Name: VCT PACIFIC 2023
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

VCT PACIFIC 2023

VALORANT

Valorant, developed and published by Riot Games, has rapidly emerged as a leading esports game on a global scale. Since its release in the summer of 2020, this first-person shooter has garnered immense popularity, captivating a vast player base. With millions of daily participants hailing from various corners of the world, Valorant has captivated both individual players and teams alike. The competitive scene is bustling with events where players and teams from around the globe vie for glory and strive to establish themselves as the ultimate champions of Valorant.

DATA

The data divided by 5 main csv such as 1v1, counter_kill (clutch rate), eco (economy rate), pick_ban (Map & Pick Ban Rate) and stats (player perfomance). The data itself gathered from vlr.gg scraped using python and combined into 5 main csv and 3 other csv for supporting other analysis with it

Tables

Agent Id Img

@kaggle.kierru_vctpacific_2023.agent_id_img

4.09 kB
20 rows
4 columns

CREATE TABLE agent_id_img (
  "agent_id" BIGINT,
  "agent" VARCHAR,
  "role" VARCHAR,
  "agent_url" VARCHAR
);

Counter Kill

@kaggle.kierru_vctpacific_2023.counter_kill

21.01 kB
1,330 rows
20 columns

CREATE TABLE counter_kill (
  "player" VARCHAR,
  "team" VARCHAR,
  "n_2k" BIGINT  -- 2k,
  "n_3k" BIGINT  -- 3k,
  "n_4k" BIGINT  -- 4k,
  "n_5k" BIGINT  -- 5k,
  "n_1v1" BIGINT  -- 1v1,
  "n_1v2" BIGINT  -- 1v2,
  "n_1v3" BIGINT  -- 1v3,
  "n_1v4" BIGINT  -- 1v4,
  "n_1v5" BIGINT  -- 1v5,
  "agent" VARCHAR,
  "map" VARCHAR,
  "tourney_type" VARCHAR,
  "game_id" BIGINT,
  "match_id" BIGINT,
  "role_agent" VARCHAR,
  "total_round" BIGINT,
  "ot" VARCHAR,
  "win_lose" VARCHAR
);

Eco

@kaggle.kierru_vctpacific_2023.eco

15.25 kB
266 rows
17 columns

CREATE TABLE eco (
  "team" VARCHAR,
  "pistol_win" DOUBLE,
  "eco_round" DOUBLE,
  "eco_win" DOUBLE,
  "semi_eco_round" DOUBLE,
  "semi_eco_win" DOUBLE,
  "semi_buy_round" DOUBLE,
  "semi_buy_win" DOUBLE,
  "buy_round" DOUBLE,
  "buy_win" DOUBLE,
  "game_id" DOUBLE,
  "tourney_type" VARCHAR,
  "map" VARCHAR,
  "match_id" DOUBLE,
  "total_round" BIGINT,
  "ot" VARCHAR,
  "win_lose" VARCHAR
);

N 1v1

@kaggle.kierru_vctpacific_2023.n_1v1

31.68 kB
5,256 rows
15 columns

CREATE TABLE n_1v1 (
  "player" VARCHAR,
  "opponent" VARCHAR,
  "team" VARCHAR,
  "opponent_team" VARCHAR,
  "kill" DOUBLE,
  "death" DOUBLE,
  "tourney_type" VARCHAR,
  "match_id" DOUBLE,
  "map" VARCHAR,
  "game_id" DOUBLE,
  "total_round" DOUBLE,
  "ot" VARCHAR,
  "win_lose" VARCHAR,
  "agent" VARCHAR,
  "role_agent" VARCHAR
);

Pick Ban

@kaggle.kierru_vctpacific_2023.pick_ban

4.99 kB
324 rows
5 columns

CREATE TABLE pick_ban (
  "team" VARCHAR,
  "pb_phase" VARCHAR,
  "map" VARCHAR,
  "tourney_type" VARCHAR,
  "match_id" BIGINT
);

Player Id Img

@kaggle.kierru_vctpacific_2023.player_id_img

6 kB
62 rows
5 columns

CREATE TABLE player_id_img (
  "team" VARCHAR,
  "player_id" BIGINT,
  "player" VARCHAR,
  "region" VARCHAR,
  "player_img" VARCHAR
);

Stats

@kaggle.kierru_vctpacific_2023.stats

40.51 kB
1,330 rows
27 columns

CREATE TABLE stats (
  "player_name" VARCHAR,
  "team" VARCHAR,
  "opponent" VARCHAR,
  "rating" DOUBLE,
  "acs" BIGINT,
  "kill" BIGINT,
  "death" BIGINT,
  "assist" BIGINT,
  "kast_percent" VARCHAR,
  "adr" BIGINT,
  "hs_percent" VARCHAR,
  "first_kill" BIGINT,
  "first_death" BIGINT,
  "agent" VARCHAR,
  "map" VARCHAR,
  "score_team" BIGINT,
  "score_opp" BIGINT,
  "score_t" BIGINT,
  "score_ct" BIGINT,
  "total_round" BIGINT,
  "ot" VARCHAR,
  "win_lose" VARCHAR,
  "tourney_type" VARCHAR,
  "game_id" BIGINT,
  "player_id" BIGINT,
  "match_id" BIGINT,
  "role_agent" VARCHAR
);

Team Id Img

@kaggle.kierru_vctpacific_2023.team_id_img

7.73 kB
10 rows
10 columns

CREATE TABLE team_id_img (
  "team" VARCHAR,
  "full_team" VARCHAR,
  "region" VARCHAR,
  "w" BIGINT,
  "l" BIGINT,
  "map" VARCHAR,
  "rnd" VARCHAR,
  "rnd_diff" BIGINT,
  "img_url" VARCHAR,
  "team_id" BIGINT
);