MARKET SIZE AND WINNING: HOW LARGE IS THE BIG-CITY ADVANTAGE IN SPANISH

FOOTBALL?

José M. Sánchez

Pablo Castellanos

Jesús A. Dopico

University of Corunna

2

PRESENTATION STRUCTURE

• MOTIVATION OF THE RESEARCH

• METHODOLOGICAL APPROACH

• DISCUSSION OF THE RESULTS

• CONCLUDING REMARKS

3

MOTIVATION OF THE RESEARCH

• To find an answer to the following questions:

– Do big-cities teams have some inherent advantage due to the markets they serve?

– How large is this advantage?

– Does this advantage impede to get an acceptable level of competitive balance?

• Special relevance of these questions for Spanish Football League:

– Spanish framework:

– Professional teams competing in First and Second Division are located in areas with very different drawing potential

– Spanish League is a win (utility) maximizing league (the large-market teams are more dominant in win maximizing leagues than in profit maximizing ones)

– Opened players’ market

– These features arise the possibility of a strong unbalance between large and small markets teams

4

METHODOLOGICAL APPROACH

• Theoretical framework:

– Relationship between market size and sports performance: derived under both the profit maximization and win (utility) maximization models (Rottemberg, 1956; Sloane, 1971, Scully, 1974 and Kesenne, 2006):

• Main hypothesis:– Given that teams are located in areas with different drawing potential, profit and utility

incentives operating in a free competitive labor market will lead to a situation in which, on average, strong-drawing areas have stronger teams, and weak-drawing areas have weaker teams.

MARKET SIZE

TALENT

REVENUE

ATTENDANCE

PLAYING SUCCESS

5

EMPIRICAL APPROACH

• Reference: Bradbury (2007)

– Case of study: MLB

– Conclusion: Although big-market teams may have an advantage over small-market teams, the advantage appears to be slight and virtually meaningless

• Our regression analysis:

– Dependent variable (Y): playing success• Proxy of playing success: long-term sports performance index (seasons from

1995 until 2007)

– Independent variable (X): local market size• Proxy of local market size: adjusted provincial population

6

Teams sorted by their local market size (X)

Team Population Team Population 1 Real Madrid 2,711.69 32 Spórting 531.50 2 At. Madrid 2,711.69 33 Oviedo 531.50 3 Barcelona 2,402.96 34 Valladolid 498.09 4 Espanyol/Español 2,402.96 35 Ponferradina 488.75 5 Valencia 2,216.29 36 Villarreal 484.57 6 Rayo Vallecano 1,807.79 37 Recreativo de Huelva 462.58 7 Getafe 1,807.79 38 Xerez/Jerez Dvo. 372.16 8 Leganés 1,807.79 39 Cádiz 372.16 9 Terrassa 1,601.98 40 Algeciras 372.16 10 Málaga C. F. 1,287.02 41 Compostela 365.34 11 Athletic Bilbao 1,122.64 42 Rácing Ferrol 365.34 12 Deportivo Coruña 1,096.03 43 Albacete 364.84 13 Celta 903.76 44 Lleida/Lérida 362.21 14 Betis 863.80 45 Burgos 348.93 15 Sevilla 863.80 46 Salamanca 345.61 16 Zaragoza 861.86 47 Ourense/Orense 338.45 17 Mallorca 841.67 48 Pontevedra 301.25 18 Tenerife 806.80 49 Las Palmas 295.89 19 Córdoba 761.66 50 Universidad Las Palmas 295.89 20 Levante 738.76 51 Vecindario 295.89 21 Elche 730.96 52 Alavés 286.39 22 Hércules 730.96 53 Logroñés 276.70 23 Real Sociedad 673.56 54 U. D. Almería 268.37 24 Jaén 643.82 55 Polidep. Ejido 268.37 25 Gimnàstic/Nàstic 609.67 56 Eibar 224.52 26 Murcia 598.82 57 Extremadura 218.29 27 Lorca Dva. 598.82 58 Mérida 218.29 28 Écija 575.87 59 Badajoz 218.29 29 Osasuna 555.83 60 Castellón 161.52 30 Toledo 541.38 61 Numancia 90.72 31 Rácing Santander 535.13

7

Teams sorted by their observed performance (Y)

