AUCTION OF PLAYERS IN INDIAN PREMIER LEAGUE: THE STRATEGIC PERSPECTIVE

16 ABSTRACT AUCTION OF PLAYERS IN INDIAN PREMIER LEAGUE: THE STRATEGIC PERSPECTIVE SONALI BHATTACHARYA*; SHUBHASHEESH BHATTACHARYA** *Associate Professor, Symbiosis Centre for Management and Human Resource Development, Pune-411057, India. **Professor, Symbiosis Institute of International Business, Pune-411057, India. Indian Premier League (IPL), one of the biggest sporting properties of the world is now in its fourth edition. It is considered as one of the best business model of recent times. On 7 th and 8 th January, 2011, it had held auctioning of players for the ten franchisees in the contest, which was televised world over by Sony Max. It is of interest to study how the various teams have strategized their decision on setting the final bidding price of the players according to performance of the players in the previous editions of IPL and other similar formats of the game, and team s own performance in previous seasons. Also, it has been a revelation how personalities of individual players and team leaders can affect the performance of the team. KEYWORDS: Indian Premier League, Auction, Game Theory, Strategy. INTRODUCTION In 2008, Vice President of Board of Control for Cricket in India (BCCI), Lalit Modi partnered with IMG executive Andrew Widblood to initiate India Premier League, a T-20 version of cricket, in which each match was to be of around 3 hours with each competing team facing twenty overs. Teams were auctioned and ownership were won by leading Business tycoons and Bollywood celebrities which ensured pumping in of huge money. The DLF IPL has been rated fourth largest sporting property by Forbes in 2009. The IPL is expected to generate revenue of nearly $2 billion in the period 2008-19, including proceeds from TV rights ($918 million), promotions ($108 million), and franchises ($724 million). Pune and Kochi are the two new franchisees added in the recent fourth Edition of IPL 2011 to the previous eight. The IPL - has four major sources of central revenue. The first is the sale of media rights for the matches, which is likely to fetch the BCCI $1 billion over a 10-year period. The second includes things like title sponsorship of the tournament, licensed merchandise and so on. From the sale of media rights, IPL keep 20% for itself, give out 8% as prize money for the tournament and distribute the remaining 72% evenly between the franchisees. These proportions will be valid till 2012, after which IPL's share goes up in two stages by 2018, with the shares of both prize money and franchisees declining.

17 The second stream - other central revenues - is shared between IPL, franchisees and prize money in the ratio 40:54:6 up to 2017 after which IPL's share will increase to 50%, the franchisees' share will drop to 45% and the remaining 5% will go for prize money. The third major source is, of course, the amounts bid by the franchisees. The fourth stream comes from the revenues generated by the franchisee rights, of which 20% will be given to IPL. IPL is reaching two different kinds of agreements with players when it gets them on board. Under one arrangement called the "firm agreement", the IPL commits a certain fee to the player. If a franchisee bids more for that player in the auction between franchisees for different players, the IPL gets to keep the excess. Under the other - the "basic agreement" the player gets whatever is bid for him. Not surprisingly, most players so far have opted for the "basic agreement". The players are ensured daily allowance of $100 and can have share of bonus and prize money depending upon the performance of the team. King Fisher Airlines has secured the official partnership right with a $0.02 billion deal and Sony Entertainment Television has won the broadcasting right with a staggering payment of $190 crore for ten years. The present paper is intended to discuss the strategies that have been used by the ten franchisee teams during the auctioning of the players in 2011 IPL season and economical, behavioral factors and cricketing attributes which may have affected the decision of the franchisee. GAME THEORY APPROACH TO AUCTION Vickerey (1961) first introduced auction by game theory approach. There are traditionally four types of auction that are used for the allocation of a single item. They are: First-price sealed-bid auctions in which bidders place their bid in a sealed envelope and simultaneously hand them to the auctioneer. The envelopes are opened and the individual with the highest bid wins, paying a price equal to the exact amount that he or she bid. Second-price sealed-bid auctions (Vickrey auctions) in which bidders place their bid in a sealed envelope and simultaneously hand them to the auctioneer. The envelopes are opened and the individual with the highest bid wins, paying a price equal to the exact amount of the second highest bid. Open Ascending-bid auctions (English auctions) in which the price is steadily raised by the auctioneer with bidders dropping out once the price becomes too high. This continues until there remains only one bidder who wins the auction at the current price. Open Descending-bid auctions (Dutch auctions) in which the price starts at a level sufficiently high to deter all bidders and is progressively lowered until a bidder indicates that he is prepared to buy at the current price. He or she wins the auction and pays the price at which they bid. Mc Milan (1992) used English open auction for administering license in Spectrum deal by Federal government. The open auction helps in avoiding winner s curse as would be evident in sealed bid, in which the highest bidder overestimates the value of the entity and often realizes later he has to pay higher price than the actual value. In an open English type auction the bidder

