
 #'
 #' @param lambda name of the column in `data` containing lambda values or one
-#' constant value (eg. \code{lambda = colname} or \code{lambda = 0.5}).
+#' constant value (eg. `lambda = colname` or `lambda = 0.5`).
 #' Lambda impact prior variance, and uncertainty of the matchup result. The
 #' higher lambda, the higher prior variance and more uncertain result of the
 #' matchup. Higher lambda flattens chances of winning.
@@ -50,29 +50,29 @@ NULL
 #'
 #'
 #' @param weight name of the column in `data` containing weights values or
-#' one constant (eg. \code{weight = colname} or \code{weight = 0.5}).
+#' one constant (eg. `weight = colname` or `weight = 0.5`).
 #' Weights increasing (weight > 1) or decreasing (weight < 1) update change.
 #' Higher weight increasing impact of event result on rating estimate.
 #'
-#' @param kappa controls \code{rd} shrinkage not to be greater than \code{rd*(1 - kappa)}.
-#'  `kappa=1` means that  \code{rd} will not be decreased.
+#' @param kappa controls `rd` shrinkage not to be greater than `rd*(1 - kappa)`.
+#'  `kappa=1` means that  `rd` will not be decreased.
 #' @param tau The system constant. Which constrains the change in volatility over
-#'  time. Reasonable choices are between 0.3 and 1.2 (\code{default = 0.5}), though
+#'  time. Reasonable choices are between 0.3 and 1.2 (`default = 0.5`), though
 #'  the system should be tested to decide which value results in greatest
-#'  predictive accuracy. Smaller values of \code{tau} prevent the volatility measures
+#'  predictive accuracy. Smaller values of `tau` prevent the volatility measures
 #'  from changing by large amounts, which in turn prevent enormous changes in
 #'  ratings based on very improbable results. If the application of Glicko-2 is
 #'  expected to involve extremely improbable collections of game outcomes, then
-#'  `tau` should be set to a small value, even as small as, say, \code{tau= 0}.
+#'  `tau` should be set to a small value, even as small as, say, `tau= 0`.
 #'
-#' @param init_r initial values for \code{r} if not provided.
-#' Default (\code{glicko = 1500}, \code{glicko2 = 1500}, \code{bbt = 25},
-#' \code{dbl = 0})
+#' @param init_r initial values for `r` if not provided.
+#' Default (`glicko = 1500`, `glicko2 = 1500`, `bbt = 25`,
+#' `dbl = 0`)
 #'
-#' @param init_rd initial values for \code{rd} if not provided.
-#' Default (\code{glicko = 350}, \code{glicko2 = 350}, \code{bbt = 25/3}, \code{dbl = 1})
+#' @param init_rd initial values for `rd` if not provided.
+#' Default (`glicko = 350`, `glicko2 = 350`, `bbt = 25/3`, `dbl = 1`)
 #'
-#' @param init_sigma initial values for \code{sigma} if not provided.
+#' @param init_sigma initial values for `sigma` if not provided.
 #' Default = 0.5
 #' @keywords internal
 rating_run <- function(
@@ -225,24 +225,17 @@ rating_run <- function(
 #'
 #' @return
 #'
-#' A "rating" object is returned: \itemize{
-#'
-#' \item \code{final_r} named vector containing players ratings.
-#'
-#' \item \code{final_rd} named vector containing players ratings deviations.
+#' A "rating" object is returned:
 #'
-#' \item \code{r} data.frame with evolution of the ratings and ratings deviations
+#' - `final_r` named vector containing players ratings.
+#' - `final_rd` named vector containing players ratings deviations.
+#' - `r` data.frame with evolution of the ratings and ratings deviations
 #'  estimated at each event.
-#'
-#' \item \code{pairs} pairwise combinations of players in analysed events with
+#' - `pairs` pairwise combinations of players in analysed events with
 #' prior probability and result of a challenge.
-#'
-#' \item \code{class} of the object.
-#'
-#' \item \code{method} type of algorithm used.
-#'
-#' \item \code{settings} arguments specified in function call.
-#' }
+#' - `class` of the object.
+#' - `method` type of algorithm used.