Team Observ. Perf. Team Observ. Perf. 1 Barcelona 96.63 32 Eibar 23.41 2 Real Madrid 96.03 33 Extremadura 23.02 3 Valencia 91.67 34 Murcia 20.04 4 Deportivo Coruña 88.49 35 Xerez/Jerez Dvo. 19.25 5 Athletic Bilbao 79.76 36 Mérida 19.05 6 Celta 77.58 37 Elche 17.06 7 Betis 76.98 38 Badajoz 16.27 8 Real Sociedad 75.99 39 Lleida/Lérida 16.07 9 Espanyol/Español 75.79 40 Cádiz 15.87 10 At. Madrid 75.20 41 Leganés 15.08 11 Mallorca 72.82 42 U. D. Almería 14.09 12 Zaragoza 72.02 43 Hércules 13.69 13 Sevilla 70.24 44 Gimnàstic/Nàstic 12.50 14 Rácing Santander 64.48 45 Logroñés 10.91 15 Valladolid 64.48 46 Córdoba 10.32 16 Villarreal 63.89 47 Polidep. Ejido 9.92 17 Alavés 53.77 48 Toledo 9.33 18 Osasuna 52.98 49 Rácing Ferrol 6.75 19 Málaga C. F. 49.40 50 Terrassa 4.96 20 Tenerife 47.82 51 Castellón 3.97 21 Spórting 40.48 52 Lorca Dva. 3.97 22 Rayo Vallecano 40.08 53 Jaén 3.37 23 Albacete 39.68 54 Ourense/Orense 2.78 24 Oviedo 35.32 55 Écija 1.79 25 Salamanca 35.12 56 Burgos 1.39 26 Recreativo de Huelva 33.13 57 Ponferradina 0.60 27 Numancia 32.54 58 Universidad Las Palmas 0.60 28 Levante 32.14 59 Algeciras 0.20 29 Las Palmas 30.95 60 Pontevedra 0.20 30 Getafe 27.58 61 Vecindario 0.20 31 Compostela 25.60

8

Statistics

Y X Valid 61 61 N

Missing 0 0 Mean 34.6767 761.2813 Median 25.5952 535.1310 Std. Deviation 29.6139 655.3994 Skewness .6191 1.7272 Kurtosis -.9358 2.1889 Minimum .1984 90.7170 Maximum 96.6270 2711.6920

9

REGRESSION ANALYSIS(Linear specification, WLS estimation)

Variable Coefficient S. D. t-Statistic p-value Constant 12.2102 3.2249 3.786 0.00036*** Population 0.0278 0.0028 9.929 <0.00001***

R2 = 0.6256 Corrected R2 = 0.6193 Sum of squared residuals = 131.006 S. D. of residuals = 1.4901 Akaike Info Criterion (AIC) = 223.737 Schwarz Info Criterion (BIC) = 227.959 Hannan-Quinn Info Criterion (HQC) = 225.391

10

METRICS à la BRADBURY

• PREDICTED PERFORMANCE: Sports performance that the teams should have based solely on their local market size

– Predicted performance = 12.2102 + 0.0278·Population

• POPULATION-ADJUSTED PERFORMANCE: The estimated sports performance of Spanish Football teams due to factors other than local market size

– Pop.- adj. performance = Observed perfomance – 0.0278·Population

• PERFORMANCE ABOVE/BELOW PREDICTED: The difference between observed (actual) sports performance and predicted performance

11

Teams sorted by their predicted performance

Team Predict. Perf. Team Predict. Perf. 1 Real Madrid 87.64 32 Spórting 26.99 2 At. Madrid 87.64 33 Oviedo 26.99 3 Barcelona 79.05 34 Valladolid 26.07 4 Espanyol/Español 79.05 35 Ponferradina 25.81 5 Valencia 73.86 36 Villarreal 25.69 6 Rayo Vallecano 62.50 37 Recreativo de Huelva 25.08 7 Getafe 62.50 38 Xerez/Jerez Dvo. 22.56 8 Leganés 62.50 39 Cádiz 22.56 9 Terrassa 56.77 40 Algeciras 22.56 10 Málaga C. F. 48.01 41 Compostela 22.37 11 Athletic Bilbao 43.44 42 Rácing Ferrol 22.37 12 Deportivo Coruña 42.70 43 Albacete 22.36 13 Celta 37.35 44 Lleida/Lérida 22.29 14 Betis 36.24 45 Burgos 21.92 15 Sevilla 36.24 46 Salamanca 21.82 16 Zaragoza 36.18 47 Ourense/Orense 21.62 17 Mallorca 35.62 48 Pontevedra 20.59 18 Tenerife 34.65 49 Las Palmas 20.44 19 Córdoba 33.40 50 Universidad Las Palmas 20.44 20 Levante 32.76 51 Vecindario 20.44 21 Elche 32.54 52 Alavés 20.18 22 Hércules 32.54 53 Logroñés 19.91 23 Real Sociedad 30.95 54 U. D. Almería 19.68 24 Jaén 30.12 55 Polidep. Ejido 19.68 25 Gimnàstic/Nàstic 29.17 56 Eibar 18.46 26 Murcia 28.87 57 Extremadura 18.28 27 Lorca Dva. 28.87 58 Mérida 18.28 28 Écija 28.23 59 Badajoz 18.28 29 Osasuna 27.67 60 Castellón 16.70 30 Toledo 27.27 61 Numancia 14.73 31 Rácing Santander 27.10

