IPL has emerged as one of the most controversial sporting contests in not just cricket but perhaps even sporting history. It has been successful as well but controversy and IPL seem to have become synonyms.
Keeping the cricket perspective aside, IPL has even generated huge interest amidst econs. Lalit Modi in his wildest dreams would not have imagined the impact of IPL on eco research. But then IPL was just a perfect setting for econ research. Things like player auctions, various auction rules, conflict of interest (BCCI official owning one of the IPL teams) etc. is just a very fertile area for econ research.
I came across this paper by Liam Lenten, Wayne Geerling and László Kónya of La Trobe University. They estimate wage premiums (and discounts) for various players:
A range of cross-sectional models are estimated with a view to establishing the factors that determine the valuation of professional athletes in a highly-specialised sport, with an application to cricket’s Indian Premier League (IPL). We distinguish between personal characteristic and playing ability factors, and with respect to the former, between ability in different forms of the sport.
We find a number of interpretable variables that have explanatory power over auction values, while decomposition according to batting and bowling specialisations produces very different results depending on the use of either Test or One-Day International (ODI) variables. There is also possible evidence of inefficient bidding, insomuch that overbidding was somewhat correlated with players with higher realised values.
So it builds this massive model inputting various attributes of a cricketer etc. They compare the model value of a player with the actual price paid by bidders.
Our most compelling findings are as follows: (i) our six models have strong explanatory power for cross-sectional models; (ii) variables from most defined categories appear as significant in most models; (iii) most of our significant estimates are of the anticipated sign. The variables most commonly appearing to have a material bearing on player value are the existence of Indian-player and X-Factor premiums, as well as a positive relation with previous Twenty20 experience (number of games). Furthermore, we interpret the presence of serial correlation as some evidence of overbidding for star players and underbidding for lesser players. Finally, ODI statistics seem to provide more informational content about batsmen than Test statistics, while the inverse is true for bowlers.
Hmm.. ODI is more valuable as T20 is mainly about batting. There are many instances of a freak batting knock changing the game vs a great bowling spell. And bidders usually see ODI record for batters and Test records for bowlers:
contrasting the use of Test versus ODI models, when the full sample is used, it is difficult to separate the models purely on the basis of the measures of fit or information criteria. However, in the player specialisation decompositions, we see an interesting development. The fit and information criteria measures show that for batsmen, ODI stats may be given slightly more weighting in assessment, whereas Test information is given more weighting for bowlers. Such an observation is consistent with the apparent consensus of cricket commentators, who note that the scope for a single bowler to determine the outcome of a Twenty20 match is limited compared to that of a single batsman. Thus, perhaps ODI data is more useful in assessing batters because of the similarity of the formats, whereas assessors fall back on Test data for bowlers as a general indication of true ‘quality’.
Clearly IPL offers fascinating scope for more research:
There is great potential for future work in auction theory to model this auction (with its unique set of attributes) in a formal setting, with a view to considering whether the findings are consistent with those presented here, as well as those from classic works in sports economics, most notably the seminal Fort and Quirk (1995) model. Nevertheless, while not comparable directly with results from any future auctions, the results could be used by the various IPL franchises, along with other information, to approximate ‘fair’ valuations for players in future seasons, to mitigate the incidence of overbidding.
Amazing. IPL actually is a very useful platform to teach insights of auction theory in Indian colleges (and other cricket crazy countries). It helps connect to the overall concept much better.