18 has the opportunity to play cautiously and discount its own estimate of the value. In an English auction, a Nash Equilibrium can be reached as a bidder may choose to be in action till the bidding price does not cross his estimated value. If all the bidders follow the same strategy, it will be the weakly dominant strategy. An intelligent bidder may then try to change his strategy. IPL AUCTION BACKGROUND In the IPL Auction there are 10 teams, each team had USD 9,000,000 at its disposal which they could use for buying or retaining at least eleven players that will be required to form their team. Two of the teams: Pune Warrior and Kochi were playing for the first time. Each player was priced at a base price depending upon his performance record and experience by the auctioneer. Bidders in order to buy the players were required to quote a price higher than or equal to the base price. To put it mathematically, Let n i be the number of IPL players to be purchased by the i th team, i = 1, 2,, 9 (since there are nine teams), where n i 11(each team requires eleven players to play a match) Let P ij be the payment to be made to j th player of i th team Then, n i pij USD 9, 000, 000 j 1 (as each team had USD 9,000,000 at their disposal to spend on the auctioning of the players.) Suppose i th team decides utility value to be given to a Player for batting, Bowling (wicket taking capability) and fielding respectively is U Bi, U wi and U Fi such that U U U 1. The Bi Wi Fi values of U Bi and U wi can vary according to whether a player is a batsman or bowler or an all rounder. Let us say ith team decides following utility values Type of player U Bi U wi U Fi Batsman 0.8 0 0.2 Bowler 0.1 0.8 0.2 All Rounder 0.4 0.4 0.2 Then, the team has to decide on the utility they wants to give to a batsman s average and strike rate. Let it be wb1 and wb2 such that wb1+wb2 =1. Similarly utility of a bowler can be based on his bowling average, strike rate and economy rate and a fielder s performance can be measured by the number of catches and stumpings. The players can be ranked based on their percentile rank in batting, bowling and fielding and bidder s assumed utility of each function. Suppose we have a pure batsman has a percentile rank of 0.9 as a batsman and has a percentile rank of 0.4 as fielder then his expected utility can be taken as 0.8 0.9 + 0.2 0.4 = 0.72+ 0.36 = 1.08

19 PROBABLE FACTORS AFFECTING THE DECISION OF THE BIDDERS (1) A bidder may then decide how many batsman and bowler he would require to form his team. As in this shorter form of this game bats man has a bigger role to play let us suppose the bidder may decide he will require seven batsmen and four bowlers. So for him we can assume U U Bi Wi (2) How many players from the top quartile he may like to be in his team. For example he may want to have at least four players from the top quartile. (3) How many players he wants from top quartile and how much money he desires to put in stake for getting these players from the top quartile. For example: he may decide to spend USD 4,000,000 on getting players from top quartile; then if he wants to secure four players from the top quartile, he may likely to spend USD 1,000,000 on each of these players. (4) Whether he wants to create the team of future then he may prefer to select a very young team. (5) If and to what extent he/she may want to give opportunity to local players of the region they are representing, though the minimum number of local players or players from the catchment area team has to accommodate was 4. (6) Similarly, a team can have at most eight foreign players while four players can take the field. SOME OF THE STATISTICS RELATED TO THE IPL AUCTION, 2011 TABLE 1: NUMBER OF PLAYERS FROM EACH COUNTRY WHO WERE SOLD/RETAINED DURING THE AUCTION Indi a Austral ia Banglade sh Englan d Netherla nd Newzeala nd Sri Lanka South Africa West Indies 52 38 1 7 1 7 10 20 3

20 TABLE 2: SUMMARIZATION OF PRICES AT WHICH PLAYERS WERE PURCHASED/ RETAINED BY VARIOUS FRANCHISEE (IN USD) Chen nai Supe r King s Deccan Chargers Delhi Daredevi ls Kings XI Punjab Kolk ata Knig ht Ride rs Koc hi Mu mbai India ns Pune Warr iors Rajas than Roya ls Royal Chall enges Bang alore Avera ge 4813 88.9 491071.4 485294.1 631363.6 7145 83.3 4582 35.3 7100 00 5764 28.6 7743 75 54281 2.5 Standa rd Deviat ion 4939 51.1 373858.2 569362.2 414874 7622 82.6 4223 48.1 6885 03 6420 11.3 5912 18.1 56920 9.9 Coeffi cient Skewn ess 1.41 2008 0.675841 1.782551 0.153705 1.67 5985 1.18 508 0.81 8191 1.65 7552 0.604 487 1.072 869 Numb er of Player s Retain ed/bid succes sfully 18 14 17 11 12 17 12 14 8 16 Some of the highlights of the above statistics are : (i) Kolkata Knight Riders purchased eleven players and is credited to have won the two players securing highest final bidding prices and they along with Mumbai Indians are making highest average payments to its players with the greatest spread. (ii) Kochi, one of the two teams who is participating in the IPL for the first time and Chennai Super king, the most consistent team in the IPL so far, (having won the championship in the last season, and finalist and semi-finalist in the previous two IPL seasons) are statistically proving to be the best strategists in playing the auction. They have now seventeen and eighteen players respectively in their teams and are making the lowest average payments to te players. They have choice of selling later some of their players at higher price.

