Economc predcon of spor performances from he Bejng Olympcs o he 2010 FIFA World Cup n Souh Afrca: he noon of surprsng sporng oucomes Wladmr Andreff Madelene Andreff To ce hs verson: Wladmr Andreff Madelene Andreff. Economc predcon of spor performances from he Bejng Olympcs o he 2010 FIFA World Cup n Souh Afrca: he noon of surprsng sporng oucomes. Placdo Rodrguez Sefan Késenne Ruud Konng. The Economcs of Compeve Spors Edward Elgar pp.185-215 2015 978 1 78347 475 2. <10.4337/9781783474769.00018>. <halshs-01244495> HAL Id: halshs-01244495 hps://halshs.archves-ouveres.fr/halshs-01244495 Submed on 15 Dec 2015 HAL s a mul-dscplnary open access archve for he depos and dssemnaon of scenfc research documens wheher hey are publshed or no. The documens may come from eachng and research nsuons n France or abroad or from publc or prvae research ceners. L archve ouvere plurdscplnare HAL es desnée au dépô e à la dffuson de documens scenfques de nveau recherche publés ou non émanan des éablssemens d ensegnemen e de recherche franças ou érangers des laboraores publcs ou prvés.
In: Placdo Rodrguez Sephan Késenne & Ruud Konng eds. The Economcs of Compeve Spor Edward Elgar Chelenham 2015 (forhcomng): CHAPTER 11 ECONOMIC PREDICTION OF SPORT PERFORMANCES FROM BEIJING OLYMPICS TO 2010 FIFA WORLD CUP IN SOUTH AFRICA: THE NOTION OF SURPRISING SPORTING OUTCOME Wladmr Andreff * & Madelene Andreff ** 1
* Professor Emerus a he Unversy of Pars 1 Panhéon Sorbonne Honorary Presden of he Inernaonal Assocaon of Spor Economss andreff@clubnerne.fr ** Former Senor Lecurer n Sascs and Economercs a he Unversy of Marnela-Vallée madandreff@gmal.com Inroducon The dsrbuon of medal wns across naons a Summer Olympcs s exremely uneven beween developed and developng counres: he former abou 40 naons concenrae from wo-hrds o hree-quarers of medal wns whle he laer - abou 160 naons oban from one-quarer o one-hrd of medals oal. Ths observaon suggess a lkely relaonshp beween a naon s Olympc spor performance and s level of economc developmen. Indeed has been emprcally verfed ha he number of medals a counry wns a Summer Olympcs sgnfcanly depends on s populaon and GDP per nhaban (Andreff 2001). Thus n a sense he number of medal wns a he Olympcs can be regarded as an addonal ndex of economc developmen jus lke he leracy rae he percenage of chldren aendng prmary school healh expendures per nhaban moraly or morbdy raes. On he oher hand he level of economc developmen and populaon could be used as realsc predcors of Olympc performances. The only spor mega-even whch can compare o Summer Olympcs n erms of fan aendance TV vewng and economc mpac s FIFA soccer World Cup. Nobody knows wheher a naon s level of economc developmen may mpac on s spor performance a soccer World Cup snce such an ssue remans unheeded n he leraure so far whaever one refers o spors economcs or developmen economcs. One movaon of hs arcle s o provde a frs nsgh no hs ssue and he oher way round check wheher a naon s performance a soccer World Cup may have any sense n reflecng s economc developmen. Economerc esmaon of how 2
much sgnfcan are he economc deermnans of medal wns by each parcpang naon s now que usual. Our core research queson s: would a model based on populaon and GDP per capa as deermnans perform as well n explanng soccer World Cup oucomes as s used o perform wh Olympc medal wns? Snce he esmaed model has provded a good predcon of medal wns a he nex Olympcs would be able o predc FIFA World Cup oucomes wh a smlar success? Afer a bref look a modellng and predcng Summer Olympcs medal dsrbuon (1) a slghly mproved model s esmaed and hen mplemened o predc how many medals each naon would have obaned a he 2008 Olympcs (2). The predcon s compared o acual oucomes observed n Bejng (3). A nex sep s o undersand why a smlar predcon model has no ye emerged wh regards o FIFA World Cup: a major reason s ha he soccer World Cup oucome s raher unpredcable due o a number of surprses surprsng oucomes durng s fnal ournamen (4). Thus adapng he model of Olympc medals predcon o FIFA World Cup requres ha some fooball-specfc or fooballsc varables be nroduced alongsde wh economc varables (5). Such emended model s esmaed on he bass of pas FIFA World Cup resuls (6) and hen used o predc he semfnalss a he 2010 World Cup n Souh Afrca (7). Snce he predcons regardng he las soccer World Cup do no exhb good resuls performance n he laer s meanngless as an ndex of economc developmen. Moreover hs opens an avenue for furher research abou he noon of surprsng sporng oucome and s mercs (8). The concluson emphaszes ha economc predcon of spor performances s o be aken wh a pnch of sal. 1. Economc deermnans of Olympc medals 3
More han hry sudes have looked for he deermnans of Olympc performances snce 1956 combnng soco-economc varables wh weaher nuron moraly n he ahlee s home naon proen consumpon relgon colonal pas newspapers supply urban populaon lfe expecancy geographcal surface area mlary expendures judcal sysem and hose spor dscplnes augh a school. A wdespread assumpon across spors economss who have parcpaed o hese sudes s ha a naon s Olympc performance mus be deermned by s endowmen n and he level of developmen of - economc and human resources capured hrough GDP per capa and populaon. Noce ha an ncrease n he number of medal wns by one counry logcally s an equvalen decrease n medals won by all oher parcpang naons. Therefore f one wans o explan he Olympc performance of one specfc naon one has o ake no accoun all oher parcpang naons whn he overall consran of he dsrbued medals oal. Durng he cold war perod anoher sgnfcan varable emerged: a naon s polcal regme. The frs Wesern work aempng o explan medal wns by naons polcal regme (Ball 1972) rggered a Sove rejonder (Novkov and Maxmenko 1972) boh dfferenang capals from communs regmes. The frs wo economerc analyses of Olympc Games (Grmes e al. 1974; Levne 1974) exhbed ha when regressng medal wns on GDP per capa and populaon communs counres were oulers: hey were wnnng more medals han her level of economc developmen and populaon were lkely o predc. A las varable has been nroduced namely snce Clarke (2000) whch s he nfluence on medal wns of beng he Olympcs hosng counry.e. a sor of home advanage. The hos gans more medals han oherwse due o bg crowds of naonal fans a sronger naonal ahlees movaon 4
