Performance analysis

More specifically this manuscript will discuss performance indicators in football from a scientific point of view.

Statistics in football/performance analysis seemed to be present for a long time, ~40 years (69). While paper and pencil was used in earlier days, software solutions like ProZone allow a more in-depth analysis of football games.


What are the “common” performance measurements?

A performance indicator is a selection, or combination, of action variables that aims to define some aspects of a performance in a given sport and, these performance indicators, should relate to successful performance or outcome (14, 35).

Utilizing this definition it seems necessary to define “action variables”, which we have then categorized into physical/physiological, technical, tactical and others parameter and will discuss them individually.


Physical/physiological parameters

Physical capacity of players seemed to be a key factor in match performance, despite the fact that non-successful teams covered greater distance in high-speed movement activity (10), which suggests that factors other than physical performance represented are more important in achieving success.

Non-significant differences were seen in body composition (48). However there were also significant differences between players from successful compared to unsuccessful teams. Differences were seen in strength and power (5, 16, 19, 94) measures such as countermovement jump, leg extension etc.

Further information stated that improved physical capacity of players influence technical ability (71), namely increased pass rates and therefore might indirectly improve performance indicators (31). Studies in England (20) and Italy (66) have reported an association between physical output and final league ranking (10). More specifically, match activity such as high-speed running in relation to league position at the end of the playing season have been used to provide an indication to which physical performance can influence the ‘success’ of teams. However, total run distance was not associated with the final result (37).

It seems obvious that the physical capacity needs to be the foundation for “being ready to play” – as different playing style will have influence on the physical demands on the players (8).

In return, being “not fit” or not ready to play also suggest that injuries will have an impact in performance and it was shown that successful teams had significant less injuries compared to non-successful team (5).


Time-motion analysis

It seems evident that “fit” players can cover greater distance if needed, disregarding of level of play. For example, researchers (9) suggested that distance covered at high intensity are more valid measure of physical performance in soccer because of their strong relationship with training status (42, 43) or level of play (59).

However, generally, time-motion analysis parameters were also influenced by many factors (such as score line, ball possession, opponent) and therefore might not be an appropriate performance indicator.


Technical parameters

Similar to the physical/physiological parameters, technical elements are very important in football and most of the time these parameters (such as shots on goal…) are very easy to measure reliably. This kind of analysis is called notational analysis (35).

It seems obvious that there is a link between number of goals scored, and more importantly number of goals conceded (12) and success in football. However, the relationship seems not so clear with regards to other parameters such as shots on goal and passes completed (and others) and the final result of a game. In accordance to Hughes and Bartlett (35) we have divided into passes, tackles and shots.

Number of passes
Overall number of passes (76), pass attempts during net playing time (76) and overall number of correct passes were figured as important factors in achieving better results (37, 49). Longer passing sequences are a more efficient way of scoring goals compared to shorter passing sequences in elite Australian football (38).

Types of passes
Types of passes were not seen as a performance indicator (37, 77, 79). However, Successful teams were able to execute a wider variety of passes as a tool to create shots, making them less predictable and being able to shoot more frequently (33). Crosses and chips were used more significantly by successful teams compared to unsuccessful teams (33).

Passes into specific areas
Penetrative passes into the box and the 6 yard area seemed to increase the number of shots on goal and consequently number of goals (30) offensively. Interestingly, unsuccessful teams tended to play significantly more passes in(to) the pre-defensive area (77).

Pass accuracy
There is not doubt that pass accuracy is an important performance indicator in football in general. For example it was shown that the pass accuracy was significant higher 5 minutes before scoring (67). Pass accuracy not only retains possession, but may also lead to scoring opportunities while also restricting possessions and scoring opportunities of the opposition (67).

Pass to opposition/interceptions
There seemed to be no evidence about pass to opposition/interception as performance indicator. It seems not clear if the interception are a consequence of the inability to pass accurately or good movement from the opponent (or a combination of both) (60). However, we believe everyone can agree that low number of opposition and high number of interception might help to succeed in the game.