21 (iii)deccan Chargers with fourteen players in their team are making lowest average payment to its players with low degree of skewness which implies payments have been symmetrically distributed amongst the players. BUILDING OF A PREDICTIVE MODEL FOR THE AUCTION PRICING Rastogi and Deodhar (2009) and Karnik (2010) had used hedonic pricing model to determine auction price of players in IPL league in which they used cricketing attributes of players like performance in one-day internationals and test cricket and as well as non-cricketing attributes such as iconic status of the players in the region they represent, as the variables determining the final bidding price. However, IPL is now four years old and have thrown up new heroes like Yusuf Pathan, R Ashwin, Manish Tiwari, Saurabh Tiwari and Robin Uthappa previously unknown in any other format of the games. Also, local icons are no longer proving to be a determining factor for retaining or picking up players as had been proved in earlier sessions of the game. For example neither Saurav Ganguly was picked up by Kolkata Knight Riders and nor Rahul Dravid was picked up by Royal Challengers Bangalore. So we have considered cricketing attributes of the players in Twenty20 format of the game for building our model. Factors considered are: (i) Batting average implying total number of runs scored by the total number of innings played. (ii) Batting Striking Rate implying numbers runs scored per hundred balls. (iii)bowling Average defined as the total number of runs conceded by the bowlers divided by the number of wickets taken by the bowler, so the lower the average the better. (iv) Bowling strike rate is defined for a bowler as the average number of balls bowled per wicket taken. The lower the strike rate, the more effective a bowler is. (v) Economy Rate of Bowlers is the number of runs scored per over bowled by a Bowler. We also took the interaction variables representing interaction of batting average and fielding(catches and stumpings per match) as well as bowling average and fielding. (vi) Whether a cricketer is a batsman,bowler or all rounder was represented by two dummy variables, dummy 1 and dummy 2 a. where dummy1 takes the value one, if a cricketer is batsman only and zero otherwise. b. Dummy 2 takes the value one, if a cricketer is mainly considered as a bowler and zero otherwise.

22 TABLE 3: CROSS TABULATION OF IPL TEAM AND NUMBER OF CRICKETERS OF EACH TYPE IPL Team Type Total All Rounder Batsman Bowler Chennai Super king 7 6 5 18 Deccan Chargers 3 6 5 14 Delhi Dare Devils 8 6 3 17 Kings XI Punjab 4 3 4 11 Kochi 4 6 7 17 Kolkata Knight Riders 6 3 3 12 Mumbai Indians 6 2 4 12 Pune Warriors 6 4 4 14 Rajasthan Royals 3 1 4 8 Royal Challengers Bangalore 4 8 4 16 Total 51 45 43 139 (vii) We also took a dummy variable to represent the IPL idols as the players who played exceptionally well in the previous IPL seasons. We considered the IPLXI players picked up by Crickinfo after the IPL season 2010 as the IPL idols. Following are the players ( and teams they represented IPL season 2010):

23 Jacques Kallis - Royal Challengers Bangalore Sachin Tendulkar - Mumbai Indians Suresh Raina - Chennai Super Kings Ambati Rayudu - Mumbai Indians TABLE 4: IPL XI BY CRICKINFO (2010) Mahendra Singh Dhoni (captain and wicketkeeper) - Chennai Super Kings Robin Uthappa - Royal Challengers Bangalore Kieron Pollard - Mumbai Indians Ravichandran Ashwin - Chennai Super Kings Anil Kumble - Royal Challengers Bangalore Lasith Maligna - Mumbai Indians Doug Bollinger - Chennai Super Kings Data were collected from www.iplcricket.com, www.cricketfundas.com/ and www.espncricinfo.com/. The Scatter Plot suggested that there exist linear relationship between cricketing attributes and the final bid price of the players. We ignored taking number of wickets or number of scores of 4 s or 6 s as determining factors as had been taken by earlier authors because we felt in this format of the game there are young players who may have little international exposures, but are locally known for their hard hitting of balls, running between wickets or striking of bowls or agility in the field and hence they may have less number of hits of fours or sixes or number of wickets in total and still may be considered good players in shorter version of the game. Following is the Summarization of Statistics used for our study.

