Package 'vscoututils' reference manual

Title:	Utility Functions for Volleyball Scout Files
Description:	Common utility functions shared across various volleyball scouting and data access packages. Functions in this package are likely to be mostly of interest to package developers, rather than end users.
Authors:	Ben Raymond [aut, cre], Adrien Ickowicz [aut]
Maintainer:	Ben Raymond <[email protected]>
License:	MIT + file LICENSE
Version:	0.1.9
Built:	2024-11-11 09:18:25 UTC
Source:	https://github.com/openvolley/vscoututils

Create the `file_meta` component of a datavolley object

Description

Create the file_meta component of a datavolley object

Usage

dv_create_file_meta(
  file_type = "indoor",
  date_format = "%Y/%m/%d",
  generator_day,
  generator_idp,
  generator_prg,
  generator_release,
  generator_version,
  generator_name
)
dv_create_file_meta(
  file_type = "indoor",
  date_format = "%Y/%m/%d",
  generator_day,
  generator_idp,
  generator_prg,
  generator_release,
  generator_version,
  generator_name
)

Arguments

`file_type`	string: "indoor", "beach"
`date_format`	string: preferred date format
`generator_day`	datetime: date and time of file creation
`generator_idp`, `generator_prg`, `generator_release`, `generator_version`, `generator_name`	string: information about the software that generated the file. If missing, defaults will be used

Value

A tibble

Create metadata component of a datavolley object

Description

Create metadata component of a datavolley object

Usage

dv_create_meta(
  match,
  more,
  comments,
  result,
  teams,
  players_h,
  players_v,
  video,
  attacks,
  setter_calls,
  winning_symbols,
  data_type = "indoor",
  style = "default"
)
dv_create_meta(
  match,
  more,
  comments,
  result,
  teams,
  players_h,
  players_v,
  video,
  attacks,
  setter_calls,
  winning_symbols,
  data_type = "indoor",
  style = "default"
)

Arguments

`match`	tibble: as returned by `dv_create_meta_match()`
`more`	tibble: as returned by `dv_create_meta_more()`
`comments`	tibble: as returned by `dv_create_meta_comments()`
`result`	tibble: as returned by `dv_create_meta_result()`
`teams`	tibble: as returned by `dv_create_meta_teams()`
`players_h`	tibble: home team table as returned by `dv_create_meta_players()`
`players_v`	tibble: visiting team table as returned by `dv_create_meta_players()`
`video`	tibble: as returned by `dv_create_meta_video()`
`attacks`	tibble: as returned by `dv_create_meta_attack_combos()`. If missing, the default attack combos for `data_type` and `style` and `simplified = TRUE` will be used
`setter_calls`	tibble: as returned by `dv_create_meta_setter_calls()`. If missing, the default setter calls for `data_type` and `style` will be used
`winning_symbols`	tibble: as returned by `dv_default_winning_symbols()`. If missing, the default winning symbols for `data_type` and `style` will be used
`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A list

Examples

 dv_create_meta(match = dv_create_meta_match(zones_or_cones = "Z"), more = dv_create_meta_more(),
                comments = dv_create_meta_comments(),
                teams = dv_create_meta_teams(
                    team_ids = c("ardv", "badg"), teams = c("Aardvarks", "Badgers")))

dv_create_meta(match = dv_create_meta_match(zones_or_cones = "Z"), more = dv_create_meta_more(),
                comments = dv_create_meta_comments(),
                teams = dv_create_meta_teams(
                    team_ids = c("ardv", "badg"), teams = c("Aardvarks", "Badgers")))

Create the `attacks` metadata component of a datavolley object

Description

The attacks metadata component of a datavolley object describes the attack combination codes

Usage

dv_create_meta_attack_combos(
  code,
  start_zone,
  side = NA_character_,
  tempo,
  description,
  colour = NA_character_,
  start_coordinate = NA_integer_,
  target_attacker
)
dv_create_meta_attack_combos(
  code,
  start_zone,
  side = NA_character_,
  tempo,
  description,
  colour = NA_character_,
  start_coordinate = NA_integer_,
  target_attacker
)