when compeng on her home ground and beng adaped o local weaher and no red by a long pre-games ravel. Economerc mehodology has developed n more recen sudes such as an ordered Log model (Andreff 2001) a Prob model (Nevll e al. 2002) or an ordered Prob model (Johnson and Al 2004) n whch a quadrac specfcaon n GDP per capa s employed o capure a posulaed nvered U-shaped relaonshp meanng ha hgher levels of GDP per capa have a posve mpac on medal wns hough decreasng afer some hreshold. The mos quoed reference s Bernard and Busse (2004) whose model has been wdely used n furher sudes. In hs Tob model mplemened for esmang and predcng Olympc performances he wo major ndependen varables - GDP per capa and populaon are aken on board wh hree dummes ha capure a hos counry effec he nfluence of belongng o Sove-ype and oher communs (and pos-sove and pos-communs afer 1990) counres as agans beng a capals marke economy. 2. Predcng Olympc medals dsrbuon n Bejng 2008 Sarng from Bernard and Busse afer a few emendaons a more specfed model has been elaboraed on (Andreff e al. 2008). The dependen varable s each naon s number of medal wns 1 : M. The frs wo ndependen varables are GDP per capa and populaon. Conrary o Bernard and Busse s no assumed here ha preparng an Olympc eam s meless and hen ndependen varables are four years lagged: GDP per nhaban (Y/N) -4 n 1995 purchasng power pary dollars and populaon N -4 (World Bank daa). The assumpon s ha four years are 5
requred o buld up ran prepare and make an Olympc eam he mos compeve n due me. A Hos dummy s used o capure a home advanage. Bernard and Busse dvde he world no communs regmes and capals marke economes whch obvously fs wh he cold war perod. Snce hen hs s oo crude wh regards o pos-communs ranson economes: he spors economy secor has dfferenaed a lo across former socals counres durng her nsuonal ransformaon process (Poupaux and Andreff 2007). Such dfferenaon has ranslaed no a scaered effcency n wnnng Olympc medals afer 1991 (Rahke and Woek 2008). A frs emendaon o Bernard and Busse s model s nroduced here wh a classfcaon ha dsngushes Cenral Easern European counres (CEEC) whch have lef a Sove-ype planned economy n 1989 or 1990 and ransformed no a democrac polcal regme runnng a marke economy: Bulgara he Czech Republc Esona Hungary Lava Lhuana Poland Romana Slovaka (and Czechoslovaka unl he 1993 spl) Slovena and he GDR (unl German reunfcaon n 1990). Anoher commonaly o hs group s ha hese counres have joned he European Unon. A second counry group (TRANS) gahers new ndependen saes (former Sove republcs) and some former CMEA member saes whch have sared up a smlar process of ranson bu are laggng behnd he CEECs n erms of ransformaon no a democrac regme and are sallng on he pah oward a marke economy: Armena Azerbajan Belarus Georga Kazakhsan Kyrgyzsan Moldova Mongola Russa Tajksan Turkmensan Ukrane Uzbeksan and Venam. None of hem has joned he EU so far or has really an opon o do so. The nex wo groups have no been Sove regmes properly speakng n he pas alhough hey have been boh communs regmes and planned economes. In he frs one (NSCOM) we sample 6
hose counres whch have sared up a ranson process n he 1990s: Albana Bosna-Herzegovna Chna Croaa Laos Macedona Monenegro and Serba (and he former FSR Yugoslava before he 1991 break up). Two counres have no ye engaged no a democrac ransformaon and a marke economy: Cuba and Norh Korea. They mus be consdered as sll communs regmes (COM). All oher counres are regarded as capals marke economes (CAPME) he reference group n our esmaons. Table 1 exhbs uneven medal dsrbuon by polcal regme. Inser Table 1 abou here Beyond Bernard and Busse a varable supposed o capure he nfluence on Olympc performance of a specfc sporng culure n a regon s nroduced. For example Afghan (and oher Mddle Eas) lades are no used o have much spor parcpaon or aend spor shows even less o be enrolled n an Olympc eam. Resulng from hese culural dspares some naons are more specalsed n one specfc spor dscplne such as wegh-lfng n Bulgara Turkey Armena and he Balkans marahon and long dsance run n Ehopa and Kenya cyclng n Belgum and he Neherlands able enns judo and maral ars n varous Asan counres sprn n Carbbean slands and he U.S. and so on. I s no easy o desgn a varable ha would exacly capure such regonal sporng culure dfferences 2 bu s assumed ha regonal dummes may reflec hem. The world s dvded no nne sporng culure regons: AFS sub-sahara Afrcan counres; AFN: Norh Afrcan counres; NAM Norh Amerca; LSA Lan and Souh Amerca; EAST Easern Europe; WEU Wesern Europe (aken as he reference regon n our esmaon); OCE Oceana; MNE Mddle Eas; and ASI (oher) Asan counres. Inser Table 2 abou here 7
8 A frs specfcaon s smply à la Bernard and Busse bu wh a dfferenly defned polcal regme varable wh a censored Tob model snce a non neglgble number of counres ha parcpae o he Olympcs do no wn any medal. Therefore a zero value of he M dependen varable does no mean ha a counry has no parcpaed and we work ou a smple Tob no a Tob 2 (wh a wo sage Heckman procedure) 3. Dummes es wheher he Olympc year s sgnfcan akng 2004 as he reference. These dummes come ou o be non sgnfcan. In a second specfcaon a daa panel Tob s adoped n order o ake no accoun unobserved heerogeney whose es s sgnfcan 4 and hus esmaon wh random effecs s oped for. Daa 5 encompass all Summer Olympcs from 1976 o 2004 excep 1980 and 1984 whch are skpped ou due o boycos whch have dsored he medal dsrbuon per counry. Therefore a frs specfcaon (1) s: q q q p p p Year gme Re Polcal Hos N Y N c M 4 4 * ln ln where ε ~ N (0σ 2 ) M observaon s defned by 0 0 0 M f M f M M A second specfcaon (2) adds he above descrbed dummy sandng for sporng culure regons (Regon r ): r r r p p p u gons Re gme Re Polcal Hos N Y N c M 4 4 * ln ln where ε ~ N (0σ 2 ε) and u ~ N (0σ 2 u) M observaon s defned by 0 0 0 M f M f M M