Tackles won/lost
Limited research is available for tackles won/lost in connection with performance in football. Interestingly, it is not reported that number of successful tackles links to success, however the number of tackles and the total fouls discriminated between top tiers and lower ranked teams (62). Additionally, a low number of successful tackles defensively may have contributed to a high number of conceding goals (60).

Shots on/off target
Disregarding success, home teams have 26% more shots, however the success rates for the shots do not differ from away teams (80). Successful teams have a greater number of shots (13, 50), shots on target (13, 50), but more importantly a better rate for number of shots per goal (24, 50) offensively, but also a lower rate of shots and shots on their own goal (13).

Furthermore, the area/zone of scoring attempt were also presented: The penalty area (44.4%), goal area (32.2%) and outside the box (20.4%) were chosen for goals (96), however 90% of all goals was scored inside the penalty area for the 1986 World Cup (63), whilst it was 80% for the World Cup 1990 and 81.8% for goal scoring attempts appeared in the penalty area for Greek domestic football (82, 95).


Tactical parameter

Ball possession
Generally, ball possession seemed to influenced by situational variables (49). As a result, the variable was influenced by the game status (winning and drawing), match location (home teams have greater possession than away teams) and quality of opponent (less possession against “good” teams (49).

Despite the mentioned, it was thought that ball possession is of central importance to success in football, however questions remain about its impact on positive team outcomes (15).  It seems that in domestic play, ball possession is an important performance indicator (-especially in England and Spain) (44, 46, 49, 86).

However, when opponent quality and home advantage was accounted for, ball possession was not a good performance indicator anymore (15).

Nonetheless, successful teams had more possession in general (13, 17, 33, 37, 39, 49, 68), however, also when a) winning and drawing (70) or even when losing or drawing (15), compared to unsuccessful teams. There was no difference between successful and non-successful teams for ball possession when winning (36).

Ball possession in a certain are of the pitch
Ball possession in certain area of the pitch seems to be influenced by the score line (72), showing less ball possession for the scoring team in the attacking and middle thirds compared to the average for the half (72). On the contraire, the conceding team significantly increased its possession in the middle and attacking third and decreased the possession in its own defensive third. Furthermore, pre-goal possession showed that the scoring team had significant more possession in the middle and attacking third (72).

Zone 14 also seemed to have a crucial role in football, more specifically, ball possession (and also its effective usage) (71).

Interestingly, unsuccessful teams played more passes in the pre-defensive area (before the half-way line) (78).

Ball possession as a sequence
In the study by Hughes et al. (34), the number of passes that led to goals scored in two FIFA World Cup finals were analyzed. It seemed as there were more goals scored from longer passing sequences than from shorter passing sequences. Longer possession resulted in more shots per possession; however, the strike ratio of goals from shots was better for “direct play” compared to “possession play”. Successful teams scored more often from longer possession (compared to short(er)) possession (34).

Possession lengths of 3 to 7 passes seemed more likely to produce goals than shorter and longer length possessions (60).

Attacking third entries
Attacking third entries was mentioned to be a performance indicator discriminating successful from unsuccessful teams (70).


Tactical ability / formation / playing style

As a clarification, we will not discuss individual tactics despite its importance on the group efficacy (40).

Despite hard to quantify, it seems evident that the tactical ability, the formation and the playing style play a role as performance indicators. For example, interception of an opponent pass and subsequent fast counter-attack would all be considered as key sports behaviors (57).

Therefore, the following paragraphs will focus not only on tactical behavior (such as ball possession above) but also on how these tactical parameters are achieved.

The so-called game modeling has been used (42, 58) to detect game patterns distinguishing successful from non-successful teams (28).

We have sort them into offensive and defensive patterns, but also highlighting the transitional phase (and pressing).

Team offensive play in sequences ending in a shot on goal are influenced by situational variables (such as numerical relationship between attack and defense players) (64).

However, offensive actions play a key role in football. More specifically, organized offense presented the highest frequency in goal scoring, followed by set pieces (35.6%) and counterattacks (20.3%) (96). Furthermore, 80% of goals scored after short duration attacks, and players touched the ball a maximum of 3 (29) or 4 (34) times. 