+#' - `settings` arguments specified in function call.
 #'
 #' @examples
 #' # the simplest example
@@ -321,26 +314,18 @@ glicko_run <- function(data, formula,
 #'
 #' @return
 #'
-#' A "rating" object is returned: \itemize{
+#' A "rating" object is returned:
 #'
-#' \item \code{final_r} named vector containing players ratings.
-#'
-#' \item \code{final_rd} named vector containing players ratings deviations.
-#'
-#' \item \code{final_sigma} named vector containing players ratings volatile.
-#'
-#' \item \code{r} data.frame with evolution of the ratings and ratings deviations
-#'  estimated at each event.
-#'
-#' \item \code{pairs} pairwise combinations of players in analysed events with
+#' - `final_r` named vector containing players ratings.
+#' - `final_rd` named vector containing players ratings deviations.
+#' - `final_sigma` named vector containing players ratings volatile.
+#' - `r` data.frame with evolution of the ratings and ratings deviations
+#' estimated at each event.
+#' - `pairs` pairwise combinations of players in analysed events with
 #' prior probability and result of a challenge.
-#'
-#' \item \code{class} of the object.
-#'
-#' \item \code{method} type of algorithm used.
-#'
-#' \item \code{settings} arguments specified in function call.
-#' }
+#' - `class` of the object.
+#' - `method` type of algorithm used.
+#' - `settings` arguments specified in function call.
 #'
 #' @examples
 #' # the simplest example
@@ -428,24 +413,16 @@ glicko2_run <- function(formula,
 #'
 #' @return
 #'
-#' A "rating" object is returned: \itemize{
-#'
-#' \item \code{final_r} named vector containing players ratings.
-#'
-#' \item \code{final_rd} named vector containing players ratings deviations.
-#'
-#' \item \code{r} data.frame with evolution of the ratings and ratings deviations
+#' A "rating" object is returned:
+#' - `final_r` named vector containing players ratings.
+#' - `final_rd` named vector containing players ratings deviations.
+#' - `r` data.frame with evolution of the ratings and ratings deviations
 #'  estimated at each event.
-#'
-#' \item \code{pairs} pairwise combinations of players in analysed events with
+#' - `pairs` pairwise combinations of players in analysed events with
 #' prior probability and result of a challenge.
-#'
-#' \item \code{class} of the object.
-#'
-#' \item \code{method} type of algorithm used.
-#'
-#' \item \code{settings} arguments specified in function call.
-#' }
+#' - `class` of the object.
+#' - `method` type of algorithm used.
+#' - `settings` arguments specified in function call.
 #'
 #' @examples
 #' # the simplest example
@@ -531,24 +508,17 @@ bbt_run <- function(formula,
 #'
 #' @return
 #'
-#' A "rating" object is returned: \itemize{
-#'
-#' \item \code{final_r} named vector containing players ratings.
-#'
-#' \item \code{final_rd} named vector containing players ratings deviations.
-#'
-#' \item \code{r} data.frame with evolution of the ratings and ratings deviations
+#' A "rating" object is returned:
+#' - `final_r` named vector containing players ratings.
+#' - `final_rd` named vector containing players ratings deviations.
+#' - `r` data.frame with evolution of the ratings and ratings deviations
 #'  estimated at each event.
-#'
-#' \item \code{pairs} pairwise combinations of players in analysed events with
+#' - `pairs` pairwise combinations of players in analysed events with
 #' prior probability and result of a challenge.
-#'
-#' \item \code{class} of the object.
-#'
-#' \item \code{method} type of algorithm used.
-#'
-#' \item \code{settings} arguments specified in function call.
-#' }
+#' - `class` of the object.
+#' - `method` type of algorithm used.
+#' - `settings` arguments specified in function call.
+#
 #'
 #' @examples
 #' # the simplest example
@@ -594,10 +564,10 @@ dbl_run <- function(formula,
 