A hrd specfcaon (3) conans an addonal varable M -4 on he rgh-hand sde jus lke n Bernard and Busse who do no commen why hey proceed n such a way. The nerpreaon here s ha wnnng medals a prevous Olympcs maers for an Olympc naonal eam whch usually expecs and aemps o acheve a leas as well as four years ago. Such neral effec s all he more relevan for hose naons eager o wn as many medals as possble ha s for mos naons wnnng more han zero medals. The hrd specfcaon (3) s used o predc he medal dsrbuon a Bejng Olympcs: M * c ln N ln 4 Y N 4 Hos p p Polcal Re gme p r r Regons r M 4 where ε ~ N (0σ 2 ) M observaon s defned by M M 0 f f M M 0 0 Inser Table 3 abou here All esmaons delver sgnfcan resuls (Table 3). In he frs one all coeffcens are posve and sgnfcan a a 1% hreshold excep for year dummes. I s confrmed once agan ha medal wns are deermned by GDP per capa populaon and a hos counry effec. Polcal regme s also an explanaory varable. The second esmaon all n all exhbs he same resuls. The coeffcens of regonal sporng culure are sgnfcan excep for Lan Amerca an area where he Norh Amercan sporng culure may have permeaed namely hrough Carbbean counres and Mexco (classfed n NAM). 9
Snce Wesern Europe s he reference a sgnfcan coeffcen wh a posve (negave) sgn means ha a regon performs relavely beer (worse) han Wesern Europe n erms of medal wns. Sub-Sahara Afrca Norh Amerca and Oceana perform beer. Though a lle b surprsng for Sub-Sahara Afrcan counres snce hey are among he leas developed n he world (excep Souh Afrca) hs s due o a few counres whch are exremely specalsed n one spor dscplne where hey are capable of a non neglgble number of medal wns such as Ehopa and Kenya n long dsance runs. Wh negave coeffcens Norh Afrca Asa Easern Europe and Mddle Eas perform worse. I s no surprsng for Norh Afrca and he Mddle Eas due o some spor pracce resrcons n he culure of varous counres. In he case of Asa only few counres are capable of a sgnfcan number of medal wns (Chna boh Koreas Mongola) gven her GDP per capa. Snce Easern European counres are known as oulers - over-performers (gven her GDP per capa and populaon) a negave coeffcen resuls from he Polcal Regme already capurng her over-performance. The poolng esmaon 6 of Model 3 may suffer from endogeney snce he resuls may be based by a correlaon beween he lagged endogenous varable and he error erm. Ths ssue s reaed wh a GMM dynamc panel (Arellano and Bond 1991) a echnque whch provdes esmaed coeffcens and predcons ha are robus and close o hose esmaed wh a Tob model. Our predcons show up n Table 4 for a counry sub-sample 7. Inser Table 4 abou here The predced frs-rank wnner s he Uned Saes followed by Russa and Chna whch benefs from home advanage. Mos developed marke economes are 10
predced o be among he major medal wnners ogeher wh some pos-communs ranson counres. 3. Predcons and acual resuls: medal wns are raher predcable Comparng predcons wh he acual medal dsrbuon ha has come ou from Bejng Olympcs he model performs well. I has provded good predcons: 70% of he observed resuls are encompassed n our predced confdence nerval (among hose 189 counres for whch daa were avalable and compuable). If predcon s assessed as accepable when he error margn s no bgger han a wo medal dfference beween prevson and acual oucome hen he model correcly predcs 88% of all Bejng resuls. The remanng unforeseen 12% accoun for surprses unexpecedly surprsng oucomes. The model correcly predcs he frs en medal wnners excep Japan (nsead of Ukrane) msses four ou of he frs weny wnners hough wh a slghly dfferen rankng. However he mos neresng s when model predcon s clearly wrong ha s bascally for 23 naons meanng ha he fve varables (plus he neral varable) have no capured some core explanaon of he Olympcs oucome. Forunaely economss are no capable o predc all Olympc resuls oherwse why sll convene he Games? The major surprse n he acual oucomes compared o model predcons s he que bgger han expeced medal wns by he Chnese eam all publshed predcons have been wrong n hs respec. The hos counry effec n Chna has been underesmaed. Possbly Chnese performance has also been boosed by 11
some undeeced dopng 8. A second surprse s he underperformance of he Russan Olympc eam he wors snce he cold war. Vladmr Pun convened he hghes decson makers of Russan spor o command a new Olympc polcy lkely o avod a repeaed dsaser a he 2012 London Olympcs. In he same ven some oher ranson counres namely Romana have won fewer medals han predced n Bejng. The curren sae of resrucurng he whole spors secor n hese counres has no been suffcenly capured by our refned polcal regme varable. The las hree sgnfcan surprses are Grea Bran Jamaca and Kenya he laer beng he only wo developng counres among he frs weny medal wnners. Early preparaon of a super-compeve eam for he 2012 London Olympcs may have been he cause for hgher han predced oucomes of he Brsh eam as s suggesed by Maenng and Wellebrock (2008) who have nroduced a nex Olympcs hos counry varable n her predcon. Grea Bran s medals concenraon n cyclng (12 medals) may race back agan o undeeced dopng and/or deep specalsaon of a naon n one spor dscplne. The laer s he mos lkely explanaon for Jamacan medals 9 concenraed n sprn and Kenyan medals n long dsance runs. Though we have aken no accoun such specalsaon hrough our lagged M -4 varable Kenya had won 7 medals and Jamaca 5 n he same dscplnes a Ahens Olympcs - he nera capured wh hs varable reveals o be nsuffcen. 4. Predcon of FIFA World Cup sem-fnalss: why s so hard? The economcs of FIFA World Cup oucome s much less developed han he economc approach o Olympc medal wns. There are wo ways of explanng 12
