Influence Month of Birth on Success Football Players
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Influence month of birth on success football players Thomas Res 10454918 Supervisor: Ron van Maurik 15-07-2016 Bachelor Thesis University of Amsterdam Faculty of Economics and Business 1 Statement of Originality This document is written by student Thomas Res who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents. 2 Contents 1. Introduction 4 2. Literature review 5 3. Data 8 4. Methodology 12 5. Conclusion 15 References 17 Appendix A 18 Appendix B 19 Appendix C 20 3 1. Introduction Imagine identical twins where the oldest is born just before new year on the 31th of December and the youngest is born just after new year on the first of January. Both have the same genes, same education and are born with the same sport talent. Yet, the youngest has far better chances of becoming a professional sports athlete. This is due to the relative age effect. A lot of research has been published about the relative age effect in sports over the last decades. According to the existing literature about the relative age effect, football clubs should be aware of this phenomenon by now and change the way of scouting. No longer scout the best players, but the players with the highest potential. Still, in selections of sport teams players born in the early months of the selection year are overrepresented. Football is a big business. Clubs want to make money, so they are able to buy players of high quality. If a club can increase their budget, they can afford signing high quality players and are more likely to gain success. It is in the best interest of a football club to have players in the squad who represents high value. Most football clubs have more players born in the early months of a selection year than players born in the last months (see table 1), while there is no evidence that players born in those early months have more potential than players born in the last months. This relative age effect has been known for several decades now. But apparently players born in the first quarter are still overrepresented. Is this a sign of bad investment or are players born in the first quarter worth more than players born in other quarters? What is the impact of month of birth on the success (quality) of football players in the Dutch League? Table 1. Month of birth in youth academies professional Dutch football clubs Bron: Tussendelinies.nl To measure the rate of success of an individual football player his market value will be used as an indicator. If a player has skills and can add value to a team in order to win prices, teams have to pay a price in order to contract him. The more qualities a player has, the more money his club can ask. The market value of a player will be a good indicator of the qualities of a player. To investigate the impact of month of birth on the market value of football players in the Dutch League data of all football players who were on the pitch during any League match in the Dutch first division in the season of 2015/2016 will be gathered. Then a regression analyse will be performed. Variables that could influence the market value of a player will be included. The age of a player, his position on the field and his month of birth. A regression analyses will be done to show the influence of all these variables and to see if the month of birth of a player does have an influence on their market value. 4 In paragraph 2 the existing literature will be discussed. In paragraph 3 the dataset will be explained and in paragraph 4 the results will be shown. In paragraph 5 the results will be discussed and a conclusion will be drawn. 2. Literature review To become a successful sport athlete, several factors play a role. Including gender, training, nutrition, family background and social cultural influences (Nakata & Sakamoto, 2011). In the last two decades, the month of birth is also considered a relevant factor. In the 1980s this effect in sport was first noted in Canadian ice hockey. Grondin, Deshaies & Nault (1984) and Barnsley, Thompson & Barnsley (1985) concluded that success as a hockey player is related to the month of birth. They suggested that this was due to the fact that if children are categorized based on their age, which is the case in sport, children born immediately after the selection date are approximately 12 months older than children born just before this selection date. The older children in the age group have a developmental advantage over the younger children in the same age group. The children born in the first months after the selection date are in general bigger, stronger and better coordinated than their teammates who are born just before the selection date. As a result, when these children play sport together, in general the older children perform better. Because they are doing better, the older children achieve more success and receive greater awards. The younger children are more likely to experience frustration and failure. This could lead to a lower self-confidence and self-esteem. As a result of these experiences, according to Barnsley and Thompson (1988), they may quit doing this sport and so their potential talent will not be exploited. After the result from Barnsley, Thompson and Barnsley in 1985, there has been done many research on the relative age effect in several sports. In football, worldwide sport number one, the relative age effect has been researched all over the world. This has been done by looking at the population of month of births of football players in all sorts of competitions. To investigate whether the population is equally distributed most researchers used a Kolmogorov-Smirnov test or a chi-square test. All players of the sample will be divided on the basis of their month of birth in quarters. Players born in the months January till March will be placed in quarter one, players born in the months April till June will be placed in quarter two, etcetera. Then a one sided Kolmogorov-Smirnov test is used to test if the distribution of the sample fits the chosen distribution, in this case a uniform distribution. Or a chi-square test is performed. With the chi-square test an expected value will be calculated for all possibilities. On the subject of the relative age effect, the months of birth will be examined, so for every month the expected total amount of players born in that month will be calculated. The chi square test will be based on a uniform distribution. For example January has 31 days, so the chance of a player being born in January = 31/365.25 = 0.085. The expected value for January is then 0.085 * total amount of players. The expected values will be compared with the observed values and if there is a significant difference, the conclusion will be drawn that the month of birth of the players is not uniform distributed. Skewed birth-date distributions have been revealed in favour of the individuals born in the first months of the selection year all over the world. Verhulst (1992) showed the relative age effect in the first and second professional divisions of Belgium, the Netherlands and France. Dudink (1994) reported a significant relative age effect in all top four leagues in England. Musch & Hay (1999) found a strong relative age effects in Germany, Japan, Brazil and Australia. Bäumler (1996) showed the effect in the highest professional division in Germany. However, Bäumler found 5 that the relative age effect among the youngest players (18-20 years) was much stronger than the relative age effect among the oldest players (33-35 years). In fact, the relative age effect on the oldest players was not significant at all. According to Bäumler this was evidence that the physical advantage of the players born early in the selection year decreases over time. Most researchers argue that the cut-off dates are the only factor underlying skewed birthdate distributions. Musch & Grondin (2001) stated that this claim must be defended against all other possible alternative explanations. Wendt (1978) showed that seasonal circumstances could influence the child’s development. For example, children go to different phases of motor learning. Warm weather during an important phase, could have a positive influence on the development of a child’s sport-related skills. According to Wendt children born in certain months of the year can profit from the fact that their critical sensitive phases are during the summer rather than during the winter. Therefore it could be that these seasonal circumstances lead to a skewed birthdate distribution. To investigate this potential factor of the skewedness of the month of birth distribution in football, Musch and Hay (1999) compared the relative age effect in German football with the relative age effect in Brazilian football. Both countries have a highly developed soccer system and used a cut-off date of August 1. However, climatologically Germany and Brazil are exact opposites. If there would be a 6-month shift in the pattern of birth dates, this would suggest that there is an influence of season or climate.