As many shots (on goal)/goals are performed from the area directly in front of the penalty area (zone 14) as well as many assists derived from that zone (32), it seems logical to penetrate that zone as much as possible or enter the final third (70). 64% of possessions within that zone derived from ball possession of between 0.5-2.5 seconds (32). 46% of off-target attempts from zone 14 were from possessions of just one second (70). However, it was also reported that not the amount of possession, but its effective usage/conversion distinguished between successful and non-successful teams (70).


Zone 14
Zone 14

Obviously crosses are also effective to increase shots on goal (41) as mentioned above 90% of all goals was scored inside the penalty area for the 1986 World Cup (63), whilst it was 80% for the World Cup 1990 and 81.8% for goal scoring attempts appeared in the penalty area for Greek domestic football (82, 95).

A mixture of short and long passes seems to be a promising way to build up attacks and furthermore scoring from short and long distances increases complexity of defending. Especially short passes seemed to be reliable in keeping ball possession (62).

Transition seems to be of high importance in football (92) as the team that just lost the ball is in a (more or less) unorganized/variable situation which was proven to have significant effect on conceding goals (27, 88).

Pressure applied to players having the ball seemed to be crucial in the mid-offensive zone, as these actions preceded “successful finishing” (70), defined as shots on target (54). The goals scored were mainly preceded by behaviors in zones near the opposition goal. Pressing was seen as a key index in/around the box and in general pressed player are less affected and therefore less dangerous (84).

Defensively, recovery of the ball was seen as a performance indicator (6).

It appears that individual defense's ability of teams to control the opposing team's movements will greatly affects on success in Football (25).

A scientific measure was the longitudinal and lateral inter-team distances, centroid position, and the area of the team span on the pitch (27).

Additional thoughts
There seems to be also another type of research in performance analysis, which in this case also discusses tactical ability. The so-called “ecological dynamics” display self-organizing systems and therefore critique the notational systems. The results in this research (93) states how attackers try to break symmetry with their nearest opponents, as defenders seek to maintain system symmetry by remaining between their own goal and the immediate attacker.

Individuals influence tactical ability/performance of a team. As a result, research constructed “ball flow” to investigate the importance of individuals in a team structure and seems able to demonstrate that flow centrality provide a powerful objective quantification of individual and further team performance (23).


Factors influencing performance

Performance seems to be a very specific index that is influenced by many variables and therefore should be considered in that context.

We also want to state that the factors interfere and therefore some limitations will be present with regards to given references.

Opponent (Successful vs. non-successful teams regarding final latter ranking)
The opponent will have great influence on performance indicators (22, 26, 46, 64). Obviously, the magnitude of influence needs to be considered with regards to your own team’s ability and the opponent. Therefore, many research has investigated with regards to final league standing and as a consequences distinguished between successful and non-successful teams. Successful teams were significant different compared non-successful teams in:

    •    Goals (47)
    •    Shots on goal (47, 64)
    •    Efficacy of shots on goals (ratio of goals per shots) (83)
    •    Possession in general (46)
    •    Position characteristics (such as counterattack) (89)
    •    Possession with 0-4 passes (89)
    •    Successful passes (65)


Furthermore it was distinguished between successful and non-successful teams taking other variables (such as score-line) into account that influence performance indicators.

Especially ball possession seemed to be discussed in this context, revealing some conflicting results. Generally, The successful teams had longer possessions than unsuccessful teams when winning and drawing (39, 70) and no difference were seen when losing. However, successful teams were also observed having longer ball possessions in general (36, 46). Interestingly, unsuccessful teams had lower ball possession when winning compared to loosing (70) however both successful and unsuccessful teams had longer durations of possession when they were losing matches compared to when winning (39).

Successful teams preferred using a pass on the ground into the final third compared with unsuccessful teams, who used aerial passes pre-dominantly (70). Successful teams were also more efficient than their opponents at scoring from set-plays (95).

Score line - Winning vs. drawing vs. losing
Obviously, scoring more then the opponent equals the ultimate performance indicator (14, 95). Especially scoring first was seen as a strong impact on final outcome (3).

However, it was also reported that the score line (if your team is winning or losing) influence performance indicator such as ball possession or distance covered (44, 45, 87).