nernaonal soccer successes n he leraure. The mos common mehod s o explan FIFA pons and rankng (he FIFA/Coca Cola World Rankng for all naonal fooball eams) a one pon n me (Hoffmann e al. 2002b; Houson e al. 2002; Macmllan and Smh 2007; Leeds and Markova Leeds 2009; Yamamura 2009). The second one consss n explanng a naon s success n FIFA World Cup over me. To he bes of our knowledge economc deermnans of he soccer World Cup oucome have only been ouched hree mes n he leraure so far. From he hree papers appears ha surprsng oucomes are he mos common occurrence. Torgler (2004) aemps explanng he deermnans of he 2002 soccer World Cup oucome. The dependen varable s a dummy ha measures wheher a eam wns a game or no n he World Cup fnal ournamen. Explanaory varables are no economc. A varable capures he srengh of a eam hrough s FIFA rankng and he posve nfluence on success of beng he hosng eam. A second se of varables s nroduced regardng he performance of a eam durng a game: shos on goal fouls corner kcks free kcks off sdes cauons expulsons acual playng me (based on ball possesson). The major resul s ha hgher FIFA rankng leads o hgher probably of wnnng a game: a one place mprovemen n world rankng ncreases a eam s probably of wnnng by approxmaely 1% bu hs resul s no always sgnfcan. Hgher number of shos on goal drves hgher probably of wnnng; havng a referee from he same regon has a posve mpac on he probably of wnnng a game bu hs effec s no sascally sgnfcan 10. A predcon model of FIFA World Cup oucome s due o Paul and Mra (2008). I s no based on economc varables eher. The auhors remnd ha n he pas four FIFA World Cup ournamens 1994 o 2006 he op eam n FIFA rankng never won excep Brazl n 1994. However hey es he relevance of he las FIFA rankng 13
publshed before he World Cup fnal ournamen as a benchmark o evaluae eams performance. In a Prob model he dependen varable s a dummy ha measures wheher a eam wns (1 = wn 0 oherwse) a game or no. The man explanaory varable s FIFA rankng wh conrollng for he number of goals scored by each eam and he number of yellow and red cards. A second OLS esng consders he scored goal dfference as he dependen varable and FIFA rank dfference s he man ndependen varable wh conrollng for goals scored he number of yellow and red cards he number of corner kcks he number of fouls he percenage of ball possesson and mach aendance. Hgher FIFA rankng s sgnfcanly assocaed wh hgher probably of wnnng a game. Hgher-ranked eams score more goals. A more surprsng resul s ha hough a hgher number of yellow or red cards are less lkely o wn a game n 2002 and 2006 eams wh more yellow cards were more lkely o wn a game (and eams wh more red cards n he 1998 Cup as well). Oher surprses are ha more corner kcks and more ball possesson are assocaed wh losng a game. Overall hgher-ranked favoures have he wnnng rend n her favour bu here s a number of unexpeced mach oucomes. Ths s why s so hard o esmae deermnans and make predcons. Monks and Husch (2009) es wheher FIFA World Cup forma may lead o a slghly rgged cones or a leas wheher may favour ceran eams n parcular he hos counry. In he ournamen hsory only seven eams have ever won he World Cup (Brazl 5 mes Ialy 4 Germany 3 Argenna and Uruguay 2 England and France 1). Of he 18 ournamens held o dae he hos has won sx mes. The auhors es he mpac of seedng home connen and hosng on FIFA Cup oucome from 1982 o 2006. The dependen varable s a naonal eam s World Cup fnal sandng (from he wnner down o he 32h among he qualfed accordng o her performance durng 14
he fnal ournamen) and s regressed on a eam s FIFA rank before he World Cup a dummy varable for beng op seeded a hos counry dummy and a dummy varable f he World Cup s beng played on a eam s own connen. Ex ane rank s posve and sgnfcan n deermnng a eam s fnal sandng. Beng op seeded resuls n an ncrease n fnal sandng of approxmaely 5 places and he home connen advanage s approxmaely 2.8 places (bu no sgnfcan). Boh effecs probably overlap wh he hos counry varable (he hos counry s op seeded by defnon) whch provdes 3 places beer han he expeced fnal sandng bu he resul s no sgnfcan. Rank beng he hos counry and playng on one s home connen 11 deermne advancemen n he ournamen o eher he quarerfnals or sem-fnals. 5. Adapng he Olympcs medal model o FIFA World Cup oucome From he above-menoned sudes s clear ha explanng FIFA World Cup oucome s much harder han fndng n soco-economc varables he deermnans of Olympcs medal wns for dfferen reasons. Soccer s a spor dscplne whch s more wdespread n some counres (for nsance Lan Amercan counres) han ohers whaever her level of economc developmen he sze of her populaon and her democrac or auocrac regme. Such specfcy requres he nroducon of some fooballsc varables n he esmaon. To he conrary he Olympcs cover so many spor dscplnes ha overall economc developmen of a naon affecs overall naon s sporng oucome beyond dspares n performance across dfferen spors hus GDP and populaon are germane o sand for a sgnfcan share of he deermnans. The number of surprsng oucomes s much hgher wh he soccer 15
World Cup han wh he Olympcs also because n one case he surprses peran o jus one spor dscplne whereas wh he Olympcs here are unexpeced (surprsng) medal wns n some spors ha may on average compensae surprsng medal losses n oher spors for he Olympc eams from bg (populaon) and rch (GDP per capa) naons. Moreover he wo coness have dfferen formas. In mos Olympcs dscplnes 12 afer a prelmnary knock-ou selecon egh ahlees reman n conenon for he fnals and he frs hree bes are rewarded wh (gold slver and bronze) medals durng he fnals. Thus s no exremely rcky o buld up an esmaon of he deermnans of medal wns - he frs hree ranked ahlees (naons). I s more complex wh FIFA World Cup fnal ournamen snce hs cones combnes a round robn frs sage before he 1/8 h fnals and hen a knock-ou second sage from he 1/8 h fnals on. The uncerany of oucome markedly ncreases from he frs o he second sage (Monks and Husch 2009) and hus he mpac of economc varables mgh well dlue n he course of some knock-ou games (hus he surprsng oucome). Ths lays ground for he choce of dependen varable o have as much comparable as possble wh medal wns: s chosen as he four naons makng for he sem-fnals (Semfn) of a soccer World Cup fnal ournamen. The deermnans of beng one of he four hghes-ranked eams n he fnal ournamen are looked for and hs faclaes usng he same esmaon model as he one explanng Olympcs medal wns. The four hghes-ranked are he wnner he fnals and wo losng semfnalss whch play a rankng game he day before he fnal. Gven he dependen varable (makng for he sem-fnals = 1; oherwse 0) a Prob model s esmaed. All naonal eams whch have parcpaed o he sem-fnals are exhbed n Appendx 1 wh her cumulave parcpaon from he frs 1930 World Cup up o 16