24 TABLE 5:SUMMARIZED DATA FOR IPL AUCTION 2011 IPL Team Age Batting Average Batting Strike Rate Bowling Bowling Economy Strike rate Rate Catches Bowling & Average Stumping per innings Chennai Mean 28.5556 21.1750 118.0667 7.5442 19.1182.3639 25.6042 Std. 3.2760 11.3431 27.6921.6747 2.8565.1376 6.8338 Deccan C Mean 26.9286 18.3679 117.4800 7.7240 18.6800.3570 22.4673 Std. 3.7306 10.3028 22.8110 1.1826 4.5217.1826 7.5575 Delhi Da Mean 28.1176 20.8471 121.2676 7.7482 21.3182.2907 27.0400 Std. 3.0183 11.1212 28.1054.6089 5.5139.1413 8.7930 Kings XI Mean 29.6364 20.9455 126.1200 7.3250 18.9875.4314 23.1988 Std. 5.0452 11.3786 12.6932.4009 3.2817.2590 4.9047 Kochi Mean 29.1765 18.5735 112.2718 7.6058 19.7250.3599 25.6425 Std. 5.5027 10.7179 21.1216.6855 5.5151.1284 6.8579 Kolkata Mean 28.7500 20.6667 109.1775 7.4433 19.4000.3885 24.2722 Std. 5.7386 10.1548 35.8655.6374 5.5170.2132 7.7795 Mumbai I Mean 29.0833 23.6975 134.5950 7.6560 23.0600.3684 29.5960 Std. 4.4611 11.0714 21.4751.5833 9.1629.1349 12.5295 Pune War Mean 27.9286 18.8929 120.5200 7.5136 20.8091.4287 26.3645 Std. 4.4283 7.4577 18.4337.7586 7.5336.2197 11.0661

25 Rajastha Mean 31.2500 15.2625 103.0363 7.7986 21.4143.3387 27.1125 Std. 5.8979 11.2098 31.7765 1.2148 7.4616 9.568E- 02 13.8587 Royal Ch Mean 27.8750 19.0525 110.1144 7.5200 27.3088.3946 37.0213 Std. 5.6080 9.3588 24.1219.9730 19.8612.3347 30.0611 Total Mean 28.5755 19.8753 117.4538 7.5900 20.8523.3709 26.6644 Std. 4.6109 10.2770 25.4191.7654 8.0174.1964 12.2259 The best model which was obtained by step-by-step regression analysis is as follow: Auction Price (USD) = 936154.5 + 15835.804 Batting Average + 19340.336 Bowling Strike Rate 137604 Bowling Economy rate. Batting average as expected as positive sign and bowling economy rate and bowling strike rate are having negative sign. The Model has been summarized as follow: TABLE6: COEFFICIENTS OF THE MODELS Model Unstandardized Coefficients B Std. Error Standardized Coefficients Beta T Sig. Collinearity Statistics VIF Tolerance 1 2 (Constant) 283469.545 106024.950 2.674.009 Batting Average 16617.121 5315.627.310 3.126.002 1.000 1.000 (Constant) -15724.710 157641.494 -.100.921 Batting Average 13979.388 5274.807.261 2.650.009.960 1.041 Bowling Strike Rate -16466.826 6563.357 -.247-2.509.014.960 1.041 3 (Constant) 936154.507 503525.949 1.859.066

26 Batting Average Bowling Strike Rate 15835.804 5274.763.295 3.002.003.930 1.075-19340.336 6619.425 -.290-2.922.004.914 1.094 Bowling Economy rate a Dependent Variable: Cost -137603.565 69248.189 -.198-1.987.050.907 1.103 TABLE7: ANOVA TABLE FOR THE MODELS Model Sum of Squares Df Mean Square F Sig. 1 Regression 2577422498545.020 1 2577422498545.020 9.772.002 Residual 24264470320603.90092 263744242615.260 Total a 26841892819148.92093 2 Regression 4147242581712.270 2 2073621290856.135 8.315.000 Residual 22694650237436.65091 249391760850.952 Total b 26841892819148.92093 3 Regression 5101083023522.090 3 1700361007840.698 7.039.000 Residual 21740809795626.83090 241564553284.743 Total c 26841892819148.92093 a Predictors: (Constant), Batting Average b Predictors: (Constant), Batting Average, Bowling Strike Rate c Predictors: (Constant), Batting Average, Bowling Strike Rate, Bowling Economy rate d Dependent Variable: Cost