 
   terms <- get_terms(data, formula)
-  MAP <- get_terms_map(data, terms)
-  X <- get_terms_mat(data, terms)
+  map <- get_terms_map(data, terms)
+  x <- get_terms_mat(data, terms)
   cls <- get_terms_cls(data, terms)
-  unique_params <- unname(unlist(apply(MAP, 2, unique)))
+  unique_params <- unname(unlist(apply(map, 2, unique)))
 
   team <- get_team_name(formula)
   team_vec <- as.character(data[[team]])
@@ -611,15 +581,13 @@ dbl_run <- function(formula,
 
   if (is.null(kappa)) kappa <- 0.0001
 
-
-
   g <- dbl(
     unique_id = unique(id_vec),
     id_vec = id_vec,
     rank_vec = rank_vec,
     team_vec = team_vec,
-    MAP = as.matrix(MAP),
-    X = as.matrix(X),
+    MAP = as.matrix(map),
+    X = as.matrix(x),
     cls = cls,
     R = r,
     RD = rd,
diff --git a/R/terms.R b/R/terms.R
index 5988f5b..23ba600 100755
--- a/R/terms.R
+++ b/R/terms.R
@@ -14,10 +14,12 @@ is_lhs_valid <- function(formula, data) {
   if (length(all.vars(update(formula, . ~ 0))) == 1) {
     warning("LHS of formula doesn't contain `| id` element.
             It will be assummed that all belongs to the same event id",
-      call. = F
+      call. = FALSE
     )
-  } else if (length(all.vars(update(formula, . ~ 0))) == 2 &
-    !grepl("[|]", format(update(formula, . ~ 0)))) {
+  } else if (
+    length(all.vars(update(formula, . ~ 0))) == 2 &&
+      !grepl("[|]", format(update(formula, . ~ 0)))
+  ) {
     stop("LHS of formula must be seperated by `|` operator eg. `rank | id ~ .`",
       call. = FALSE
     )
@@ -62,8 +64,7 @@ is_team_term_valid <- function(formula, single) {
   team_term_vars <- gsub("player\\(|\\)", "", team_term)
   team_term_vars <- trimws(unlist(strsplit(x = team_term_vars, split = "[|]")))
 
-  if (!length(team_term_vars) %in% c(1, 2) &&
-    all(team_term_vars != "")) {
+  if (!length(team_term_vars) %in% c(1, 2) && all(team_term_vars != "")) {
     stop("Only one or two variables are allowed within player(...) term function:
          Please specify as one of following:
          * player(player_var | team_var)
diff --git a/R/utils.R b/R/utils.R
index 0622ced..46c43ee 100755
--- a/R/utils.R
+++ b/R/utils.R
@@ -38,7 +38,8 @@ check_numeric_argument <- function(x, var_name, min = -Inf, max = Inf) {
       call. = FALSE
     )
   } else if (any(!is.finite(x))) {
-    stop(sprintf("Variable %s contains non-finite values. All elements should be finite.", var_name),
+    stop(
+      sprintf("Variable %s contains non-finite values. All elements should be finite.", var_name),
       call. = FALSE
     )
   } else if (any(x < min | x > max)) {
@@ -69,11 +70,10 @@ check_integer_argument <- function(x, var_name, min = -Inf, max = Inf) {
 
 check_string_argument <- function(x, var_name) {
   if (!is.character(x)) {
-    stop(sprintf("Variable %s should be of type character.", var_name),
-      call. = FALSE
-    )
+    stop(sprintf("Variable %s should be of type character.", var_name), call. = FALSE)
   } else if (any(is.na(x))) {
-    stop(sprintf("Variable %s contains non-finite values. All elements should be finite.", var_name),
+    stop(
+      sprintf("Variable %s contains non-finite values. All elements should be finite.", var_name),
       call. = FALSE
     )
   }
@@ -232,14 +232,15 @@ initialize_vec <- function(var, data, argname, min = -Inf, max = Inf) {
         var, argname
       ))
     }
-    var_vec <- data[[var]] # 1/n_it
+    var_vec <- data[[var]] # 1 divided by n_it
     check_numeric_argument(var_vec, var, min = min, max = max)
   } else if (is.numeric(var) && length(var) == 1) {
     check_numeric_argument(var, argname, min = min, max = max)
     var_vec <- rep(var, nrow(data))
   } else {
-    stop(sprintf("%s should be variable name from `data` argument or
-                 single numeric value.", argname))
+    stop(
+      sprintf("%s should be variable name from `data` argument or single numeric value.", argname)
+    )
   }
 
   return(var_vec)
diff --git a/data-raw/ranking.R b/data-raw/ranking.R
index 0e2fefb..a46f3f3 100755
--- a/data-raw/ranking.R
+++ b/data-raw/ranking.R
@@ -2,13 +2,13 @@
 #'
 #' Ranks multiple inputs with custom options
 #'
-#' @param a vector of attributes with prefix \code{a*} as variable to be ranked. Multiple arguments can be provided like \code{a1}, \code{a2}, ... \code{a10}. All arguments will be examined in given order to obtain ranking. If some observation have the same attribute (tie) then next argument will be decisive about ranking etc.
-#' @param b vector of attributes with prefix \code{b*}
-#' @param x vector with non-NA value pointing for an excluded from ranking. Ranking for \code{!is.na(x)} is being set to \code{NA} and others are updated
+#' @param a vector of attributes with prefix `a*` as variable to be ranked. Multiple arguments can be provided like `a1`, `a2`, ... `a10`. All arguments will be examined in given order to obtain ranking. If some observation have the same attribute (tie) then next argument will be decisive about ranking etc.
+#' @param b vector of attributes with prefix `b*`
+#' @param x vector with non-NA value pointing for an excluded from ranking. Ranking for `!is.na(x)` is being set to `NA` and others are updated
 #' @param ties method of dealing with ties. Available 'first' and default='none'
 #'
 #' @return A list with the elements
-#' \item{y}{The sum of the squared values.}
+#' - `y` - The sum of the squared values.
 #' @note This is a very simple function.
 #' @examples
 #' df <-
diff --git a/man/bbt_run.Rd b/man/bbt_run.Rd
index 2c1df3c..8700b83 100755
--- a/man/bbt_run.Rd
+++ b/man/bbt_run.Rd
@@ -19,18 +19,20 @@ bbt_run(
 }
 \arguments{
 \item{formula}{formula which specifies the model. RHS Allows only player
-rating parameter and it should be specified in following manner:
+rating parameter and it should be specified in following manner:\cr
 