2006. Reanng he sem-fnalss as he dependen varable also makes sense when referrng o FIFA economc ncenves. Gven FIFA dsrbuon rules each eam enerng he World Cup fnal ournamen earns a 3.79 mllon bonus (n 2006). The nex sep reachng he 1/8 h fnals ncreases hs amoun by an exra 1.59 mllon followed by an addonal 1.90 mllon bonus when makng for he quarerfnals. Then for qualfyng o he sem-fnals here s a huge jump of 6.33 mllon followed by only 630000 exra o make for he fnals and wnnng he fnals adds anoher 1.27 mllon (Coupé 2007). In economc erms s raher sgnfcan o qualfy for he sem-fnals. Independen varables are seleced wh a double purpose n mnd: a/ comparng wheher he same soco-economc varables play a role n deermnng FIFA World Cup oucome as wh Summer Olympcs medal wns; b/ fndng a sample of socoeconomc and fooballsc varables ha explan he soccer World Cup oucome n he long run n order o come up wh an ex pos benchmark model ha can be used furher n ex ane predcng he sem-fnalss of he 2010 World Cup. Due o daa avalably he reaned observaon perod runs from he 1962 soccer World Cup up o 2006 whch ncludes 12 fnal ournamens. Daa cover all naonal eams whch have parcpaed o soccer World Cup fnal ournamens snce 1962 ha s 16 from 1962 o 1978 24 eams from 1982 o 1994 and hen 32 eams from 1998 on.e. 272 observaons n an obvously unbalanced panel. Populaon (Pop) and GDP per 1000 nhabans (GDP/cap) are he frs wo ndependen varables consdered jus lke n he Olympcs medal model (World Bank daa). Squares are added for boh varables (Pop 2 and GDP/cap 2 ) n une wh Houson e al. (2002) and Macmllan and Smh (2007) n order o conrol for possble decreasng reurns of populaon and GDP per capa n erms of soccer World Cup 17
performance. The expecaon s ha populaon would have a posve effec on reachng he sem-fnals whle he specfcy of soccer may lead o eher sgnfcan or non sgnfcan effec of GDP per capa. These varables are nroduced n he model wh a wo year me lag under a smlar assumpon as wh he Olympcs: he economc sze and level of developmen of a naon wo years ago s he conex n whch he preparaon and ranng of a naonal soccer eam sars up. In he wo years afer a FIFA World Cup naonal eams are used o parcpae o a regonal nernaonal cones such as UEFA Euro or he Afrcan Cup of Naons. Preparng he World Cup really sars up afer he end of such coness (whch means n -2) when counres sar playng he prelmnary World Cup qualfcaon sage a a regonal level 13. In prevous sudes has appeared ha a naon s hsory n he fooball doman such as World Cup appearances and he lengh of FIFA membershp maers when explanng s nernaonal soccer performance. Gven our objecve of explanng sem-fnals parcpaon a specfc sem-fnal hsory varable (SFsory) s derved from he daa n Appendx 1. I s calculaed by dvdng all he fgures n Appendx 1 by he number of FIFA World Cup fnal ournamens from 1930 up o he year appearng n a column of Appendx 1 (for nsance n he 2006 column all fgures are dvded by 18 n 2002 by 17 and so on). Ths varable descrbes he uneven longerm capacy of a naonal eam o make for he sem-fnals n a hsorcal perspecve and ranks naons accordng o hs capacy. When one alks abou fooballsc naons or fooball-nvolved counres Germany Brazl or Ialy are ofen menoned: ndeed hey have been he mos frequen sem-fnalss a FIFA World Cups. As n prevous sudes FIFA rank s esed as one explanaory varable akng 18
FIFA rankng one monh before he begnnng of he fnal ournamen and a dummy (Hos) for beng he hosng counry. A regonal varable (Reg) s dfferen from he one used n he Olympcs medal model. The laer s purpose was o capure a regonal spor culure effec whle n he case of FIFA World Cup mus measure he relave srengh and densy of ele fooball n sx dfferen geographcal zones no whch FIFA s dvded ha s: AFC for Asa CAF for Afrca CONMEBOL for Souh Amerca OFC for Oceana UEFA for Europe and CONCACAF for Norh Cenral Amerca and he Carbbean. Seedng of he fnal ournamen round robn sage vares across years bu s based on eams successes from each regon n prevous World Cups and organsed n such a way as o assure ha op-seeded eams wll no have o play each oher unl he second phase (1/8 h fnals) of he fnal ournamen (Monks and Husch 2009). A las assumpon o be esed s wheher a soccer-orened naon ha s one whch he number of players s relavely hgh compared o overall populaon s successful n nernaonal soccer. The argumen goes alongsde wh a pyramdal explanaon of ele spor sang ha he larger he mass of spor parcpans a he pyramd base he beer he ele op. Thus mos fooball-orened naons should have hghes probably o qualfy for FIFA World Cup sem-fnals. The number of (regsered) soccer players (Players) dvded by populaon can capure such possble effec. Esmang he deermnans of FIFA World Cup sem-fnalss reles on a Prob model: Pr ( Semfn * 1) [ a b SFsory 4 c N 2 d N 2 2 e Y N 2 f Y N 2 2 g Hos h FIFArank r r D r Reg where Φ s he cumulave normal dsrbuon. k Players ] 19
The paucy of avalable daa for FIFArank and Players has led o esmae hree dfferen specfcaons. FIFA rankng s only avalable snce 1993 when FIFA sared publshng whereas he number of regsered soccer players n all naonal federaons has been publshed only n 2000 and 2006 (FIFA Bg Coun 2000 and 2006) whch markedly reduces he sze of he daa sample. Thus n a frs M1 specfcaon hese wo varables are no aken on board. In a second M2 specfcaon FIFA rankng s nroduced bu he sample s reduced o four World Cup fnal ournamens (1994 o 2006). Snce FIFA rankng does no show up as sascally sgnfcan wh M2 s excluded n a hrd M3 specfcaon whereas he proporon of regsered players n he populaon s aken on board assumng ha he daa for 2000 s accepable for esmang he 2002 FIFA World Cup oucome. Wh a small and unbalanced panel Prob esmaon s used as a frs sep. Then o ackle he endogeney of he sem-fnal hsory varable a Prob model wh an endogenous regressor and nsrumenal varables s resored o. Vald nsrumens mus be exogenous sources of varaon n he sem-fnalss and s dffcul o hnk of canddae nsrumens relevan o explan nernaonal soccer performance (Macmllan and Smh 2007). Thus hose exogenous varables of he bes prevous esmaed model are reaned as nsrumens. 6. Soco-economc and fooballsc deermnans of FIFA World Cup semfnalss Before esmang M1 a prelmnary esng has shown ha addng year dummes o M1 comes ou wh none of hese year dummes beng sgnfcan. Therefore we do no proceed wh panel daa esmaon. 20