Arguments

`code`	character: vector of two-character (uppercase) attack codes. Attack codes must start with C, G, I, J, L, P, V, W, X, Y, or Z
`start_zone`	integer: vector of start zones
`side`	character: vector of L, C, R
`tempo`	character: vector of tempo codes F, H, M, N, O, Q, T, U
`description`	character: vector of attack descriptions
`colour`	character: vector of colour codes (maybe) used when plotting, in "#RRGGBB" format
`start_coordinate`	integer: vector of start locations as single-index coordinates (see e.g. `datavolley:dv_xy2index`)
`target_attacker`	character: vector of single-character codes giving the target attacker: B (back/right side attacker), C (centre), F (front/left side attacker), P (pipe), S (setter attack)

Value

A tibble

Create the `comments` metadata component of a datavolley object

Description

Create the comments metadata component of a datavolley object

Usage

dv_create_meta_comments(
  summary,
  match_description,
  home_coach_comments,
  visiting_coach_comments
)
dv_create_meta_comments(
  summary,
  match_description,
  home_coach_comments,
  visiting_coach_comments
)

Arguments

summary, match_description, home_coach_comments, visiting_coach_comments

string: comments

Value

A tibble

Create the `match` metadata component of a datavolley object

Description

Create the match metadata component of a datavolley object

Usage

dv_create_meta_match(
  date,
  season,
  league,
  phase,
  home_away,
  day_number,
  match_number,
  regulation = "indoor rally point",
  zones_or_cones
)
dv_create_meta_match(
  date,
  season,
  league,
  phase,
  home_away,
  day_number,
  match_number,
  regulation = "indoor rally point",
  zones_or_cones
)

Arguments

`date`	Date or datetime: match date and time
`season`	string: season name
`league`	string: league name
`phase`	string: match phase (e.g. "Playoffs", "Finals")
`home_away`	string: typically "Home" or "Away"
`day_number`, `match_number`	numeric: day and match number
`regulation`	string: "indoor sideout", "indoor rally point" (default), or "beach rally point"
`zones_or_cones`	string: are attacks being scouted with "zones" or "cones" (or "Z" or "C")

Value

A tibble

Create the `match_id` metadata component of a datavolley object

Description

The match_id is generated from the match and teams components of the mx object, so ensure that these are fully populated before generating a match_id

Usage

dv_create_meta_match_id(mx)
dv_create_meta_match_id(mx)

Arguments

`mx`	list: the `meta` component of a datavolley object

Value

A string

Create the `more` metadata component of a datavolley object

Description

Create the more metadata component of a datavolley object

Usage

dv_create_meta_more(referees, spectators, receipts, city, arena, scout)
dv_create_meta_more(referees, spectators, receipts, city, arena, scout)

Arguments

`referees`, `spectators`, `receipts`, `city`, `arena`	string: match descriptors
`scout`	string: name of the scout

Value

A tibble

Create the `players_h` or `players_v` metadata component of a datavolley object

Description

Create the players_h or players_v metadata component of a datavolley object

Usage

dv_create_meta_players(players)
dv_create_meta_players(players)

Arguments

players

data.frame: the team roster, as a data.frame. players must contain the columns lastname, firstname, and number. Columns player_id, role, nickname, special_role, foreign, and starting_position_set1 - starting_position_set5 are optional

Value

A tibble

Create the `result` metadata component of a datavolley object

Description

Note that the returned object has some NA values. It is expected that the user will call dv_update_meta() on the full datavolley object, which will update entries in this metadata component.

Usage

dv_create_meta_result(
  home_team_scores = NA_integer_,
  visiting_team_scores = NA_integer_,
  durations = NA_integer_
)
dv_create_meta_result(
  home_team_scores = NA_integer_,
  visiting_team_scores = NA_integer_,
  durations = NA_integer_
)

Arguments

`home_team_scores`	integer: vector of home team scores in each set
`visiting_team_scores`	integer: vector of visiting team scores in each set
`durations`	integer: vector of set durations (in minutes). If not provided, these will be calculated from video times by `dv_update_meta()`

Value

A tibble

Create the `sets` (setter calls) metadata component of a datavolley object

Description

Create the sets (setter calls) metadata component of a datavolley object

Usage

dv_create_meta_setter_calls(
  code,
  description,
  colour = NA_character_,
  start_coordinate = NA_integer_,
  mid_coordinate = NA_integer_,
  end_coordinate = NA_integer_,
  path = NA_character_,
  path_colour = NA_character_
)
dv_create_meta_setter_calls(
  code,
  description,
  colour = NA_character_,
  start_coordinate = NA_integer_,
  mid_coordinate = NA_integer_,
  end_coordinate = NA_integer_,
  path = NA_character_,
  path_colour = NA_character_
)