When loosing, the teams showed the tendency to improve ball possession in mid offensive zones (7). When winning, teams frequently performed defence/attack transition behaviors to get closer to the opponent goal (7). While drawing, teams tended to vary the offensive methods to score a goal (6). The most frequent position to shoot was the center position.

Winning teams showed different profiles from drawing and losing teams in terms of recovering the ball in their own half (center area) and to use penetrative passes into the opponents box (30).

Match location (home vs. away)
I guess everyone has experienced “home advantage” in some stage in his career (22, 30, 80). The home team created significant more possession (44, 46), greater number of turnovers and crosses  (30, 91), corners, passes and shots in the attacking third and in general exhibited more behaviors linked with success such as won tackles, passes completed and won aerial challenges (91). The home team also covered more distance in low-intensity activities (45).

Type of competition (League vs. knock-out system)
There is limited evidence of the type of competition on performance indicators. However, from coaching experience it seems warranted that one of the best teams will win a league (with consist performance over a long(er) period of time), while during a knock-out stage (like in national cups or international tournaments) it seems that the team with suppose to have lower performance also have a chance to win. Lagos et al. (51) stated for knockout stages the role of performance is less important, as there were no statistically significant differences in the performance obtained by winners and losers (51). However, other research (81) shows the importance of consistent performance over all games of a tournament.

Game period
It seemed that game period had an effect on performance parameters (4, 64). Game period had significant effects on the length of offensive actions, the distance covered (64) and more goals were scored as time progresses. The above could be explained by the deterioration in physical conditioning, the tactical play, fluid balance and lapses in concentration (4).

Other factors
In the following paragraphs we would like to list (additional) others factors that will influence performance and therefore its indicators.

Training (hours) experience
Experienced players circulated the ball more in SSG resulting in longer offensive sequences from the entire team, while the non-experienced participants performed faster offensive sequences with a predominance of individual actions (1).

Body mass and muscle mass was related to the total distance covered (73). Moreover, players from successful teams were found to be leaner and more muscular than their unsuccessful counterparts (48).

Psychological factors
Psychological factors were not really discussed throughout the literature, however it was seen that emotional intelligence scores predict team sports performance in national cricket (18).  Emotional intelligence is involved in the capacity to perceive emotions, assimilate emotion-related feelings, understand the information of those emotions, and manage them (56). Emotional intelligence helps individual team members in order to deal with interpersonal and intrapersonal conflicts, enhance communication and commitment, and to accomplish team goals (21). We speculate that emotional intelligence might be seen as a psychological factor in football performance as well.

There is only limited evidence about the effect of fatigue on performance indicators. Fatigue that players appear towards the end of a game, which consequently leads to goal scoring by the opponent team (97). Fatigue affected soccer skills (66, 75) in footballers. The assumption was that pass accuracy is reduced, therefore ball possession and as a consequence the ability to control the match (and therefore performance).

Dismissals will have an effect on performance indicators (11). Players need to cover greater distance, have less recovery time between high-intensity efforts and have more activity, especially in the moderate-intensity level (11).

Dead-ball situations can play a significant role in match outcome. For example up to ~36% of all goals were scored through set-pieces (95, 96).

Not necessarily related to match outcome, however still interesting was the investigation by Pulling et al. (65), who investigated zonal vs. 1-on-1 marking in corners. The authors’ results showed no significant association between the marking set-up and the number of attempts at goal conceded when defending corner kicks. However, teams who applied zonal marking conceded fewer goals and fewer attempts at goal than teams who used one-to-one marking.

Who scores the goals
Interestingly, in successful teams, 62% of the goals are scored by typical attacking players (33). Whereas in unsuccessful teams only 25% of the goals are scored by the same kind of players.

Gender differences
There seemed to be gender differences in performance indicators. One factor seemed to be the physical/physiological differences, which might be responsible for successful long-range shots for example (2).  The women used more heading in general and tried to get closer to the goal before trying to score (2).

Dribbling seemed to be the most important skill to creating scoring opportunities, followed by first touch, passing, and individual defense (90).

Crosses received inside the box and corner kicks revealed good goal scoring opportunities (55).  Individual tactics in womens football was observed by Konstadinidiou et al. 2005 - (41).