Inser Table 5 abou here The esmaon of M1 shows ha populaon and populaon squared s sgnfcan a a 1% hreshold; he sze of a naon maers wh decreasng reurns. Hosng he World Cup s also a sgnfcan deermnan of makng for he sem-fnals. The hos counry has ofen muddled hrough he frs round robn phase of he ournamen o qualfy for he sem-fnals. The mpac of belongng o each of he sx regons on qualfyng for he sem-fnals s no sgnfcan for four regons ou of sx. Takng hese four regons as he reference Europe and Souh Amerca show up as sgnfcan varables a a 1% hreshold. Beng a European or Souh Amercan eam sgnfcanly ncreases he probably of beng sem-fnals. Mos sem-fnalss have been eher European or Souh Amercan eams so far. A las sgnfcan varable hough only a 10% s he sem-fnal hsory varable. Havng parcpaed o pas sem-fnals has a posve effec on he probably of reachng hs sage agan. GDP per capa and s square are no sgnfcan. Ths makes a major dfference beween FIFA World Cup based on a sngle spor dscplne and he mul-spor Olympcs. The laer s oucome s deermned by he level of economc developmen n parcpang counres whereas he former s no. Wh M2 esed from 1994 o 2006 he nroducon of FIFA rankng as an ndependen varable has a devasang effec. Mos varables become non sgnfcan namely populaon populaon squared and hosng he World Cup. FIFA rank self s no sgnfcan eher. The problem wh hs varable s endogeney snce s calculaon ncludes each eam performance (namely qualfyng for he sem-fnals) n he pas hree World Cups 14 and hus FIFA rankng nerferes wh he sem-fnal hsory. The hos counry effec fades away from he deermnans of qualfyng for he sem-fnals agans he frequen hos naon expecaon ha s eam has a home 21
advanage o qualfy. Overall M2 s he mos dffcul specfcaon o nerpre even hough manans he European and Souh Amercan regons as sgnfcan deermnans of makng for he sem-fnals. The sem-fnal hsory remans sgnfcan a 10% and prevals over FIFA rankng as he relevan fooballsc varable. The number of soccer players per nhaban n each parcpang naon s nroduced n M3 nsead of FIFA rank. The esmaon s run for he las wo World Cups whch s n self a lmaon o M3. Then he hos varable s auomacally dropped because here are only wo observaons. The number of players s no sgnfcan whch may be nerpreed as follows: soccer mass parcpaon s no a deermnan of a naon s parcpaon o he sem-fnals of he World Cup fnal ournamen. Ths nvaldaes for soccer he pyramdal vew of spor where he larger he pyramd base of mass parcpaon he hgher performance n nernaonal coness. On he oher hand populaon s sgnfcan he sem-fnal hsory varable s even more sgnfcan (a 5%) han n prevous specfcaons whle GDP per capa and squared become sgnfcan a 10%. However regonal varables Europe and Souh Amerca are no sgnfcan because only wo World Cups are kep: n 2006 no Souh Amercan eam has reached he sem-fnals whereas n 2002 one sem-fnals was neher European nor Souh Amercan (Souh Korea). Fnally a conrol for endogeney beween he dependen varable and one explanaory varable he sem-fnal hsory s requred. The laer s nfluenced by each new World Cup resuls hough n he long run hese resuls have a decreasng margnal effec on our cumulave varable. Thus he sem-fnal hsory s used as an endogenous regressor and all oher varables aken on board n M1 as nsrumens. Frs he sem-fnal hsory varable s regressed on populaon populaon squared GDP per capa and squared hosng he Cup and regonal varables and hen he 22
relaonshp beween he dependen varable (makng for he sem-fnals) and he endogenous sem-fnal hsory regressor s suded. Inser Table 6 abou here Table 6 shows ha all he nsrumenal varables are explanaory of he sem-fnal hsory excep he hos dummy. I s logcal snce he sem-fnal hsory varable s a cumulave percenage over 18 Cups whereas a counry has been hosng he Cup only once or wce 15. Now he model s que conssen and close o he Olympcs medal model snce no only populaon and regonal varables bu also GDP per capa are sgnfcan deermnans of FIFA World Cup oucome. A clear specfcy s ha hosng he soccer World Cup s no a comparable advanage o he one of hosng Summer Olympcs. However such realy has been blurred for a long me by he World Cup beng always locaed eher n Europe or Souh Amerca unl 1990. Snce hen he number of excepons has ncreased wh one locaon n Norh Amerca (1994) Asa (2002) and Afrca (2010). 7. The predcon for he 2010 FIFA World Cup n Souh Afrca: sll so hard! The model esmaed wh nsrumenal varables as well as M1 specfcaon are now used o forecas he 2010 FIFA World Cup sem-fnalss akng no accoun he daa for populaon and GDP n 2008 and he cumulave sem-fnal hsory varable up o 2006. The predcon s exhbed n Table 7. Inser Table 7 abou here The four eams wh he hghes probably o make for he sem-fnals n Souh Afrca are he same wh boh M1 and he model wh nsrumenal varables. If one nerpres he wo hghes ranks (probables) as he mos probable fnalss he former predcs Germany playng Ialy n he fnals whle he laer forecass Germany 23
