Also, several top European soccer clubs have adopted an unofficial contract policy with shorter contracts lengths as players are nearing 30 years, based on a belief that elite players are well past their peak performance after this age Dendir, Thus, the age of professional soccer players and at which age professional soccer players peak seems to be an important variable of interest not only to performance analysts and sport scientists, but also managers and coaches.
Knowledge of when players are in their optimal age, therefore, has substantial value for the soccer industry. From a sport perspective, this provide useful information regarding at which age soccer players are likely to perform at the highest level. However, while the evolution of tactical, technical and physical performance over time have been studied extensively e.
In tennis, for example, Kovalchik , p. Chronological age of highest performance differs among sports Smith, and depends on different biological capabilities involved in each sport and by the specific skills and attributes needed to succeed Allen and Hopkins, This argues the evidence that physiological and technical constraint of each sport dictates the window for optimal performance Dendir, At this respect, peak window of mids estimated by Dendir seems to be explained by the combination of endurance and explosive power necessary to cope with physical and physiological demands of modern elite soccer.
We hypothesize that the average age of the Champions League players has increased across all positions and team levels. We further hypothesize that an inverted-U curve defines the association between market value and age, with peak value occurring at the mids.
Each participation of a player in a season was recorded as an individual case, i. This classification was done according to the information provided by the official UEFA website 1. In line with previous studies and for posterior analyses Botek et al. The assumption of normality of the data was checked both graphically and using the Kolmogorov—Smirnov test. All data were normally distributed. As the samples were normally distributed and displayed homogenous variance, a one-way analysis of variance ANOVA was used to evaluate differences in mean ages across different playing positions.
Subsequently, one-way independent-measures ANOVA test with sphericity assumed was used to compare mean age from each season. In the event of a difference being present, Bonferroni-adjusted post hoc tests were used to identify specific effects. Moreover, the effects of the age of the players AGE , the playing position PP , the number of seasons in the club NS and the number of Champions Leagues won NCL on the market values of the players were also examined through a linear regression model.
Positive or negative coefficients indicate a greater or lesser market value of the players, respectively. The model is as follows:. The histogram of the age distribution for players included in the study is presented in Figure 1. The age of the players ranges from 16 to 43, with an average of From 29 years an onward, there is a substantial yearly decrease in the number of players.
However, this increase was not uniform, and two break-points were identified along these seasons, the first one in season — and the second one in season —, which can be observed in Figure 2. Figure 1. GK As can be seen in Figure 4 , although an aging trend was found for all categories of team performance considered, no significant differences were found between winners, finalists or semifinalists and the other categories. Effects of independent variables on the market values of the players are displayed in Table 1.
Table 1. The influence of the age of the players, playing position, number of seasons in the club and number of Champions Leagues won on the market values of soccer players. The more seasons a player stays in a club, the higher their market value is. The principal finding of the present study is that an aging trend has occurred in the last three decades in the UEFA Champions League.
Previous studies Kuper, ; Caley, ; Dendir, have demonstrated that professional soccer players peak around their mids. However, none of these studies have analyzed the aging pattern in elite soccer. It seems that the evolution of contemporary soccer is probably associated with increasing age of athletes. Although an aging tendency has occurred for all playing positions between the — and — seasons, GK and CB tend to peak later than F.
Recently, Dendir found that the average forward and defender peaks at 25 and 27, respectively. These findings can be largely explained by differences in the physical demands of playing each position, which has previously been heavily studied Bangsbo et al.
Using time-motion analysis, these studies have shown that forward performs both higher number of and longer maximal sprints, higher number of shuffles, more contact at high intensity and higher amount of high and very high intensity activities; defenders the spend the least time running and sprinting, while midfielders the most Bangsbo et al.
The lower physical demand for defenders is likely one of the reasons they tend to peak at a later age, as well as maintaining a high performance higher up in age. In similar fashion, the higher amount of high-intensity activity is probably one of the causes of the earlier peak of forward.
Conventional wisdom suggests that there is a perfect age to be a successful player. The average age of the 32 teams that participated in the last two World Cups was It has been found that a one-year increase in average team age results in a performance drop of four positions in the World Cup Dendir, According to our results, although an aging trend was found for all team performance categories considered, no significant differences were found between winners, finalists or semifinalists and the other classifications.
These results may be due to the fact that players from all over the world participate in the Champions League, and the differences between the participating teams probably are smaller than in the World Cup.
The good news is that you can finish that beer. Skip to main content. Getty Images. Connor Fleming July 29, Connor Fleming fleming the He drops out of the data set.
The only older forwards remaining are the freaks and the greats. For example, Zlatan Ibrahimovic is still scoring goals in the Premier League but Andy Johnson, who was born in just like Ibrahimovic, is now retired and has taken a position as a club ambassador for Crystal Palace.
If he were still playing in the Premier League, Johnson's numbers would surely be quite bad and drag down his peers' averages. But he isn't playing and so the older players' numbers are falsely inflated. There's a simple way to fix the "missing old guys" problem and several more complex ways. The simple method provides the most straightforward way of mapping age: You just add up all the minutes played.
There are many, many year-olds in the Premier League and very few year-olds because players reach their peak performance levels around age As this chart shows, players generally peak between the ages of , but there are differences by position. Wingers tend to peak and decline the earliest. Wide attackers under the age of 23 play more minutes than U players at other positions, but wide attackers over 30 are much rarer than strikers or center-backs of an equally advanced age.
While most of the curves are well on the downslope by 30, the curve for center-backs by contrast doesn't really begin to decline until 31 or This suggests a general rule. Players tend to get slower and generally lose athleticism as they age, but they also gain skills and know-how to balance that out.
Positions that require the most athleticism are a young person's game, whereas older players will more often be found at positions that most prize guile. Ranked from the most to the least "age-sensitive" positions: Wide attacking midfielder, central attacking midfielder, full-back, central midfielder, striker, center-back, goalkeeper.
It's extremely difficult to play midfield in the modern game without peak athletic skills. At striker or center-back, a player who adds skill and guile may hang on for much long as his athleticism declines.
One way players can thus buck their aging trends is by moving positions, just as Javier Mascherano extended his career by moving from central midfield to center-back; likewise, Cristiano Ronaldo subtly moved to a "true" striker role after years as a hybrid winger. Players can do this by developing other skills to make up for what they lose. Different skills, then, have different aging curves, which can help to predict more specifically how player production will evolve over the course of a career.
To identify player skills, we are using a new method that compares a player's performance in one season to his performance in the next. This method avoids most of the problems of the "missing old players" because if a player disappears from the data set in the next season, his previous season is also not included. One thing this age curve can help with is roster planning for the future.
Right now, Chelsea have the Premier League's top scoring striker in Diego Costa, as well as highly-touted prospect Michy Batshuayi in reserve. Costa, however, has been scoring more goals. Such a pattern of high shot rates with lower conversion at a young age is common with forwards.
The aging curve for attacking players shows a tendency for players to take fewer shots as they age, but to increasingly get on the end of better chances and therefore make up the difference.
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