Arguments

`code`	character: vector of two-character (uppercase) setter call codes. Setter call codes must start with K
`description`	character: vector of setter call descriptions
`colour`	character: vector of colour codes (maybe) used when plotting, in "#RRGGBB" format
`start_coordinate`, `mid_coordinate`, `end_coordinate`	integer: vector of start/mid/end locations as single-index coordinates (see e.g. `datavolley:dv_xy2index`)
`path`	character: vector of paths, each a comma-separated list of single-index coordinates
`path_colour`	character: vector of colour codes in "#RRGGBB" format

Value

A tibble

Create the `teams` metadata component of a datavolley object

Description

dv_create_meta_teams2 provides an alternative parameterization with home and visiting team information specified separately.

Usage

dv_create_meta_teams(
  team_ids,
  teams,
  sets_won,
  coaches,
  assistants,
  shirt_colours
)

dv_create_meta_teams2(
  home_team_id,
  home_team,
  home_coach,
  home_assistant,
  home_shirt_colour,
  visiting_team_id,
  visiting_team,
  visiting_coach,
  visiting_assistant,
  visiting_shirt_colour,
  sets_won
)
dv_create_meta_teams(
  team_ids,
  teams,
  sets_won,
  coaches,
  assistants,
  shirt_colours
)

dv_create_meta_teams2(
  home_team_id,
  home_team,
  home_coach,
  home_assistant,
  home_shirt_colour,
  visiting_team_id,
  visiting_team,
  visiting_coach,
  visiting_assistant,
  visiting_shirt_colour,
  sets_won
)

Arguments

`team_ids`	character: (required) 2-element vector of home and visiting team IDs
`teams`	character: (required) 2-element vector of home and visiting team names
`sets_won`	integer: 2-element vector of the number of sets won by the home team and visiting team
`coaches`	character: 2-element vector of home and visiting team coach names
`assistants`	character: 2-element vector of home and visiting team assistant coach names
`shirt_colours`	character: 2-element vector of home and visiting team shirt colours in "#RRGGBB" format
`home_team_id`, `visiting_team_id`	string: home and visiting team IDs
`home_team`, `visiting_team`	string: home and visiting team names
`home_coach`, `visiting_coach`	string: home and visiting coach name
`home_assistant`, `visiting_assistant`	string: home and visiting assistant coach name
`home_shirt_colour`, `visiting_shirt_colour`	string: home and visiting shirt colours in "#RRGGBB" format

Value

A tibble

Create the `video` metadata component of a datavolley object

Description

Create the video metadata component of a datavolley object

Usage

dv_create_meta_video(video_file)
dv_create_meta_video(video_file)

Arguments

video_file

character: path to video file. More than one is allowed, but anything other than the first might be ignored by some functions

Value

A data.frame

Decode evaluation codes

Description

Decode evaluation codes

Usage

dv_decode_evaluation(
  skill,
  evaluation_code,
  table,
  data_type = "indoor",
  style = "default"
)
dv_decode_evaluation(
  skill,
  evaluation_code,
  table,
  data_type = "indoor",
  style = "default"
)

Arguments

`skill`	character: full skill names (Serve, Reception, etc)
`evaluation_code`	character: evaluation codes (#, +, etc)
`table`	data.frame: optional table with columns `skill`, `evaluation_code`, `evaluation`. If not provided, the default table for `data_type` and `style` will be used
`data_type`	string: "indoor" or "beach"
`style`	string: "default", "volleymetrics"

Value

A character vector of evaluations, with a "dvmessages" attribute if any issues were found

Examples

dv_decode_evaluation("Serve", "#")
dv_decode_evaluation("Attack", "!")

dv_decode_evaluation("Serve", "#")
dv_decode_evaluation("Attack", "!")