playng Brazl. France s ranked fourh n boh cases. Compared o FIFA rankng publshed n May 2010 hese resuls are srkngly dfferen: he frs four FIFA-ranked eams are Brazl and Span (poenal fnalss) hen Porugal and he Neherlands. Brazl s he mos wdely admed sem-fnals whaever he mehodology used for predcon. If one goes as far as nerpreng hese rankngs as a probably o parcpae o he 1/8 h fnals here s a good chance ha Argenna Brazl Chle England France Germany Greece Ialy he Neherlands Porugal Serba Span and Uruguay would qualfy for he second sage of he 2010 soccer World Cup fnal ournamen. Snce he wo models encompass a hos counry effec boh predc Souh Afrca qualfyng for he second sage of he fnal ournamen conrarly o hs naon s FIFA rankng (83 rd n May 2010). Of course hose foureen eams 16 whch are no menoned n Table 7 would be bg surprses f qualfed for he sem-fnals. None of hem has made! Acually he four sem-fnalss of he 2010 World Cup have been: 1/ Span 2/ Neherlands 3/ Germany 4/ Uruguay. Thus our model dd no perform wh he soccer World Cup as well as dd wh Olympc medals snce correcly predced only one sem-fnals (Germany). Nobody (see below) expeced Uruguay o qualfy for he sem-fnals whle s he ffh bes probably (behnd France) o qualfy n our model predcon. The bankng busness has recenly sared usng predcons of he soccer World Cup oucome as an appealng facor o nvesors wh negrang hese predcons n he promoon of fnancal producs. Consequenly some banks economss have elaboraed on predcon models ha can be compared ncludng her resuls wh our model. Goldman Sachs J.P. Morgan and UBS (Unon des Banques Susses) have produced a prognoss abou he sem-fnalss of he 2010 soccer World Cup. 24
Goldman Sachs (2010) has predced he followng sem-fnalss ranked accordng o her probably o qualfy: 1/ Brazl 2/ Span 3/ Germany 4/ England - wo correc ou of four wh a mehodology prmarly based on bookmakers odds (Ladbrokes.com) as of May 4 2010 and parly on smulang he oucome of each qualfcaon group and hen of each of he hypohecal resulng mach durng he knock ou sage. However some guessmaes nerfere as: from Group A France would seem he sronges bu Mexco looks dangerous Uruguay s a b of an unknown and hen here are he hoss Souh Afrca Ths could be que a rcky group for he ageng (and some especally Irsh observers mgh say undeservng!) French. I am gong o assume ha Mexco wns and Souh Afrca s runner-up. Wrong anyway bu from a mehodologcal pon of vew hs sounds hardly more han a oss-up! The sudy by J.P. Morgan (2010) adaps s QUANT scorng model (used o denfy long/shor radng opporunes n fnancal markes) o forecasng he soccer World Cup oucome by combnng several fooballsc varables. Ths scorng model delvers he followng rankng: 1/ Brazl 2/ Span 3/ England 4/ Neherlands. Then he calculaed scores (for all eams) are used excludng any ed game ogeher wh a penaly shoo ou merc o decde whch counry wll wn each of he 64 fxures; he calculaon comes ou wh a England-Span fnals won by England due o a beer penaly shoo ou ndex. Ths model confnes self o FIFA World Cup varables bu does no perform beer predcng only wo of he acual sem-fnalss. UBS (2010) approach saes from he very begnnng ha socoeconomc facors lke populaon sze or GDP growh have no explanaory power when comes o forecasng he performance of a specfc eam and ha a every World Cup here s a leas one surprse parcpan n he sem-fnals. UBS model akes on board: a 25
eam s pas performance n he World Cup; wheher or no a eam s a hos naon; an objecve quanave measure ha assesses he srengh of each eam hree monhs before he sar of he World Cup. The las varable s calculaed by usng he Elo rangs developed o measure and rank he srengh of chess players; s assumed o be beer han FIFA rankng because akes no accoun no only he number of a eam s wns losses and draws bu also he specfc crcumsances under whch hose evens occurred. Brazl s predced o have he hghes probably o wn he 2010 World Cup (Span has only he 7 h bes probably). The bes probables o make for he sem-fnals are: 1/ Brazl 2/ Germany 3/ Neherlands 4/ Ialy. Sll 50% correc predcons are found whch also means 50% wrong. 8. Spor surprsng oucomes and s mercs: an avenue for furher research Unexpeced or surprsng oucomes of a spor game or cones have no really been analysed so far. The frs pon o clarfy s he dfference beween he concep of oucome uncerany and a surprsng oucome. On he one hand he uncerany of oucome bascally s an ex ane concep resuls from he equaly or closeness of sporng forces whch are gong o be opposed n a game or a spor cones whle a surprsng oucome s necessarly an ex pos noon: he acual oucome has appeared surprsng compared o some ex ane expecaon or predcon or sandng. A surprsng oucome s o some exen he oppose of oucome uncerany whch s deeply rooed n oucome unpredcably. The laer s very hgh when wo eams are so close n erms of sporng forces ha s mpossble o predc he game oucome (or all eams are so close ha he league s fnal rankng canno be predced). A surprsng oucome s que he oppose nsofar as occurs when a sporng oucome 26
s raher predcable bu happens o be dfferen from he predcon. Ths happens when opponens n a game (cones) have clearly uneven sporng forces and he underdog wns he favoure for nsance a low FIFA-ranked naonal eam defeas a hgh FIFA-ranked naon. In a nushell a surprsng spor oucome may be defned as he ex pos nvaldaon of an ex ane raher hgh oucome cerany (predcably) whereas oucome uncerany s he ex ane unpredcably of an ex pos acual oucome. Many mercs may be conceved for measurng he occurrence of a surprsng sporng oucome. Ths s an avenue for furher research and as a frs sep macroand mcro-assessmens of a surprsng sporng resul can be suggesed 17. Wh he aforemenoned FIFA World Cup predcon model a macro-surprse would occur when a eam had no made for he sem-fnals whle he model was predcng s qualfcaon and symmercally when an unpredced eam qualfed for he semfnals. As o hs model Span and he Neherlands qualfcaon (o a lesser exen Uruguay qualfcaon) were surprsng as well as Brazl Ialy and France no makng for he sem-fnals. To oban an overall mercs suffce o pu ha when a eam s hgher (lower) ranked by he model han he acual rankng of he fnal ournamen one wness a surprsng spor macro-oucome. The surprse magnude can be assessed by he rank dfference beween he model s predcon and he acual oucome (Table 8). In a same way would be possble o defne macro-surprses comparng FIFA rankng and FIFA World Cup oucome or comparng he laer wh banks predcons. Inser Table 8 abou here Wh all predcons hree bg surprses emerged: Ghana Paraguay and Japan makng for he 1/8 h fnals. Uruguay also s a raher bg surprse snce s 27
