Dataset: TATA IPL Auction 2025 Sold Players Dataset

About this Dataset

TATA IPL Auction 2025 Sold Players Dataset

The TATA IPL 2025 auction saw some big moves, with teams strengthening their squads for the upcoming season. From seasoned internationals to uncapped talents, the auction was filled with excitement, with each franchise investing in players who can make a significant impact on the field.

In this comprehensive list, you can explore:

Top-Price Signings:

The marquee players of the auction, including those with the highest winning bids. These star players, like Jos Buttler, Shreyas Iyer, and Rishabh Pant, are expected to lead their teams to victory with their world-class skills.

Capped vs. Uncapped Players:

We’ve separated the capped (players with international experience) from uncapped (new faces or domestic talents) players. The auction revealed a strong mix of established internationals and promising uncapped players, providing each team a blend of experience and youthful energy.

Team-Specific Purchases:

Explore how each team built its squad by securing players across various categories like batting, bowling, and all-rounders. From explosive hitters to game-changing bowlers, see how teams like Mumbai Indians, Rajasthan Royals, and Gujarat Titans filled their gaps and bolstered their squads.

Auction Dynamics:

Understanding the strategies behind the bids – which teams went all in for big names and which ones took a more calculated approach, picking up rising talents at a reasonable price.

Future Stars:

A special look at the uncapped players who are making their way into the IPL spotlight. These rising stars, though inexperienced at the international level, bring immense promise with their performances in domestic cricket.

The All-Rounder Factor:

All-rounders have always been in high demand in the IPL, and the 2025 auction reflected this. Players like Marcus Stoinis, Mitchell Marsh, and Krunal Pandya went for hefty amounts, adding versatility and depth to their teams. All-rounders are crucial for balancing a team’s playing XI, and these acquisitions are set to play pivotal roles in both batting and bowling.

Breaking Auction Records:

The IPL 2025 auction witnessed new records being set for the highest-ever bids for uncapped players. The competition for some players was fierce, and the increasing value of homegrown talent proved that IPL franchises are keen to nurture their domestic pool while securing valuable international players.

Tables

Csk Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.csk_players_list

4.62 KB
20 rows
5 columns


CREATE TABLE csk_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Dc Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.dc_players_list

4.58 KB
19 rows
5 columns


CREATE TABLE dc_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Gt Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.gt_players_list

4.63 KB
20 rows
5 columns


CREATE TABLE gt_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Kkr Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.kkr_players_list

4.47 KB
15 rows
5 columns


CREATE TABLE kkr_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Lsg Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.lsg_players_list

4.54 KB
19 rows
5 columns


CREATE TABLE lsg_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Mi Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.mi_players_list

4.58 KB
18 rows
5 columns


CREATE TABLE mi_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Pbks Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.pbks_players_list

4.69 KB
23 rows
5 columns


CREATE TABLE pbks_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Rcb Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.rcb_players_list

4.61 KB
19 rows
5 columns


CREATE TABLE rcb_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Rr Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.rr_players_list

4.49 KB
14 rows
5 columns


CREATE TABLE rr_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);

Srh Players List

@kaggle.bhadramohit_tata_ipl_auction_2025_sold_players_dataset.srh_players_list

4.47 KB
15 rows
5 columns


CREATE TABLE srh_players_list (
  "sr_no" BIGINT,
  "player" VARCHAR,
  "base_price" BIGINT,
  "winning_bid" BIGINT,
  "capped_uncapped" VARCHAR
);