27 STRATEGIES USED BY INDIVIDUAL IPL TEAMS Before we look into strategies used by various IPL teams let us look into the performance of the eight IPL teams who had been in the IPL seasons of 2008, 2009 and 2010 which played an important role in designing the strategy for picking up the team TABLE 8: STATISTICS OF IPL TEAM PERFORMANCE Team Span Title s Matche s Wo n Los t No Resul t Win % For (r/o) Agains t (r/o) Best Wors t Chennai Super Kings 2008-2010 1 47 26 20 1 56.38 4,75 2 / 574. 4 4,475 / 569.1 Champion s Semifinals Deccan Chargers 2008-2010 1 46 19 27 0 41.29 4,63 7 / 580. 2 4,694 / 582.4 Champion s 8th of 8 Delhi Daredevils 2008-2010 0 44 24 19 1 54.56 4,21 9 / 524. 5 4,330 / 547.0 3 rd 5th of 8 Kings XI Punjab 2008-2010 0 43 21 22 0 48.83 4,25 1 / 531. 1 4,274 / 529.1 Semifinals 8th of 8 Kolkata Knight Riders 2008-2010 0 42 16 24 2 39.74 3,60 2 / 491. 3 3,585 / 459.3 6th of 8 8th of 8 Mumbai Indians 2008-2010 0 44 23 20 1 52.28 3,97 7 / 505. 3 3,898 / 523.1 Runnersup 7th of 8 Rajasthan 2008-1 44 25 18 1 55.81 4,28 9 / 4,213 / Champion 7th of

28 Royals 2010 554. 2 564.2 s 8 Royal Challenger s Bangalore 2008-2010 0 46 21 25 0 45.65 4,26 3 / 587. 3 4,521 / 574.5 Runnersup 7th of 8 (i) CHENNAI SUPER KINGS It has been the most consistent team in earlier seasons of the IPL. It had retained four players before the auction and could win the maximum, three players, from IPL idols list. Their Strategy has been more or less to continue with winning combination. Emphasis has been to quote higher price for players who are good batsmen and fielders, though the team has five speacialist bowlers. Following is the model which best describes the bidding strategy of Chennai Super Kings with an adjusted R square of 0.926 as obtained through step-wise regression. The model can be given as : Auction Price = 56366.404 + 730907.680 (IPL10 IDOLS) + 18357.796 (Interaction of Batting and Fielding). TABLE 9: CHENNAI SUPER KING: REGRESSION MODEL FOR AUCTION Unstandardized Coefficients Standardized Coefficients t Sig. (Constant) 56366.404 56162.759 1.004.345 IPL10 IDOLS 730907.680 87165.703.848 8.385.000 BATFIELD 18357.796 7124.187.261 2.577.033 (ii) DECCAN CHARGERS Deccan Chargers perhaps has been the most inconsistent performer. They had finished bottom of the table in 2008, Champion in 2009 and semifinalist in 2010. Percentage of winnings recorded by the team is higher only to Kolkata Knight Riders and though the number of runs scored by the team is second only to Chennai, runs conceded by them is the highest. The statistically most significant model as obtained by stepwise regression, with an adjusted R-square of 0.96, shows that Age, main effects of Bowling Average, Batting Average, Fielding, and their interactions all proved to be significant factors in their bidding strategy. Average age of the team players is lowest at 26.9286 years and final bidding price of senior players were higher. Their apparent

29 strategy was to get young players who with allround performance. Pragyan Ojha, the player with lowest bowling average in twenty-20 was taken at a final bidding price of USD 500000 and Michael Lumb of England one of top-5 players in Bowling Strike Rate was taken at a bidding price of USD 80000. The model is given as: Final Bidding Price = 1354783 + 76007.9 Age +2812494(Catches & Stumping per innings) +32482.3 (Batting Average)- 43044.5 (Bowling Average). Players with all round performance in batting, bowling and fielding were preferred. Senior players were given premiums. (iii) DELHI DARE DEVILS Delhi Dare Devils performance in the earlier seasons of IPL can at best be described as average. They had finished 4 th in 2008, 3 rd in 2009 and 5 th in 2010. Batting has been there forte. In this season of IPl they had retained Virendra Sehwag, one of the finest batsmen in shorter form of the games and one of the top five players in batting strike rate in twenty-20. Aaron Finch, an Australian player with highest strike rate and Robert Frylinck of Australia one of the top most players with high batting average in twenty-20 format were picked up. The best model for Delhi Dare Devil s strategy as obtained through step-wise regression is given as Auction Price = 690342.7 + 960.087 (Interaction between batting average and batting strike rate) TABLE 10: DELHI DARE DEVILS: REGRESSION MODEL FOR AUCTION BIDDING PRICE Coefficie nts Standard Error t Stat P-value Intercept 690342.7 308101.5 Interaction between batting average and batting strike rate. 960.087 489.0522 2.2406 34 1.9631 59 0.0417 85 0.0698 1 (iv) KING S XI PUNJAB Performance of King s XI Punjab can be described as below par, semifinalist in the first season and finishing at fifth and eighth position in 2009 and 2010. Confidence on its key player Yuvraj Singh seemed to have lost and it neither retained Yuvraj and nor seemed to be keen in winning him in the auction. Batsman, Shaun Marsh of Australia with a Batting average of 45.3, Wicket