12

Teams sorted by their performance above predicted

Team Perf. above predicted Team Perf. above predicted 1 Deportivo Coruña 45.79 32 Espanyol/Español -3.26 2 Real Sociedad 45.05 33 Xerez/Jerez Dvo. -3.32 3 Betis 40.75 34 U. D. Almería -5.59 4 Celta 40.23 35 Lleida/Lérida -6.21 5 Valladolid 38.42 36 Cádiz -6.69 6 Villarreal 38.20 37 Murcia -8.83 7 Rácing Santander 37.39 38 Logroñés -8.99 8 Mallorca 37.20 39 Polidep. Ejido -9.75 9 Athletic Bilbao 36.32 40 At. Madrid -12.44 10 Zaragoza 35.84 41 Castellón -12.73 11 Sevilla 34.00 42 Elche -15.48 12 Alavés 33.59 43 Rácing Ferrol -15.63 13 Osasuna 25.30 44 Gimnàstic/Nàstic -16.67 14 Valencia 17.81 45 Toledo -17.94 15 Numancia 17.81 46 Ourense/Orense -18.85 16 Barcelona 17.58 47 Hércules -18.85 17 Albacete 17.32 48 Universidad Las Palmas -19.85 18 Spórting 13.48 49 Vecindario -20.24 19 Salamanca 13.30 50 Pontevedra -20.39 20 Tenerife 13.17 51 Burgos -20.53 21 Las Palmas 10.51 52 Algeciras -22.36 22 Real Madrid 8.39 53 Rayo Vallecano -22.42 23 Oviedo 8.32 54 Córdoba -23.08 24 Recreativo de Huelva 8.06 55 Lorca Dva. -24.90 25 Eibar 4.96 56 Ponferradina -25.21 26 Extremadura 4.73 57 Écija -26.44 27 Compostela 3.22 58 Jaén -26.75 28 Málaga C. F. 1.39 59 Getafe -34.92 29 Mérida 0.77 60 Leganés -47.42 30 Levante -0.62 61 Terrassa -51.81 31 Badajoz -2.01

13

DISCUSSION OF RESULTS (i)• Data about predicted performance allow us to estimate threshold values (the minimum values required to achieve

a particular success level if the sports performance were determined solely by the team local market size)

– These figures confirm that factors other than local market size (management, coaching…) play a meaningful role in sports success, because we can identify teams located in areas with population below those thresholds and that, however, are able to reach levels of success above predicted.

• Data about observed performance:

– Dominance of ‘large market’ teams, that is, teams located in a large city combined with a large fan base (i.e. Barcelona, R. Madrid, Valencia).

• Comparison between predicted performance and observed performance:

– There are several teams with similar predicted performance and with very different observed performance (i.e. Real Sociedad-Jaén, Mallorca-Elche, Betis-Zaragoza…). Even we can find teams that exhibit higher observed performance than others in spite of having a lower predicted perfomance (i.e. Deportivo-Real Madrid, Ath. Bilbao-At. Madrid…)

SUCCESS LEVEL LOCAL MARKET SIZE THRESHOLD VALUE (in thousands)

League Championship 3,156 UEFA Champions League appearance 2,899 UEFA Cup appearance 2,728 Keep on First Division 1,787

14

DISCUSSION OF RESULTS (ii)

– Comparison between observed performance and population-adjusted performance:

• Without their big-market advantage, teams located in largest markets (Real Madrid, Barcelona and Valencia) would exhibit a substantial reduction in their playing success.

• Teams with the best adjusted-population performance don’t serve the largest markets; however, over the last decade these teams have attained some playing success (Deportivo, Real Sociedad, Betis, Villarreal…)

– Comparing the population-adjusted with observed performance for every team over the past decade, it is possible to measure how well teams performed above/below the levels predicted by local market size

• Group A: Big markets with a relative poor performance (At. Madrid, Español, Hércules, Rayo Vallecano, Córdoba…)

• Group B: Big markets with a relative good performance (Barcelona, Real Madrid, Valencia, Ath. Bilbao, Betis…)

• Group C: Small markets with a relative poor performance not attributable to market size (Algeciras, Badajoz, Logroñés, Pontevedra, Castellón…)

• Group D: Small markets with a relative good performance (R. Huelva, Osasuna, Alavés, Salamanca, Eibar…)

15

CONCLUDING REMARKS

– The empirical evidence derived from the present research allows us to gain a greater understanding of the influence of local market size on Spanish football teams’ playing success.

– Big-market teams have a clear advantage over small-market teams; however, the market size-sports performance relationship seems to be less strong than the theoretically anticipated one.

– The big-city advantage is meaningful but doesn’t impede that teams that are not located in areas with the largest market size have at least periodic opportunities of success.

– Any prolonged under/over performance by specific clubs might be the result of factors other than market size.

– The results suggest that the long-run Spanish League viability is not in serious danger because of the observed dominance by a group of very few teams.