Performance (and therefore its indicators) needs to be considered with regards to several situational variables (such as quality of opponent, location of match, type of competition and game period).  In addition, first goal and in general score-line and dismissals will also have an effect on performance. As a result, key performance index seemed to change during the game (22, 45, 87). It seems that teams need to develop a specific performance index (such as how to enter the attacking third) for a specific opponent, at a specific location, in a specific type of competition for a specific time during the match.


Furthermore, the performance index might be individual to specific positions as the technical (85) and physical (61) demands differ. For example, target strikers have different movements (amount and intensity), different technical skills (such as ball possession) compared to central midfielders. However, their shots on goal will be more crucial as they are usually positioned closer to the goal and therefore have greater chance to score.


Generally, efficacy seems to be key offensively (goals per shots) as well as defensively (gaining re-possession quickly) (50, 78). Ball possession (to us) seems to be important in controlling the game, however, not necessarily as an important performance indicator. As it seems having ball possession for a long time does not ensure goals scoring, however is very effective way to control the game when winning.


Creating/cover spaces over large distance on the pitch offensively seems to create opportunities for individual players and therefore lowers chances for interceptions, however, simultaneously increase the demand and the complexity of re-organizing the defense when losing the ball. As a result, counterattacking is a very effective way to win a game, especially for “lower-ranked” in certain situations (away games, less comfortable with ball possession etc).


Set pieces are very important and can decide about winning or loosing as well. Additionally, it seems warrant to scout the opponent and not only to research our own team (88).



1.    Almeida, C.H., A.P. Ferreira, and A. Volossovitch, Offensive sequences in youth soccer: effects of experience and small-sided games. Journal of Human Kinetics, 2013. 36: 97-106.

2.    Althoff, K., J. Kroiher, and E.M. Hennig, A soccer game analysis of two World Cups: playing behavior between elite female and male soccer players. Footwear Science, 2010. 2(1): 51-56.

3.    Armatas, V., et al., Evaluation of goals scored in top ranking soccer matches: Greek "Superleague" 2006-07. Serbian Journal of Sports Sciences, 2009. 3(1): 39-43.

4.    Armatas, V., A. Yiannakos, and P. Sileloglou, Relationship between time and goal scoring in soccer games: Analysis of three World Cups. International Journal of Performance Analysis in Sport, 2007. 7(2): 48-58.

5.    Arnason, A., et al., Physical fitness, injuries, and team performance in soccer. Medicine and Science in Sports and Exercise, 2004. 36(2): 278-285.

6.    Barraeira, D., et al., Ball recovery patterns as a performance indicator in elite soccer. Journal of Sports Engineering and Technology, 2014. 228(1): 61-72.

7.    Barreira, D., J. Garganta, and T. Anguera, In search of nexus between attacking game-patterns, match status and type of ball recovery in European Soccer Championship 2008, in Research Methods and Performance Analysis, M. Hughes, et al., Editors. 2011, University of West Hungary. p. 226-237.

8.    Bradley, P.S., et al., The effect of playing formation on high-intensity running and technical profiles in English FA Premier League soccer matches. J Sports Sci, 2011. 29(8): 821-830.

9.    Bradley, P.S., et al., High-intensity activity profiles of elite soccer players at different performance levels. J Strength Cond Res, 2010. 24(9): 2343-2351.

10.    Carling, C., Interpreting Physical Performance in Professional Soccer Match-Play: Should We be More Pragmatic in Our Approach? Sports Medicine, 2013.

11.    Carling, C. and J. Bloomfield, The effect of an early dismissal on player work-rate in a professional soccer match. J Sci Med Sport, 2010. 13(1): 126-128.

12.    Carling, C., et al., Squad management, injury and match performance in a professional soccer team over a championship-winning season. Eur J Sport Sci, 2014: 1-10.

13.    Castellano, J., D. Casamichana, and C. Lago, The Use of Match Statistics that Discriminate Between Successful and Unsuccessful Soccer Teams. Journal of Human Kinetics, 2012. 31: 139-147.

14.    Clemente, F., et al., Team's performance on FIFA U17 World Cup 2011: Study based on notational analysis. Journal of Physical Education and Sport, 2012. 12(1): 13-17.