Decode number of players

Description

Decode number of players

Usage

dv_decode_num_players(
  skill,
  num_players_code,
  table,
  data_type = "indoor",
  style = "default"
)
dv_decode_num_players(
  skill,
  num_players_code,
  table,
  data_type = "indoor",
  style = "default"
)

Arguments

`skill`	character: full skill names (Serve, Reception, etc)
`num_players_code`	character: number of players codes (0, 1, etc)
`table`	data.frame: optional table with columns `skill`, `num_players_code`, `num_players`. If not provided, the default table for `data_type` and `style` will be used
`data_type`	string: "indoor" or "beach"
`style`	string: "default", "volleymetrics"

Value

A character vector of number of players, with a "dvmessages" attribute if any issues were found

Examples

dv_decode_num_players("Reception", 7)
dv_decode_num_players("Attack", 3, data_type = "beach")

dv_decode_num_players("Reception", 7)
dv_decode_num_players("Attack", 3, data_type = "beach")

Decode skill subtypes

Description

Decode skill subtypes

Usage

dv_decode_skill_subtype(
  skill,
  skill_subtype_code,
  evaluation,
  table,
  data_type = "indoor",
  style = "default"
)
dv_decode_skill_subtype(
  skill,
  skill_subtype_code,
  evaluation,
  table,
  data_type = "indoor",
  style = "default"
)

Arguments

`skill`	character: full skill names (Serve, Reception, etc)
`skill_subtype_code`	character: subtype codes (H, P, etc)
`evaluation`	character: skill evaluations (Ace, Perfect pass, etc). Only used to make small adjustments for certain scouting styles, which will be skipped if `evaluation` is not provided
`table`	data.frame: optional table with columns `skill`, `skill_subtype_code`, `skill_subtype`. If not provided, the default table for `data_type` and `style` will be used
`data_type`	string: "indoor" or "beach"
`style`	string: "default", "volleymetrics"

Value

A character vector of skill subtypes, with a "dvmessages" attribute if any issues were found

Examples

dv_decode_skill_subtype("Reception", "M")
dv_decode_skill_subtype("Attack", "P")
dv_decode_skill_subtype("Dig", "Q")

dv_decode_skill_subtype("Reception", "M")
dv_decode_skill_subtype("Attack", "P")
dv_decode_skill_subtype("Dig", "Q")

Decode skill type (tempo) codes

Description

Decode skill type (tempo) codes

Usage

dv_decode_skill_type(
  skill,
  skill_type_code,
  table,
  data_type = "indoor",
  style = "default"
)
dv_decode_skill_type(
  skill,
  skill_type_code,
  table,
  data_type = "indoor",
  style = "default"
)

Arguments

`skill`	character: full skill names (Serve, Reception, etc)
`skill_type_code`	character: skill type (tempo) codes (Q, M, H, etc)
`table`	data.frame: optional table with columns `skill`, `skill_type_code`, `skill_type`. If not provided, the default table for `data_type` and `style` will be used
`data_type`	string: "indoor" or "beach"
`style`	string: "default", "volleymetrics"

Value

A character vector of skill types, with a "dvmessages" attribute if any issues were found

Examples

dv_decode_skill_type("Serve", "Q")
dv_decode_skill_type("Attack", "Z")

dv_decode_skill_type("Serve", "Q")
dv_decode_skill_type("Attack", "Z")

Decode special codes

Description

Decode special codes

Usage

dv_decode_special_code(
  skill,
  special_code,
  evaluation,
  table,
  data_type = "indoor",
  style = "default"
)
dv_decode_special_code(
  skill,
  special_code,
  evaluation,
  table,
  data_type = "indoor",
  style = "default"
)

Arguments

`skill`	character: full skill names (Serve, Reception, etc)
`special_code`	character: special codes (Z, U, etc)
`evaluation`	character: skill evaluations (Ace, Perfect pass, etc)
`table`	data.frame: optional table with columns `skill`, `special_code`, `special`. If not provided, the default table for `data_type` and `style` will be used
`data_type`	string: "indoor" or "beach"
`style`	string: "default", "volleymetrics"

Value

A character vector of special code interpretations, with a "dvmessages" attribute if any issues were found