 \code{rank | id ~ player(name)}.
 \itemize{
-  \item {rank} player position in event.
-  \item {id} event identifier in which pairwise comparison is assessed.
-  \item {player(name)} name of the contestant. In this case \code{player(name)}
-    helps algorithm point name of the column where player names are stored.
+\item \code{rank} player position in event.
+\item \code{id} event identifier in which pairwise comparison is assessed.
+\item \code{player(name)} name of the contestant. In this case \code{player(name)}
+helps algorithm point name of the column where player names are stored.
 }
-Users can also specify formula in in different way:
- \code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
- and results are observed for teams not for players. For more see vignette.}
+
+Users can also specify formula in in different way:\cr
+
+\code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
+and results are observed for teams not for players. For more see vignette.}
 
 \item{data}{data.frame which contains columns specified in formula, and
 optional columns defined by \code{lambda}, \code{weight}.}
@@ -50,42 +52,36 @@ Default (\code{glicko = 1500}, \code{glicko2 = 1500}, \code{bbt = 25},
 \item{init_rd}{initial values for \code{rd} if not provided.
 Default (\code{glicko = 350}, \code{glicko2 = 350}, \code{bbt = 25/3}, \code{dbl = 1})}
 
-\item{lambda}{name of the column in `data` containing lambda values or one
+\item{lambda}{name of the column in \code{data} containing lambda values or one
 constant value (eg. \code{lambda = colname} or \code{lambda = 0.5}).
 Lambda impact prior variance, and uncertainty of the matchup result. The
 higher lambda, the higher prior variance and more uncertain result of the
 matchup. Higher lambda flattens chances of winning.}
 
-\item{share}{name of the column in `data` containing player share in team
+\item{share}{name of the column in \code{data} containing player share in team
 efforts. It's used to first calculate combined rating of the team and
 then redistribute ratings update back to players level. Warning - it should
-be used only if formula is specified with players nested within teams (`player(player|team)`).}
+be used only if formula is specified with players nested within teams (\code{player(player|team)}).}
 
-\item{weight}{name of the column in `data` containing weights values or
+\item{weight}{name of the column in \code{data} containing weights values or
 one constant (eg. \code{weight = colname} or \code{weight = 0.5}).
 Weights increasing (weight > 1) or decreasing (weight < 1) update change.
 Higher weight increasing impact of event result on rating estimate.}
 
 \item{kappa}{controls \code{rd} shrinkage not to be greater than \code{rd*(1 - kappa)}.
-`kappa=1` means that  \code{rd} will not be decreased.}
+\code{kappa=1} means that  \code{rd} will not be decreased.}
 }
 \value{
-A "rating" object is returned: \itemize{
-
+A "rating" object is returned:
+\itemize{
 \item \code{final_r} named vector containing players ratings.
-
 \item \code{final_rd} named vector containing players ratings deviations.
-
 \item \code{r} data.frame with evolution of the ratings and ratings deviations
- estimated at each event.
-
+estimated at each event.
 \item \code{pairs} pairwise combinations of players in analysed events with
 prior probability and result of a challenge.
-
 \item \code{class} of the object.
-
 \item \code{method} type of algorithm used.
-
 \item \code{settings} arguments specified in function call.
 }
 }
diff --git a/man/dbl_run.Rd b/man/dbl_run.Rd
index df69b2a..0494796 100755
--- a/man/dbl_run.Rd
+++ b/man/dbl_run.Rd
@@ -19,8 +19,8 @@ dbl_run(
 \arguments{
 \item{formula}{formula which specifies the model. Unlike other algorithms
 in the packages (glicko_run, glicko2_run, bbt_run), this method doesn't allow
-players nested in teams with `player(player | team)` and user should matchup
-in formula using `player(player)`. DBL allows user specify multiple parameters
+players nested in teams with \code{player(player | team)} and user should matchup
+in formula using \code{player(player)}. DBL allows user specify multiple parameters
 also in interaction with others.}
 
