Dataset: VCT PACIFIC 2023

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

Eco

@kaggle.kierru_vctpacific_2023.eco

14.9 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
);

Agent Id Img

@kaggle.kierru_vctpacific_2023.agent_id_img

4 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

20.52 KB
1330 rows
20 columns


CREATE TABLE counter_kill (
  "player" VARCHAR,
  "team" VARCHAR,
  "n_2k" BIGINT,
  "n_3k" BIGINT,
  "n_4k" BIGINT,
  "n_5k" BIGINT,
  "n_1v1" BIGINT,
  "n_1v2" BIGINT,
  "n_1v3" BIGINT,
  "n_1v4" BIGINT,
  "n_1v5" BIGINT,
  "agent" VARCHAR,
  "map" VARCHAR,
  "tourney_type" VARCHAR,
  "game_id" BIGINT,
  "match_id" BIGINT,
  "role_agent" VARCHAR,
  "total_round" BIGINT,
  "ot" VARCHAR,
  "win_lose" VARCHAR
);

Team Id Img

@kaggle.kierru_vctpacific_2023.team_id_img

7.54 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
);

Player Id Img

@kaggle.kierru_vctpacific_2023.player_id_img

5.86 KB
62 rows
5 columns


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

N 1v1

@kaggle.kierru_vctpacific_2023.n_1v1

30.93 KB
5256 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
);

Stats

@kaggle.kierru_vctpacific_2023.stats

39.56 KB
1330 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
);

Pick Ban

@kaggle.kierru_vctpacific_2023.pick_ban

4.87 KB
324 rows
5 columns


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