15.    Collet, C., The possession game? A comparative analysis of ball retention and team success in European and international football, 2007-2010. Journal of Sports Sciences, 2013. 31(2): 123-136.

16.    Cometti, G., et al., Isokinetic strength and anaerobic power of elite, subelite and amateur French soccer players. International Journal of Sports Medicine, 2001. 22(1): 45-51.

17.    Correia, V., et al., From recording discrete actions to studying continuous goal-directed behaviours in team sports. Journal of Sports Sciences, 2013. 31(5): 546-553.

18.    Crombie, D., C. Lombard, and T. Noakes, Emotional intelligence scores predict team sports performance in national cricket competition. International Journal of Sports Science & Coaching, 2009. 4(2): 2009.

19.    Dellal, A., et al., Small-sided games in soccer: Amateur vs. professional players' physiological responses, physical, and technical activities. Journal of Strength and Conditioning Research, 2011. 25(9): 2371-2381.

20.    Di Salvo, V., et al., Analysis of high intensity activity in Premier League soccer. International Journal of Sports Medicine, 2009. 30(3): 205-212.

21.    Druskat, V.U. and S.B. Wolff, Building the Emotional Intelligence of Groups. Harvard Business Review, 2001. 79(3): 80-90.

22.    Duarte, R., et al., Capturing complex, non-linear team behaviours during competitive football performance. Journal of Systems Science and Complexity, 2013. 26: 62-72.

23.    Duch, J., J.S. Waitzman, and L.A. Amaral, Quantifying the performance of individual players in a team activity. PLoS One, 2010. 5(6): e10937.

24.    Ensum, J., R. Pollard, and S. Taylor. Applications of logistic regression to shots at goal in association football: calculation of shot probabilities, quantification of factors and player/team. in Journal of Sport Sciences. 2004.

25.    Fatemeh, H., et al., Effectiveness of types of individual defense performance in achieving success. International Research Journal of Applied and Basic Science, 2012. 3(4): 891-895.

26.    Folgado, H., et al., Competing with Lower Level Opponents Decreases Intra-Team Movement Synchronization and Time-Motion Demands during Pre-Season Soccer Matches. PLoS One, 2014. 9(5): e97145.

27.    Frencken, W., et al., Variability of inter-team distances associated with match events in elite-standard soccer. Journal of Sports Sciences, 2012. 30(12): 1207-1213.

28.    Garganta, J., Trends of tactical performance analysis in team sports: bridging the gap between research, training and competition. Revista Portuguesa de Ciências do Desporto, 2009. 9(1): 81-89.

29.    Garganta, J., J. Maia, and F. Basto. Analysis of goal-scoring patterns in European top level soccer teams. in Third World Congress of Science and Soccer. 1997. London: E & FN.

30.    Gomez, M.A., et al., Effects of game location and final outcome on game-related statistics in each zone of the pitch in professinal football. European Journal of Sport Science, 2012. 12(5): 393-398.

31.    Helgerud, J., et al., Aerobic endurance training improves soccer performance. Medicine and Science in Sports and Exercise, 2001. 33(11): 1925-1931.

32.    Horn, R., R. Williams, and J. Ensum, Attacking in central areas: A preliminary analysis of attacking play in the 2001-2002 Premiership season. Insight, 2002. 3(5): 28-31.

33.    Hughes, M. and S. Churchill, Attacking profiles of successful and unsuccessful teams in Copa America 2001. Journal of Sport Sciences, 2004. 22(6): 505.

34.    Hughes, M. and I. Franks, Analysis of passing sequences, shots and goals in soccer. Journal of Sports Sciences, 2005. 23(5): 509-514.

35.    Hughes, M.D. and R.M. Bartlett, The use of performance indicators in performance analysis. Journal of Sports Sciences, 2002. 20(10): 739-754.

36.    James, N., P.D. Jones, and S.D. Mellalieu, Possession as a performance indicator in soccer as a function of successful and unsuccessful teams. Journal of Sport Sciences, 2004. 22(6): 507-508.