 \item{data}{data.frame which contains columns specified in formula, and
@@ -34,19 +34,19 @@ with initial value \code{init_r}.}
 then \code{rd} will be created automatically for parameters specified in \code{formula}
 with initial value \code{init_rd}.}
 
-\item{lambda}{name of the column in `data` containing lambda values or one
+\item{lambda}{name of the column in \code{data} containing lambda values or one
 constant value (eg. \code{lambda = colname} or \code{lambda = 0.5}).
 Lambda impact prior variance, and uncertainty of the matchup result. The
 higher lambda, the higher prior variance and more uncertain result of the
 matchup. Higher lambda flattens chances of winning.}
 
-\item{weight}{name of the column in `data` containing weights values or
+\item{weight}{name of the column in \code{data} containing weights values or
 one constant (eg. \code{weight = colname} or \code{weight = 0.5}).
 Weights increasing (weight > 1) or decreasing (weight < 1) update change.
 Higher weight increasing impact of event result on rating estimate.}
 
 \item{kappa}{controls \code{rd} shrinkage not to be greater than \code{rd*(1 - kappa)}.
-`kappa=1` means that  \code{rd} will not be decreased.}
+\code{kappa=1} means that  \code{rd} will not be decreased.}
 
 \item{init_r}{initial values for \code{r} if not provided.
 Default (\code{glicko = 1500}, \code{glicko2 = 1500}, \code{bbt = 25},
@@ -56,22 +56,16 @@ Default (\code{glicko = 1500}, \code{glicko2 = 1500}, \code{bbt = 25},
 Default (\code{glicko = 350}, \code{glicko2 = 350}, \code{bbt = 25/3}, \code{dbl = 1})}
 }
 \value{
-A "rating" object is returned: \itemize{
-
+A "rating" object is returned:
+\itemize{
 \item \code{final_r} named vector containing players ratings.
-
 \item \code{final_rd} named vector containing players ratings deviations.
-
 \item \code{r} data.frame with evolution of the ratings and ratings deviations
- estimated at each event.
-
+estimated at each event.
 \item \code{pairs} pairwise combinations of players in analysed events with
 prior probability and result of a challenge.
-
 \item \code{class} of the object.
-
 \item \code{method} type of algorithm used.
-
 \item \code{settings} arguments specified in function call.
 }
 }
diff --git a/man/glicko2_run.Rd b/man/glicko2_run.Rd
index 09d5984..1a83b5b 100755
--- a/man/glicko2_run.Rd
+++ b/man/glicko2_run.Rd
@@ -22,18 +22,20 @@ glicko2_run(
 }
 \arguments{
 \item{formula}{formula which specifies the model. RHS Allows only player
-rating parameter and it should be specified in following manner:
+rating parameter and it should be specified in following manner:\cr
 
 \code{rank | id ~ player(name)}.
 \itemize{
-  \item {rank} player position in event.
-  \item {id} event identifier in which pairwise comparison is assessed.
-  \item {player(name)} name of the contestant. In this case \code{player(name)}
-    helps algorithm point name of the column where player names are stored.
+\item \code{rank} player position in event.
+\item \code{id} event identifier in which pairwise comparison is assessed.
+\item \code{player(name)} name of the contestant. In this case \code{player(name)}
+helps algorithm point name of the column where player names are stored.
 }
-Users can also specify formula in in different way:
- \code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
- and results are observed for teams not for players. For more see vignette.}
+
+Users can also specify formula in in different way:\cr
+
+\code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
+and results are observed for teams not for players. For more see vignette.}
 
 \item{data}{data.frame which contains columns specified in formula, and
 optional columns defined by \code{lambda}, \code{weight}.}
@@ -50,18 +52,18 @@ with initial value \code{init_rd}.}
 estimates. If not specified then \code{sigma} will be created automatically for
 parameters specified in \code{formula} with initial value \code{init_sigma}.}
 
-\item{lambda}{name of the column in `data` containing lambda values or one
+\item{lambda}{name of the column in \code{data} containing lambda values or one
 constant value (eg. \code{lambda = colname} or \code{lambda = 0.5}).
 Lambda impact prior variance, and uncertainty of the matchup result. The
 higher lambda, the higher prior variance and more uncertain result of the
 matchup. Higher lambda flattens chances of winning.}
 
-\item{share}{name of the column in `data` containing player share in team
+\item{share}{name of the column in \code{data} containing player share in team
 efforts. It's used to first calculate combined rating of the team and
 then redistribute ratings update back to players level. Warning - it should
-be used only if formula is specified with players nested within teams (`player(player|team)`).}
+be used only if formula is specified with players nested within teams (\code{player(player|team)}).}
 