Examples

dv_decode_special_code("Reception", "P", NA_character_) ## evaluation is irrelevant here
dv_decode_special_code("Attack", "N", "Error")
dv_decode_special_code("Attack", "N", "Winning attack") ## different interpretation if not an error
dv_decode_special_code("Attack", "C", "Winning attack") ## "C" is not valid for winning attack
dv_decode_special_code("Attack", "C", "Positive, good attack") ## but is for attacks in play
dv_decode_special_code("Attack", "Q", "Positive, good attack") ## this is invalid everywhere

dv_decode_special_code("Reception", "P", NA_character_) ## evaluation is irrelevant here
dv_decode_special_code("Attack", "N", "Error")
dv_decode_special_code("Attack", "N", "Winning attack") ## different interpretation if not an error
dv_decode_special_code("Attack", "C", "Winning attack") ## "C" is not valid for winning attack
dv_decode_special_code("Attack", "C", "Positive, good attack") ## but is for attacks in play
dv_decode_special_code("Attack", "Q", "Positive, good attack") ## this is invalid everywhere

Default attack combination codes table

Description

Default attack combination codes table

Usage

dv_default_attack_combos(
  data_type = "indoor",
  style = "default",
  simplified = TRUE
)
dv_default_attack_combos(
  data_type = "indoor",
  style = "default",
  simplified = TRUE
)

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"
`simplified`	logical: if `TRUE`, just the most common ones (indoor only)

Value

A tibble

Default number of players table

Description

Default number of players table

Usage

dv_default_num_players(data_type = "indoor", style = "default")
dv_default_num_players(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default scouting (type and evaluation for each skill) table

Description

Default scouting (type and evaluation for each skill) table

Usage

dv_default_scouting_table(data_type = "indoor", style = "default")
dv_default_scouting_table(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default setter calls table

Description

Default setter calls table

Usage

dv_default_setter_calls(data_type = "indoor", style = "default")
dv_default_setter_calls(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default skill evaluation table

Description

Default skill evaluation table

Usage

dv_default_skill_evaluations(data_type = "indoor", style = "default")
dv_default_skill_evaluations(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default skill_subtype (type of hit) table

Description

Default skill_subtype (type of hit) table

Usage

dv_default_skill_subtypes(data_type = "indoor", style = "default")
dv_default_skill_subtypes(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default skill_type (tempo) table

Description

Default skill_type (tempo) table

Usage

dv_default_skill_types(data_type = "indoor", style = "default")
dv_default_skill_types(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default special codes table

Description

Default special codes table

Usage

dv_default_special_codes(data_type = "indoor", style = "default")
dv_default_special_codes(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Default winning symbols table

Description

Default winning symbols table

Usage

dv_default_winning_symbols(data_type = "indoor", style = "default")
dv_default_winning_symbols(data_type = "indoor", style = "default")

Arguments

`data_type`	string: "indoor", "beach"
`style`	string: conventions "default", "volleymetrics", "german"

Value

A tibble

Expand scouted rally codes

Description

insert dummy rally rows for score corrections. Note that this will not adjust the setter position in the dummy rows nor insert intermediate setter positions (but will insert one setter position code per team at the start of the returned data frame, if needed)
for a substitution, insert the setter assignment code (*PXX or aPXX) if it was the on-court setter that was substituted
insert the setter position codes at the start of the rally. These should not be inserted on the first point of a set, in that situation they should be in the >LUp codes - so for the first point, make sure that the last_home_setter_position and last_visiting_setter_position are passed as their starting values)

Usage

dv_expand_rally_codes(
  rx,
  last_home_setter_position,
  last_home_setter,
  last_visiting_setter_position,
  last_visiting_setter,
  last_home_team_score,
  last_visiting_team_score,
  keepcols,
  meta,
  rebuild_codes = TRUE,
  do_warn = TRUE
)
dv_expand_rally_codes(
  rx,
  last_home_setter_position,
  last_home_setter,
  last_visiting_setter_position,
  last_visiting_setter,
  last_home_team_score,
  last_visiting_team_score,
  keepcols,
  meta,
  rebuild_codes = TRUE,
  do_warn = TRUE
)

Arguments

`rx`	data.frame: with at least the columns: point_id, code, team ("*" or "a"), point, substitution, timeout, home_setter_position, visiting_setter_position home_team_score, visiting_team_score (scores at the end of the rally) player_out, player_in (substitions) and optional columns: player_number, skill (one-character code), skill_type_code, evaluation_code (used to rebuild the codes before calling `dv_green_codes()`
`last_home_setter_position`, `last_visiting_setter_position`	integer: home and visiting setter positions in the previous rally
`last_home_setter`, `last_visiting_setter`	integer: home and visiting setter jersey numbers in the previous rally
`last_home_team_score`, `last_visiting_team_score`	integer: home and visiting team scores at the end of the previous rally
`keepcols`	character: names of the columns in `rx` to keep, when inserting new rows. Values in these columns will be copied from an adjacent row. If `keepcols` is not provided, a guess will be made
`meta`	list: meta component from a datavolley object
`rebuild_codes`	logical: if `TRUE`, reconstruct the scout code before calling `dv_green_codes()`
`do_warn`	logical: if `FALSE`, suppress warnings issued directly by this function (but warnings generated by downstream code will still occur)

