IPL is a lab for experimenting with fair price discovery systems. So Ravichandran Ashwin’s recent warning against reinstating the right to match rule should be taken seriously

Before we plot the high-stakes connection between the Indian Premier League and market logic, let’s look at an observation from Peter Cramton, an economist who has done extensive work on auction design.

He wrote in the European Economic Review in 1998: “With neither theory nor experiments providing definitive results, it is easy to conclude that which auction format is best is an empirical matter. How one would go about answering this empirical question is difficult at best, since rarely do we see multiple formats being used in easily comparable settings.”

This is where the IPL and Ravichandran Ashwin come in. The IPL is a high-stakes laboratory for experimenting with auction design – a rare luxury that India’s governments, public sector units or bankruptcy courts do not have. And the spinner, who has 310 wickets in 324 T20 matches, recently spoke out loudly against the possible reinstatement of the right-to-match (RTM) card at the next IPL auction. He believes the RTM system undervalues the player.

Before we weigh the logic behind Ashwin’s claim, let’s define the key terms. At the IPL, players are traded in an ascending price auction – the teams place bids in increments. The winner is the team willing to pay the most, with no one else willing to outbid it.

In economic literature, RTM is also known as the right of first refusal. Introduced at the 2018 IPL mega auction, the rule allows teams to keep up to five players from the previous season by using the player retention rule before the auction or RTM at the auction. If they match the highest price bid at the auction, the RTM allows a team to reacquire a player who they did not retain before the auction. A maximum of three retentions or three RTMs were permitted, subject to the overall limit of five.

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Why teams want RTM

Recent reports indicate that teams want to bring back RTM in the 2025 auction. Rebuilding an entire team defies logic. So teams would like to retain as many core players as possible. At the least, they would prefer a mix of retention and RTM.

Some preferential treatment is observed in other sports leagues, too. An example would be to let the team that performed the worst in the previous season pick the first player from the available pool in the ensuing season. This allows everyone to build a competitive team. But this idea cannot be extended to RTM.

At the IPL auction, the team interested in exercising RTM puts in a bid at the base price of the player and then watches the bidding unfold between other teams. They would behave differently if they had to participate actively in the auction for a player who was not part of their team. In the latter case, the team reveals the maximum price it would pay for a player; under RTM, the true valuation of the player as ascertained by the team exercising the RTM is not necessarily revealed.

Consider the case of Faf du Plessis in 2018. He had played for Chennai Super Kings, who matched the highest bid of Rs 1.6 crore and retained him. In 2022, he was bought by Royal Challengers Bangalore for Rs 7 crore. The IPL 2022 mega auction did not have RTM. It was probably a combination of recent form, the desire for RCB to have him as their captain and the absence of RTM that contributed to his higher valuation.

A mathematical model formalising this line of thinking will throw up the downside of RTM for players. RTM can discourage bidders from bidding actively. A team will expect that winning against the RTM holder is more expensive. It brings in a big element of uncertainty while building the ideal team.

Also, there is the notion of a team overpaying – beating the RTM holder essentially means that the right holder does not value the player as much as the winner does. Empirical evidence from other contexts suggest that RTM can create a situation where the right holder pays less for a player than what they would have if they had participated in open bidding for the player.

RTM with additional features

The first option is to have a rule requiring the team to exercise RTM to top the highest bid at the auction by the incremental bid in that slab. For example, if the highest bid for a player is Rs 10 crore, then the team exercising RTM will have to pay a certain percentage over this amount. Depending on the industry and nature of the contract, top-ups over the winning bid is usually in the region of 5-25 per cent.

The second option is to fix the maximum number of retentions. In earlier auctions, the rules permitted payment of Rs 16, 12, 8 and 6 crore to the first, second, third and fourth choice players, respectively.

Suppose for arguments sake, now eight players can be retained and IPL rules do not specify a retention price slab but allow the team to negotiate with the players. Thus each team would have the right of first offer (RoFO) to the player – which the player can accept or decline. The offer price is recorded by the IPL authorities but not disclosed if the player declines. If the player accepts, he is retained; else, he goes to the auction.

Here, the player takes the risk of being unsold or sold at a lower price. If the highest bid received by the player is lower than the amount offered by his original team, then the original team has the option to match this price and retain him. Under this scenario, the player is aware of the principle of ‘no risk, no gain’.

All these transactions have to respect the overarching guideline for all teams – to not exceed the total budget and to fulfill the minimum and maximum number of players any team needs to have on its roster.

If there was no ambiguity over these rules, a staggering 2,500-odd research articles would not have been written on RoFR since 2020. That’s why Ashwin’s concern cannot be dismissed. And why those designing government auctions should stay tuned to the IPL debate. 

(Views are personal)

S Chandrasekhar

Professor, Indira Gandhi Institute of Development Research

Shivangi Chandel

Associate Professor, O P Jindal Global University