-\item{weight}{name of the column in `data` containing weights values or
+\item{weight}{name of the column in \code{data} containing weights values or
 one constant (eg. \code{weight = colname} or \code{weight = 0.5}).
 Weights increasing (weight > 1) or decreasing (weight < 1) update change.
 Higher weight increasing impact of event result on rating estimate.}
@@ -77,7 +79,7 @@ Default (\code{glicko = 350}, \code{glicko2 = 350}, \code{bbt = 25/3}, \code{dbl
 Default = 0.5}
 
 \item{kappa}{controls \code{rd} shrinkage not to be greater than \code{rd*(1 - kappa)}.
-`kappa=1` means that  \code{rd} will not be decreased.}
+\code{kappa=1} means that  \code{rd} will not be decreased.}
 
 \item{tau}{The system constant. Which constrains the change in volatility over
 time. Reasonable choices are between 0.3 and 1.2 (\code{default = 0.5}), though
@@ -86,27 +88,20 @@ predictive accuracy. Smaller values of \code{tau} prevent the volatility measure
 from changing by large amounts, which in turn prevent enormous changes in
 ratings based on very improbable results. If the application of Glicko-2 is
 expected to involve extremely improbable collections of game outcomes, then
-`tau` should be set to a small value, even as small as, say, \code{tau= 0}.}
+\code{tau} should be set to a small value, even as small as, say, \code{tau= 0}.}
 }
 \value{
-A "rating" object is returned: \itemize{
-
+A "rating" object is returned:
+\itemize{
 \item \code{final_r} named vector containing players ratings.
-
 \item \code{final_rd} named vector containing players ratings deviations.
-
 \item \code{final_sigma} named vector containing players ratings volatile.
-
 \item \code{r} data.frame with evolution of the ratings and ratings deviations
- estimated at each event.
-
+estimated at each event.
 \item \code{pairs} pairwise combinations of players in analysed events with
 prior probability and result of a challenge.
-
 \item \code{class} of the object.
-
 \item \code{method} type of algorithm used.
-
 \item \code{settings} arguments specified in function call.
 }
 }
diff --git a/man/glicko_run.Rd b/man/glicko_run.Rd
index e59e15b..85023bc 100755
--- a/man/glicko_run.Rd
+++ b/man/glicko_run.Rd
@@ -22,18 +22,20 @@ glicko_run(
 optional columns defined by \code{lambda}, \code{weight}.}
 
 \item{formula}{formula which specifies the model. RHS Allows only player
-rating parameter and it should be specified in following manner:
+rating parameter and it should be specified in following manner:\cr
 
 \code{rank | id ~ player(name)}.
 \itemize{
-  \item {rank} player position in event.
-  \item {id} event identifier in which pairwise comparison is assessed.
-  \item {player(name)} name of the contestant. In this case \code{player(name)}
-    helps algorithm point name of the column where player names are stored.
+\item \code{rank} player position in event.
+\item \code{id} event identifier in which pairwise comparison is assessed.
+\item \code{player(name)} name of the contestant. In this case \code{player(name)}
+helps algorithm point name of the column where player names are stored.
 }
-Users can also specify formula in in different way:
- \code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
- and results are observed for teams not for players. For more see vignette.}
+
+Users can also specify formula in in different way:\cr
+
+\code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
+and results are observed for teams not for players. For more see vignette.}
 
 \item{r}{named vector of initial players ratings estimates. If not specified
 then \code{r} will be created automatically for parameters specified in \code{formula}
@@ -50,42 +52,36 @@ Default (\code{glicko = 1500}, \code{glicko2 = 1500}, \code{bbt = 25},
 \item{init_rd}{initial values for \code{rd} if not provided.
 Default (\code{glicko = 350}, \code{glicko2 = 350}, \code{bbt = 25/3}, \code{dbl = 1})}
 
-\item{lambda}{name of the column in `data` containing lambda values or one
+\item{lambda}{name of the column in \code{data} containing lambda values or one
 constant value (eg. \code{lambda = colname} or \code{lambda = 0.5}).
 Lambda impact prior variance, and uncertainty of the matchup result. The
 higher lambda, the higher prior variance and more uncertain result of the
 matchup. Higher lambda flattens chances of winning.}
 
-\item{share}{name of the column in `data` containing player share in team
+\item{share}{name of the column in \code{data} containing player share in team
 efforts. It's used to first calculate combined rating of the team and
 then redistribute ratings update back to players level. Warning - it should
-be used only if formula is specified with players nested within teams (`player(player|team)`).}
+be used only if formula is specified with players nested within teams (\code{player(player|team)}).}
 