30 keeper and Captain Adam Gichrist and Dinesh Karthik are expected to be their prized procession. Final bidding price of the players picked for the team is fairly symmetrically distributed. The most significant model with adjusted R-square of 0.957 shows picking up bowlers with good strike rate and good fielders has been their key strategy. The model is given as: Auction Price = -2279081.123-126019.318 Bowling Strike Rate TABLE 11: KINGS XI PUNJAB: REGRESSION MODEL FOR AUCTION BIDDING PRICE Unstandardized Coefficients Standardized T Sig. Collinearity Coefficients Statistics B Std. Error Beta Tolerance VIF (Constant) -2279081.123 277183.129-8.222.000 Bowling Strike Rate -126019.318 13231.850.-890-9.524.000.996 1.004 (v) KOCHI Though, we could not exactly come out with a statistical model which can explain strategy of incumbent Kochi, but one of their key strategy has been to get key established players of other IPL teams which did not perform up to the mark in previous seasons. It has been able to get Brad Hodge and Brendon McCullum of Australia who have batting average of well above 30 in twenty-20 format at final bidding price of USD 425000 and USD475000 only. Both these players earlier formed part of Kolkata Knight Riders. Other key players will be VVS Laxaman of Australia and Muttiah Muralitharan and Mahela Jayawardene, all of them excellent players but are aged at wrong side of thirty. Another interesting observation is that Kochi team has players with highest average batting strike rate, which also implies focus has been in getting good batsmen and bowlers who are quick between the wickets. Impetus given on getting the two senior players of Srilanka (vi) KOLKATA KNIGHT RIDERS Out of eight teams who have participated in previous three seasons of IPL Kokata Knight Riders performance has been the poorest. They are the only team who have never reached the semifinals and has only 39.74% winning record in the IPL. In 2011, they have intended to give a new look to their team. Former skipper, Saurav Ganguly was not picked up. Similarly, key former players Brendon McCullum, Brad Hodge and Chris Gyale who in 2009 were being considered for captainship were not even considered for bidding. Two of the players who secured highest bidding price IPL Auction 2011, Gautam Gambhir and Yusuf Pathan were won by KKR. Gautam Gambhir got the benefit of winner s curse for having been first player to be auctioned

31 and will be the captain of the side. They have one of the best all rounders, Jacques Kallis, one of the IPLX idols, Yusuf Pathan, a batsman with second highest batting strike rate and twenty year old Jaidev Unadkat as a potentially good bowler. Statistically, only batting strike rate appear as moderately significant predictor of final bidding price with R square of 43% through stepwise regression. The model is as follow has been tabulated below. The Model is given as: Auction Price = -302151 + 9312.671 (Batting Strike Rate) TABLE 12: KOLKATA KNIGHT RIDERS: AUCTION MODEL FOR BIDDING PRICE Coefficients Standard Error t Stat P-value Intercept -302151 691458.3-0.43698 0.671414 Batting Strike Rate 9312.671 6041.561 1.541435 0.154237 (vii) MUMBAI INDIANS Mumbai Indians who was Runners up in 2010 season had like Chennai Superking retained four of its star performers before the bidding. They are Harbhajan Singh, Sachin Tendulkar, Lasith Malinga and Kieron Pollard. Three of these players also formed part of IPLX idols. Statistically most significant model with an adjusted R-square of 87% show good bowlers and batsmen with good batting average and fielding as well as age came out to significant factors. The model has been tabulated as bellow TABLE 13: MUMBAI INDIANS: AUCTION MODEL FOR BIDDING PRICE Coefficients Standard Error t Stat P-value Intercept 6425589 1729279 3.715763 0.02055 Age -169111 40769.39-4.148 0.014283 Bowling average -202236 42105.28-4.80311 0.008629 Bowling Economy rate -126643 61545.88-2.0577 0.108736 Catches & Stumping per innings -7888177 2245701-3.51257 0.024615 Batting and Fielding 329807.8 95553.56 3.451549 0.026018