qualfcaon for he 1/8 h fnals and even he ¼ fnals were only predced wh our model. To some exen England s rankng due o a severe loss (1-4) agans Germany n he 1/8 h fnals was also surprsng. Noce ha Goldman Sachs dd no fnd any bg surprse whle he varance beween s predcons and acheved oucomes s hgher han wh our model. The laer deecs wo bg surprses: Uruguay qualfyng for he ¼ fnals and he falure of England s eam. JP Morgan s predcons have he hghes varance wh he acheved oucomes whereas s confrmed ha FIFA rankng s no a good predcor eher. However dfferences n he exac meanng of measured surprses mus be underlned. A comparson beween he acual FIFA World Cup oucome and our model s predcons exhbs sporng surprses wh regards o naons economc developmen and her pas performances n he World Cup. Wh JP Morgan s predcon and FIFA rankng srcly speakng fooballsc surprses are poned a: he acual oucome s surprsng compared o exclusvely fooballsc varables. Goldman Sachs predcon shows how much bookmakers odds before he World Cup were dsan from he acheved oucomes. Beng n accordance wh Goldman Sachs on Germany as he Cup wnner would have resuled n a gambler s moneary loss whle beng on Span as one of he fnalss would have yelded some reurn. A mcro-mercs of surprsng spor oucomes may be based on a weaker eam (underdog) wnnng a sronger eam (favoure). If one lower FIFA-ranked eam won a hgher FIFA-ranked eam hs would be a mcro-surprse. Wh our model Ghana- USA (2-1) n he 1/8 h fnals was surprsng as well as Neherlands-Brazl (2-1) n he ¼ fnals and Span-Germany (1-0) n he sem-fnals. Wh FIFA rankng and Goldman Sachs predcon he mcro-surprses were only Ghana-USA (2-1) and Neherlands- Brazl (2-1). On he oher hand JP Morgan s predcon was surprsed by Ghana-USA 28
(2-1) and Germany-England (4-1) n he 1/8 h fnals and Neherlands-Brazl (2-1) and Germany-Argenna (4-0) n he ¼ fnals. JP Morgan s predcon defnely s he furhes from acual oucomes when lookng a boh mcro- and macro-surprses. The noon of surprsng sporng mcro-oucome may be refned wh he hsorcal varable of our model checkng wheher n he 2010 World Cup fnal ournamen a naon whch never made for he sem-fnals has been able o wn a naon whch already qualfed for he sem-fnals a leas once snce 1930. Wh such a creron followng oucomes are surprsng: Ghana-USA (2-1) n he 1/8 h fnals and durng he round robn sage Mexco-France (2-0) Souh Afrca-France (2-1) Serba-Germany (1-0) Slovaka-Ialy (3-2) and Swzerland-Span (1-0). Two eams dd no survve o her surprsng losses n he qualfcaon groups (France and Ialy) whereas he wo ohers even made for he sem-fnals (Germany and Span). Concluson Snce our modelled predcon had been able o correcly deec 70% of acual medal wnners a he Bejng Games a naon s sze (populaon) and level of economc developmen once compleed wh a few dummes are good predcors of medal wns. The laer can be aken as a relevan ndex for comparng economc developmen across naons n addon o oher economc and socal ndexes. A same model does no perform ha well wh predcng he 2010 FIFA World Cup sem-fnalss. Soccer World Cup oucomes are n no way an accepable ndex of economc developmen. The hos counry effec (home advanage) s less sgnfcan n soccer World Cup han n Summer Olympcs. However any economc predcon of sporng performance mus be aken wh a pnch of sal. Ths s namely due o a 29
number of surprsng sporng oucomes. Elaborang on a mercs o quanfy hem should be a promsng avenue for furher research. References: Andreff M. W. Andreff & S. Poupaux (2008) Les déermnans économques de la performance olympque: Prévson des médalles qu seron gagnées aux Jeux de Pékn Revue d Econome Polque 118 (2) 135-69. Andreff W. (2001) The Correlaon beween Economc Underdevelopmen and Spor European Spor Managemen Quarerly 1 (4) 251-79. Arellano M. & S. Bond (1991) Some Tess of Specfcaon for Panel Daa: Mone Carlo Evdence and an Applcaon o Employmen Equaons Revew of Economc Sudes 58 277-97. Ball D. (1972) Olympc Games Compeon: Srucural Correlaes of Naonal Success Inernaonal Journal of Comparave Socology 13 186-200. Bernard A.B. & M.R. Busse (2004) Who Wns he Olympc Games: Economc Resources and Medal Toals Revew of Economcs and Sascs 86 (1) 413-17. Clarke S.R. (2000) Home Advanage n he Olympc Games n G. Cohen & T. Langry eds. Proceedngs of he Ffh Ausralan Conference on Mahemacs and Compuers n Spor Conference proceedngs Sydney: Unversy of Technology Sydney 43-51. Coupé T. (2007) Incenves and Bonuses The Case of he 2006 World Cup Kyklos 60 (3) 349-358. 30
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Yamamura E. (2009) Technology Transfer and Convergence of Performance: An Economc Sudy of FIFA Fooball Rankng Appled Economcs Leers 16 261-266. 1 Bernard and Busse use he percenage of medal wns by each counry for M nsead. Our regressons are calculaed wh boh he absolue number of medals (Table 3) and he percenage of medals per counry and he resuls are no sgnfcanly dfferen. 2 Hoffmann e al. (2002a) consder ha an mporan deermnan of Olympc successes les n he degree o whch sporng acves are embedded n a naon s culure. The proxy used o capure such deermnan s he oal number of mes a counry has hosed Summer Olympcs from 1946 o 1998. 3 A dscussan has suggesed o es n a frs sage a wnnng versus no wnnng a medal hypohess and hen esmae n a second sage he number of medal wns (when > 0). Here we assume ha wnnng zero medal or wnnng 1 2 n medals resuls from he same procedure and mus be esmaed wh he same explanaory varables. 4 A es of maxmum lkelhood shows ha he rho coeffcen s sgnfcan (Pr = 0.00). 5 Our daa panel s no balanced snce he number of parcpang counres has ncreased beween 1976 and 2004 namely due o he break up of he former Sove Unon former Yugoslava and former Czechoslovaka (+ 20 counres n he world) only parly compensaed by he re-unfcaon of Germany and Yemen (- 2 counres). 6 A es of maxmum lkelhood shows ha he rho coeffcen s no sgnfcan (Pr = 0.26) whch allows o op for a poolng esmaon. 7 Resul for any oher counry s avalable on reques addressed o he auhors. 8 Ths ssue s dscussed n deph n Andreff e al. (2008) explanng why we had no been able o negrae dopng among ndependen varables despe ha we wshed o do so. 33