-\item{weight}{name of the column in `data` containing weights values or
+\item{weight}{name of the column in \code{data} containing weights values or
 one constant (eg. \code{weight = colname} or \code{weight = 0.5}).
 Weights increasing (weight > 1) or decreasing (weight < 1) update change.
 Higher weight increasing impact of event result on rating estimate.}
 
 \item{kappa}{controls \code{rd} shrinkage not to be greater than \code{rd*(1 - kappa)}.
-`kappa=1` means that  \code{rd} will not be decreased.}
+\code{kappa=1} means that  \code{rd} will not be decreased.}
 }
 \value{
-A "rating" object is returned: \itemize{
-
+A "rating" object is returned:
+\itemize{
 \item \code{final_r} named vector containing players ratings.
-
 \item \code{final_rd} named vector containing players ratings deviations.
-
 \item \code{r} data.frame with evolution of the ratings and ratings deviations
- estimated at each event.
-
+estimated at each event.
 \item \code{pairs} pairwise combinations of players in analysed events with
 prior probability and result of a challenge.
-
 \item \code{class} of the object.
-
 \item \code{method} type of algorithm used.
-
 \item \code{settings} arguments specified in function call.
 }
 }
diff --git a/man/gpheats.Rd b/man/gpheats.Rd
index 2587e0a..9ecd14e 100755
--- a/man/gpheats.Rd
+++ b/man/gpheats.Rd
@@ -6,17 +6,19 @@
 \format{
 A data frame with >19000 rows and 11 variables:
 \describe{
-  \item{id}{event identifier}
-  \item{season}{year of Grand-Prix, 1995-now}
-  \item{date}{date of turnament}
-  \item{round}{round in season}
-  \item{name}{Turnament name}
-  \item{heat}{heat number, 1-23}
-  \item{field}{number of gate, 1-4}
-  \item{rider}{rider name, string}
-  \item{points}{paints gained, integer}
-  \item{position}{position at finish line, string}
-  \item{rank}{rank at finish line, integer}
+\itemize{
+\item \code{id} - event identifier
+\item \code{season} - year of Grand-Prix, 1995-now
+\item \code{date} - date of turnament
+\item \code{round} - round in season
+\item \code{name} - Turnament name
+\item \code{heat} - heat number, 1-23
+\item \code{field} - number of gate, 1-4
+\item \code{rider} - rider name, string
+\item \code{points} - paints gained, integer
+\item \code{position} - position at finish line, string
+\item \code{rank} - rank at finish line, integer
+}
 }
 }
 \source{
diff --git a/man/gpsquads.Rd b/man/gpsquads.Rd
index f70ca54..279d613 100755
--- a/man/gpsquads.Rd
+++ b/man/gpsquads.Rd
@@ -6,15 +6,17 @@
 \format{
 A data frame with >4000 rows and 9 variables:
 \describe{
-  \item{id}{event identifier}
-  \item{season}{year of Grand-Prix, 1995-now}
-  \item{date}{date of turnament}
-  \item{place}{stadium of event}
-  \item{round}{round in season}
-  \item{name}{Turnament name}
-  \item{rider}{rider names, 1-6}
-  \item{points}{points gained, integer}
-  \item{classification}{classification after an event}
+\itemize{
+\item \code{id} - event identifier
+\item \code{season} - year of Grand-Prix, 1995-now
+\item \code{date} - date of turnament
+\item \code{place} - stadium of event
+\item \code{round} - round in season
+\item \code{name} - Turnament name
+\item \code{rider} - rider names, 1-6
+\item \code{points} - points gained, integer
+\item \code{classification} - classification after an event
+}
 }
 }
 \source{
diff --git a/man/rating_run.Rd b/man/rating_run.Rd
index 6741920..a6a270f 100644
--- a/man/rating_run.Rd
+++ b/man/rating_run.Rd
@@ -28,18 +28,20 @@ rating_run(
 optional columns defined by \code{lambda}, \code{weight}.}
 
 \item{formula}{formula which specifies the model. RHS Allows only player
-rating parameter and it should be specified in following manner:
+rating parameter and it should be specified in following manner:\cr
 