32 Auction Price = 6425589-169111 Age + -202236 Bowling average -126643 Bowling Economy rate -7888177 Catches & Stumping per innings + 329807.8 Batting and Fielding (viii) PUNE WARRIORS Pune warriors who were to be playing for the first time in IPL 2011 has played well in the auction. They could grab Yuvraj Singh from Kings XI at final bid price of USD 1800000 and IPL Idol 2010 player Robin Uthappa at USD 2100000. Key strategy has been to pick up players with good batting average. The most significant model with an adjusted R-square of 53% is tabulated below: TABLE 14: PUNE WARRIORS: REGRESSION MODEL FOR AUCTION BIDDING PRICE Coefficients Standard Error t Stat P-value Intercept 39489.78 360775 0.109458 0.91481 IPL idols 1500220 507591.8 2.955563 0.013079 Batting Average 22748.29 18190.61 1.250552 0.237045 Auction Price = 39489.78 + 1500220 IPL idols + 22748.29 Batting Average (ix) RAJASTHAN ROYAL Rajasthan Royal s performance has been topsy-turvy in IPL. They spend the least in IPL 2008 auction. A young team of unknown local players under the inspired leadership of Shane Warne went on to become the Champion. Their performance was motivated by the famous Oscar nominated film Laagan whose storyline was based on similar theme and on the same locality. In 2009, they however finished at the bottom of table, and reached semifinal in 2010. They did not seem to have the desire to deviate from their once successful model. They had retained Shane Warne and Shane Watson at USD 1800000 and USD 1300000. Only six more players were bid successfully in the auction. Other players is expected to be hired from local areas. Their strength is bowling with only specialist Batsman, Rahul Dravid grabbed from Royal Challengers Bangalore. The average age of the players are more than thirty and average batting average is lower than the other teams. The final average bidding price of the players are much higher than as predicted by the general model. (x) ROYAL CHALLENGERS BANGALORE Royal challengers Bangalore has finished at the bottom of the table in 2008 and went onto become runners up in 2009 and got third position in 2010. They have relied more on talented Indians, with Virat Kohli retained with a price of USD 1800000 and projected as the skipper of the team. The most significant model explaining biding price strategy of Bangalore has adjusted R-square of 0.87 as given below:

33 TABLE 15: ROYAL CHALLENGERS BANGALORE: REGRESSION MODEL FOR BIDDING PRICE Coefficients Standard Error t Stat P-value Intercept -1210779 318509.3-3.80139 0.002936 Bowling Strike Rate -18478.4 3002.163-6.155031 7.16E-05 Catches & Stumping per innings 1208228 188448.5 6.411449 5E-05 batting strike rate 12381.59 3936.8 3.14509 0.009323 batting average 17786 10548.84 1.68606 0.119906 Auction Price = -1210779-18478.4 Bowling Strike Rate + 1208228 Catches & Stumping per innings + 12381.59 Batting Strike Rate +17786 Batting average SOME INTERESTING ASPECTS OF IPL (i) (ii) Vijay Mallaya, franchisee owner of Royal Challenger Bangalore (RCB) and owner of UB group had clearly stated in 2008 that his objective of being part of the IPL business was to promote his alcohol brand, which otherwise is banned to be promoted directly in India. Much attention was not paid in the composition of the team. The situation worsened due to sacking of team manager, Charu Sharma and pressure being created on the team captain, Rahul Dravid to resign. The result was RCB finishing at the bottom of the table. Their strategy of giving a new look to the team in 2009, with emphasis on youth and good fielders clicked under the leadership of Anil Kumble and they reached the final in 2009 after losing four consecutive matches. Anil Kumble s leadership style was of leading by example. RCB also reached the semifinal in 2010. In the first IPL in 2008 the Emerging Media Group, who owns Rajasthan Royals, was the lowest bidder and paid $65 million to become the least expensive franchise in the eightteam IPL. They didn t have high profile players in their team and nor had any accomplished celebrity as brand ambassador. What they accomplished was by identifying young talents through a Cricket Star Reality Show, nurturing them through proper coaching and focusing on their objective of winning. Darren Berry, director of coaching with the Rajasthan Royals had said in an interview that each of the players was assigned a specific role to play during a match and they focused on their role and worked as a team talking to each other in times of crisis. They clung together as a team: when their bagman lost his mother but did not leave the tournament, all the players wore black bands in his mother s respect throughout the tournament. Many prodigal players like Yusuf Pathan, Robin Uthappa who will now be representing other team are discoveries of RR.