Value

rx potentially with additional rows inserted. Note that the added rows might have fractional point_id values, in which case you will need to renumber all point_ids in the match to integers afterwards

Detect scout file type

Description

Returns the general file type (format), but does not differentiate e.g. indoor from beach. Type is based on the file extension and a minimal check of the contents, but without fully parsing the file. For dv_file_data_type the type is based only on a minimal check of the contents (provided in x)

Usage

dv_file_type(filename, error_on_unknown = FALSE)

dv_file_data_type(x, error_on_unknown = FALSE)
dv_file_type(filename, error_on_unknown = FALSE)

dv_file_data_type(x, error_on_unknown = FALSE)

Arguments

`filename`	character: paths to files. Files that do not exist will be classified as "unknown" type
`error_on_unknown`	logical: if `TRUE` an error will be thrown if an unknown file type is encountered
`x`	character: a character vector with the contents of a scout file

Value

Character vector containing:

"dvw"
"vsm"
"psvb"
"hxml"
"unknown"

Examples

## Not run: 
  library(ovdata)
  dv_file_type(ovdata_example("190301_kats_beds")) ## dvw
  x <- readLines(ovdata_example("190301_kats_beds"), warn = FALSE)
  dv_file_data_type(x)

  dv_file_type(ovdata_example("clickscout")) ## dvw
  dv_file_data_type(readLines(ovdata_example("clickscout"), warn = FALSE))

  dv_file_type(ovdata_example("2017_AVL_mens_HEAT_vs_UTSSU")) ## psvb
  dv_file_data_type(readLines(ovdata_example("2017_AVL_mens_HEAT_vs_UTSSU"), warn = FALSE))

  dv_file_type(tempfile(fileext = ".dvw")) ## unknown (contents not as expected for dvw)
  dv_file_data_type(readLines(tempfile(fileext = ".dvw"))) ## "unknown", with warning


## End(Not run)
## Not run: 
  library(ovdata)
  dv_file_type(ovdata_example("190301_kats_beds")) ## dvw
  x <- readLines(ovdata_example("190301_kats_beds"), warn = FALSE)
  dv_file_data_type(x)

  dv_file_type(ovdata_example("clickscout")) ## dvw
  dv_file_data_type(readLines(ovdata_example("clickscout"), warn = FALSE))

  dv_file_type(ovdata_example("2017_AVL_mens_HEAT_vs_UTSSU")) ## psvb
  dv_file_data_type(readLines(ovdata_example("2017_AVL_mens_HEAT_vs_UTSSU"), warn = FALSE))

  dv_file_type(tempfile(fileext = ".dvw")) ## unknown (contents not as expected for dvw)
  dv_file_data_type(readLines(tempfile(fileext = ".dvw"))) ## "unknown", with warning


## End(Not run)

Extract player metadata by team and jersey number

Description

Extract player metadata by team and jersey number

Usage

dv_get_player_meta(team, number, meta)
dv_get_player_meta(team, number, meta)

Arguments

`team`	character: vector of "*" or "a"
`number`	integer: vector of player jersey numbers
`meta`	list: the `meta` component of a datavolley object, or a datavolley object

Value

A data frame with columns "team" and plus those in meta, sorted to match the inputs team and number

Add green codes to the scouted codes from a rally

Description

Add green codes to the scouted codes from a rally

Usage

dv_green_codes(code, meta, do_warn = TRUE)
dv_green_codes(code, meta, do_warn = TRUE)

Arguments

`code`	character: a character vector of scouted codes for a rally. The codes must be non-compound but need only be the first 6 characters (i.e. up to and including the evaluation_code). The code vector must have a valid point code at the end (the `⁠*p⁠` or `ap` code)
`meta`	list: meta component from a datavolley object
`do_warn`	logical: if `FALSE`, suppress warnings issued directly by this function (but warnings generated by downstream code will still occur)