 \code{rank | id ~ player(name)}.
 \itemize{
-  \item {rank} player position in event.
-  \item {id} event identifier in which pairwise comparison is assessed.
-  \item {player(name)} name of the contestant. In this case \code{player(name)}
-    helps algorithm point name of the column where player names are stored.
+\item \code{rank} player position in event.
+\item \code{id} event identifier in which pairwise comparison is assessed.
+\item \code{player(name)} name of the contestant. In this case \code{player(name)}
+helps algorithm point name of the column where player names are stored.
 }
-Users can also specify formula in in different way:
- \code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
- and results are observed for teams not for players. For more see vignette.}
+
+Users can also specify formula in in different way:\cr
+
+\code{rank | id ~ player(name|team)}. Which means that players are playing in teams,
+and results are observed for teams not for players. For more see vignette.}
 
 \item{r}{named vector of initial players ratings estimates. If not specified
 then \code{r} will be created automatically for parameters specified in \code{formula}
@@ -63,24 +65,24 @@ Default (\code{glicko = 350}, \code{glicko2 = 350}, \code{bbt = 25/3}, \code{dbl
 \item{init_sigma}{initial values for \code{sigma} if not provided.
 Default = 0.5}
 
-\item{lambda}{name of the column in `data` containing lambda values or one
+\item{lambda}{name of the column in \code{data} containing lambda values or one
 constant value (eg. \code{lambda = colname} or \code{lambda = 0.5}).
 Lambda impact prior variance, and uncertainty of the matchup result. The
 higher lambda, the higher prior variance and more uncertain result of the
 matchup. Higher lambda flattens chances of winning.}
 
-\item{share}{name of the column in `data` containing player share in team
+\item{share}{name of the column in \code{data} containing player share in team
 efforts. It's used to first calculate combined rating of the team and
 then redistribute ratings update back to players level. Warning - it should
-be used only if formula is specified with players nested within teams (`player(player|team)`).}
+be used only if formula is specified with players nested within teams (\code{player(player|team)}).}
 
-\item{weight}{name of the column in `data` containing weights values or
+\item{weight}{name of the column in \code{data} containing weights values or
 one constant (eg. \code{weight = colname} or \code{weight = 0.5}).
 Weights increasing (weight > 1) or decreasing (weight < 1) update change.
 Higher weight increasing impact of event result on rating estimate.}
 
 \item{kappa}{controls \code{rd} shrinkage not to be greater than \code{rd*(1 - kappa)}.
-`kappa=1` means that  \code{rd} will not be decreased.}
+\code{kappa=1} means that  \code{rd} will not be decreased.}
 
 \item{tau}{The system constant. Which constrains the change in volatility over
 time. Reasonable choices are between 0.3 and 1.2 (\code{default = 0.5}), though
@@ -89,7 +91,7 @@ predictive accuracy. Smaller values of \code{tau} prevent the volatility measure
 from changing by large amounts, which in turn prevent enormous changes in
 ratings based on very improbable results. If the application of Glicko-2 is
 expected to involve extremely improbable collections of game outcomes, then
-`tau` should be set to a small value, even as small as, say, \code{tau= 0}.}
+\code{tau} should be set to a small value, even as small as, say, \code{tau= 0}.}
 }
 \description{
 Apply rating algorithm
diff --git a/man/summary.rating.Rd b/man/summary.rating.Rd
index 19974a2..b022767 100755
--- a/man/summary.rating.Rd
+++ b/man/summary.rating.Rd
@@ -12,24 +12,28 @@
 \item{...}{optional arguments}
 }
 \value{
-List with following elements \itemize{
+List with following elements:
+\itemize{
 \item \code{formula} modeled formula.
 \item \code{method} type of algorithm used.
-\item \code{Overall Accuracy} named vector containing players ratings.
-\item \code{r} data.frame summarized players ratings and model winning probabilities. Probabilities are returned only in models with one variable (ratings) \itemize{
+\item \verb{Overall Accuracy} named vector containing players ratings.
+\item \code{r} data.frame summarized players ratings and model winning probabilities.
+}
+
+Probabilities are returned only in models with one variable (ratings):
+\itemize{
 \item \code{name} of a player
 \item \code{r} players ratings
 \item \code{rd} players ratings deviation
-\item \code{`Model probability`} mean predicted probability of winning the challenge by the player.
-\item \code{`True probability`} mean observed probability of winning the challenge by the player.
-\item \code{`Accuracy`} Accuracy of prediction.
-\item \code{`pairings`} number of pairwise occurrences.
-}
+\item \verb{Model probability} mean predicted probability of winning the challenge by the player.
+\item \verb{True probability} mean observed probability of winning the challenge by the player.
+\item \code{Accuracy} Accuracy of prediction.
+\item \code{pairings} number of pairwise occurrences.
 }
 }
 \description{
 Summarizing rating objects
-Summary for object of class `rating`
+Summary for object of class \code{rating}
 }
 \examples{
 model <- glicko_run(