34 (iii) Now let us look into how some of the players who were not picked up by any of the franchisees in the auction. The top players who were left unsold in the auction with their base prices are as follow: Sourav Ganguly ($400,000) Brian Lara ($400,000) Chris Gayle ($400,000) James Anderson ($400,000) Graeme Swann ($400,000) Luke Wright ($400,000) Herschelle Gibbs ($200,000) Graham Manou ($50,000) Matt Prior ($200,000) Mark Boucher ($200,000) Dilhara Fernando ($100,000) Ajanta Mendis ($200,000) Chamara Kapugedera ($100,000) Tamim Iqbal ($100,000) Saurav Ganguly, aged 38 years has a good enough batting average of 27.07 and was captain of Kolkata Knight Riders (KKR) for the previous three seasons but did not find any takers. Though he recorded great performances in flashes in IPL but most of the time he seemed to stick to the wicket at a low strike rate not letting other younger players to take the crease and increase the pace of scoring runs. His batting strike rate of 109.09 is just same as the average batting strike rate of present KKR team and lower than average strike rate of all other teams except Rajasthan Royals (which is yet to build its complete team). Saurav Ganguly s bowling average is 24.48, bowling economy rate is 7.73, bowling strike rate 19 and catche/stumpings per match is 0.362, which is again comparable with averages of most other teams as can be seen from table 11.. His age, batting strike rate and the fact that his leadership could not win even a semi-final berths for KKR in any of the previous seasons worked against him. Brian Lara, aged 42 years has an experience of only 3 matches in twenty-20 format with batting average of 33 and strike rate of 115.11. His age and inexperience in this format of the game, resulted in none of the teams showing confidence in him. Similarly, Chris Gayle aged 32 years who represented KKR in

35 earlier seasons has batting average of 30 and strike rate 140.16 higher than most players auctioned and also is a useful part-time bowler but was not picked perhaps due to his rash play and showing impatience when the team needed him to stay in the wicket for a while. Also he participated in only nine of the matches out of fourteen which KKR played in the third edition which is evidence of his casual approach in the field. Another surprise omission was Herschelle Gibbs a wicket-keeper batsman with batting strike rate of 125.09 and batting average of 26.05 in twenty-20 and catches/stumpings of 0.51. He was instrumental in Deccan Charger s winning the league in the second season but did not perform well with Chargers in other seasons and has also fallen out his national team, South Africa. His age at 37 puts him in the wrong side of thirty. Also, his former team, Deccan chargers has opted this time for a very young team, (infact the average age of the players is least as compare to other teams) and emphasized in getting good bowlers. Another factor which remotely may have worked against him could be his being caught in microphone in making racial comment against section of the crowd in a match in Pakistan which resulted him being banned by ICC from playing couple of matches in 2007. English Players like James Anderson, Graemme Swann, Luke Wight might not have been picked up due to the apprehension that they may not fetch big money as they have domestic cricketing commitments to keep during the IPL seasons. Paul Collingwood has reportedly said that England players were less attractive in the auction because they are expected to play in at least one firstclass fixture before the first Test of the 2011 summer, against Sri Lanka at Lord's on 26 May meaning they will not be available for the latter stages of the IPL, which will run from 8 April to 22 May. Australian Player, Graham Manou s performance in twenty-20 has been rather unimpressive with a batting average of 10.37. Dihara Fernando of Srilanka who played for Mumbai Indians in earlier seasons has only one notable bowling figure of 4 for 18 again Royal Challengers Bangalore which won him the Man of the Match title. Similarly, Chamara Kapugedera fate was affected by his inconsistencies in performance in IPL 2009 season for Chennai Superking which found him no takers in the next two seasons. Ajantha Mendis had to pay for having been picked for the 2010 season by the low performing team KKR, which did not bring into limelight his performance. Tamim Iqbal of Bangladesh was not picked up for reasons unknown even after Sachin Tendulkar had reportedly advised Mumbai Indians to bid for him. (iv) Andrew Symonds and Harbhajan Singh will both be playing for Mumbai Indians (MI) in the IPL season IV. They are the players, who were caught in verbal racial argument during an international match between by India and Australia some years back and were reprimanded by International Cricket Council. Yet, MI represents city of Mumbai which did not allow two foreign women to perform as cheer leaders during a match in the first IPL season. It is strange how a game of cricket can mend feeling of cross-cultural differences. The presence of the two players, both excellent all-rounders in their own rights will add to the entertainment value. The performance of the KKR team in 2009 edition in South Africa was marred by charges of racial discrimination within team members( http://cricket.zeenews.com/fullstory.aspx?nid=20167).

36 REFERENCES Karnik A (2010).Valuing Cricketers Using Hedonic Price Models, Journal of Sports Economics, 11, 4, 456-469 Vickrey, William (1960). Counterspeculation, Auctions and Competitive Sealed Tenders, Journal of Finance, 16(1), 8-37. McMillan, John (1992). Games, Strategies, and Managers, New York, Oxford University Press. Rastogi, S.K., and Deodhar, S.K. (2009). Player Pricing and Valuation of Cricketing Attributes, Vikalpa, 34(2), 15-23. www.iplcricket.com www.cricketfundas.com www.espncricinfo.com/