Value

A character vector of codes. This will be the same as the input code vector, but potentially with additional green code entries (⁠*$$&H#⁠, ⁠*$$&H=⁠, ⁠a$$&H#⁠, ⁠a$$&H=⁠) inserted before the last entry

Insert setting actions for attacks that have not been scouted with sets

Description

This function will insert setting actions prior to attacks, where those attacks do not already have a set scouted. The sets are assigned to the setter on court for that team. It is therefore possible to scout a match, only manually scouting the setting actions where they were made by a player other than the designated setter. The remaining setting actions (made by the designated setter) can be filled in using this function, making the live scouting a little more efficient. Note, however, that automatically-inserted sets do not have the full information that can be included when scouting manually, including setter calls (but see the note on the set_call_table parameter) and location of the set.

Usage

dv_insert_sets(
  x,
  no_set_attacks = c("PP", "P2", "PR"),
  phase_select = "Reception",
  default_set_evaluation = "+",
  attack_rows,
  set_call_table
)
dv_insert_sets(
  x,
  no_set_attacks = c("PP", "P2", "PR"),
  phase_select = "Reception",
  default_set_evaluation = "+",
  attack_rows,
  set_call_table
)

Arguments

`x`	datavolley: datavolley object as returned by `datavolley::dv_read()`
`no_set_attacks`	character: vector of attack codes for which we will not automatically insert sets (e.g. setter tips, overpass attacks)
`phase_select`	character: play phase(s) of attacks to consider. One or more of "Reception", "Transition"
`default_set_evaluation`	string: the default evaluation code for a set (used unless the attack was against 0 or 1 blockers, in which case it gets "#")
`attack_rows`	integer: a vector of row numbers of attacks for which sets should be inserted. Automatically calculated if not provided
`set_call_table`	data.frame: a data.frame with columns `attack_code` and `set_call`. Setter calls will be added to sets associated with attack codes in this list. Note that setter calls from this table will NOT be inserted on sets where the setter did not set the middle hitter (e.g. if the middle ran X1 but the setter set someone else, no "K1" call can be inserted because there is no way of knowing what the middle was running). This gives a biased set of setter call entries that are unlikely to be useful for analysis purposes. It is therefore recommended that you provide `set_call_table` to this function ONLY if you are then going to manually insert setter calls on the remaining rows

Value

A modified copy of x

Examples

## Not run: 
  x <- dv_read(dv_example_file())
  sum(plays(x)$skill == "Set", na.rm = TRUE)
  x <- dv_insert_sets(x)
  sum(plays(x)$skill == "Set", na.rm = TRUE)

## End(Not run)

## Not run: 
  x <- dv_read(dv_example_file())
  sum(plays(x)$skill == "Set", na.rm = TRUE)
  x <- dv_insert_sets(x)
  sum(plays(x)$skill == "Set", na.rm = TRUE)

## End(Not run)

Find attacks for which we could insert missing setting actions

Description

Find attacks for which we could insert missing setting actions

Usage

dv_insert_sets_check(
  x,
  no_set_attacks = c("PP", "P2", "PR"),
  phase_select = "Reception"
)
dv_insert_sets_check(
  x,
  no_set_attacks = c("PP", "P2", "PR"),
  phase_select = "Reception"
)

Arguments

`x`	datavolley: datavolley object as returned by `datavolley::dv_read()`
`no_set_attacks`	character: vector of attack codes for which we will not automatically insert sets (e.g. setter tips, overpass attacks)
`phase_select`	character: play phase(s) of attacks to consider. One or more of "Reception", "Transition"

Value

The row numbers of attacks in the plays component of x, for which sets could be inserted

Insert technical timeouts

Description

Insert technical timeouts

Usage

dv_insert_technical_timeouts(x, at, data_type)
dv_insert_technical_timeouts(x, at, data_type)

Arguments

`x`	datavolleyplays: the plays component of a datavolley object as returned by `dv_read()`
`at`	list: (optional) a two-element list can be supplied, giving the scores at which technical timeouts will be inserted for sets 1–4, and set 5 or golden sets. If not provided, technical timeouts are inserted at points 8 and 16 of sets 1–4 (for indoor files) or when the team scores sum to 21 in sets 1–2 (beach)
`data_type`	string: "indoor" or "beach". If not provided, a guess will be made as to whether `x` is beach or indoor data

Value

A modified copy of x

Update the metadata component of a datavolley object

Description

These elements will be updated:

the played, duration, and score-related columns in x$meta$result
the sets_won and won_match columns in x$meta$teams
the starting positions and substitutions in x$meta$players_h and x$meta$players_v

Usage

dv_update_meta(x)
dv_update_meta(x)

Arguments

`x`	datavolley: as returned by e.g. `datavolley::dv_read()`

Value

A modified copy of x

Define errortype interpretations

Description

Define the interpretation of errortypes associated with events.

Usage

pv_default_errortypes(data_type)
pv_default_errortypes(data_type)

Arguments

data_type

string: "indoor" or "beach"

Value

a tibble with columns "skill", "errortype", and "evaluation"

Examples

pv_default_errortypes("beach")

pv_default_errortypes("beach")

Define eventgrade interpretations

Description

Define the interpretation of eventgrades associated with events.

Usage

pv_default_eventgrades(data_type)
pv_default_eventgrades(data_type)

Arguments

data_type

string: "indoor" or "beach"

Value

a tibble with columns "skill", "eventgrade", "evaluation_code" (the equivalent DataVolley code, if there is one), "evaluation", and "win_loss"

Examples

pv_default_eventgrades("beach")

pv_default_eventgrades("beach")

Lookup tables for Perana Sports database codes

Description

Lookup tables for Perana Sports database codes

Usage

pv_default_eventtypes(data_type)
pv_default_eventtypes(data_type)

Arguments

data_type

string: "indoor" or "beach"

Value

A tibble

Define subevent interpretations

Description

Define the interpretation of subevents associated with events

Usage

pv_default_subevents(data_type)
pv_default_subevents(data_type)

Arguments

data_type

string: "indoor" or "beach"

Value

a tibble with columns "skill", "subevent", and "interpretation"

Examples

pv_default_subevents("beach")

pv_default_subevents("beach")

Define subevent2 interpretations

Description

Define the interpretation of subevents2 associated with events

Usage

pv_default_subevents2(data_type)
pv_default_subevents2(data_type)

Arguments

data_type

string: "indoor" or "beach"

Value

a tibble with columns "skill", "subevent2", and "interpretation"

Examples

pv_default_subevents("beach")

pv_default_subevents("beach")

Parse a ballstring found in Perana Sports files

Description

Parse a ballstring found in Perana Sports files

Usage

pv_parse_ballstring(z, which = "start")
pv_parse_ballstring(z, which = "start")

Arguments

`z`	character: vector of ballstring entries
`which`	string: "start", "mid", or "end". Will be used to name the columns of the returned data.frame

Value

A data.frame with columns start_coordinate_x and start_coordinate_y (or ⁠mid_*⁠ or ⁠end_*⁠, depending on which)

Examples

pv_parse_ballstring(c("51.25, 143.33"))

pv_parse_ballstring(c("51.25, 143.33"))

vscoututils

Description

Utility Functions for Volleyball Scout Files

Author(s)

Maintainer: Ben Raymond [email protected]

Authors:

Adrien Ickowicz

Package 'vscoututils'

Help Index

Create the file_meta component of a datavolley object

Description

Usage

Arguments

Value

Create metadata component of a datavolley object

Description

Usage

Arguments

Value

Examples

Create the attacks metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the comments metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the match metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the match_id metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the more metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the players_h or players_v metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the result metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the sets (setter calls) metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the teams metadata component of a datavolley object

Description

Usage

Arguments

Value

Create the video metadata component of a datavolley object

Description

Usage

Arguments

Value

Decode evaluation codes

Description

Usage

Arguments

Value

Examples

Decode number of players

Description

Usage

Arguments

Value

Examples

Decode skill subtypes

Description

Usage

Arguments

Value

Create the `file_meta` component of a datavolley object

Create the `attacks` metadata component of a datavolley object

Create the `comments` metadata component of a datavolley object

Create the `match` metadata component of a datavolley object

Create the `match_id` metadata component of a datavolley object

Create the `more` metadata component of a datavolley object

Create the `players_h` or `players_v` metadata component of a datavolley object

Create the `result` metadata component of a datavolley object

Create the `sets` (setter calls) metadata component of a datavolley object

Create the `teams` metadata component of a datavolley object

Create the `video` metadata component of a datavolley object