37.    Jankovic, A., et al., Influence of certain tactical attacking patterns on the result achieved by the teams participants of the 2010 FIFA World Cup in South Africa. Physical Culture, 2010. 65(1): 34-45.

38.    Johnson, K. and A. Murphy, Passing and goal scoring characteristics in the Australian A-League. Journal of Science and Medicine in Sport, 2010. 12: e118.

39.    Jones, P.D., N. James, and S.D. Mellalieu, Possession as a performance indicator in soccer. International Journal of Performance Analysis in Sport, 2004. 4(1): 98-102.

40.    Kapidzic, A., et al., Differences in indicators of situational effectiveness between teams that compete in different competitions ranks. Sports SPA, 2012. 9(1): 49-57.

41.    Konstadinidou, X. and N. Tsigilis, Offensive playing profiles of football teams from the 1999 Women’s World Cup Finals. International Journal of Performance Analysis in Sport, 2005. 5(1): 61-71.

42.    Krustrup, P., et al., The yo-yo intermittent recovery test: physiological response, reliability, and validity. Medicine and Science in Sports and Exercise, 2003. 35(4): 697-705.

43.    Krustrup, P., et al., Physical demands during an elite female soccer game: importance of training status. Medicine and Science in Sports and Exercise, 2005. 37(7): 1242-1248.

44.    Lago, C., The influence of match location, quality of opposition, and match status on possession strategies in professional association football. Journal of Sports Sciences, 2009. 27(13): 1463-1469.

45.    Lago, C., et al., The effects of situational variables on distance covered at various speeds in elite soccer. European Journal of Sport Science, 2010. 10(2): 103-109.

46.    Lago, C. and R. Martin, Determinants of possession of the ball in soccer. Journal of Sports Sciences, 2007. 25(9): 969-974.

47.    Lago-Ballesteros, J. and C. Lago-Penas, Performance in team sports: Identifying the keys to success in soccer. Journal of Human Kinetics, 2010. 25: 85-91.

48.    Lago-Penas, C., et al., Anthropometric and physiological characteristics of young soccer players according to their playing positions: relevance for competition success. Journal of Strength and Conditioning Research, 2011. 25(12): 3358-3367.

49.    Lago-Penas, C. and A. Dellal, Ball possession strategies in elite soccer according to the evolution of the match-score: the influence of situational variables. Journal of Human Kinetics, 2010. 25: 93-100.

50.    Lago-Penas, C., et al., Game-related statistics that discriminated winning, drawing and losing teams from the Spanish soccer league. Journal of Sports Science and Medicine, 2010. 9: 288-293.

51.    Lagos, C., Are winners different from losers? Performance and chance in the FIFA World Cup Germany 2006. International Journal of Performance Analysis in Sport, 2007. 7(2): 36-47.

52.    Lames, M. and T. McGarry, On the search for reliable performance indicators in game sports. 2007.

53.    Luhtanen, P., et al., A comparative tournament analysis between the EURO 1996 and 2000 in soccer. International Journal of Performance Analysis in Sport, 2004. 4(1): 74-82.

54.    Machado, J., D. Barreira, and J. Garganta, Attacking game-patterns in Soccer. A sequential analysis of the World Cup 2010 winner team, in Research Methods and Performance Analysis, M. Hughes, et al., Editors. 2011, University of West Hungary. p. 238-245.

55.    Mara, J.K., K.W. Wheeler, and K. Lyons, Attacking strategies that lead to goal scoring opportunities in high level women's football. International Journal of Sports Science & Coaching, 2012. 7(3): 2012.

56.    Mayer, J.D., D.R. Caruso, and P. Salovey, Emotional intelligence meets traditional standards for an intelligence. Intelligence, 1999. 27(4): 267-298.

57.    McGarry, T., Applied and theoretical perspectives of performance analysis in sport: Scientific issues and challenges. International Journal of Performance Analysis in Sport, 2009. 9(1): 128-140.

58.    McGarry, T., et al., Sport competition as a dynamical self-organizing system. Journal of Sports Sciences, 2002. 20(10): 771-781.

59.    Mohr, M., P. Krustrup, and J. Bangsbo, Match performance of high-standard soccer players with special reference to development of fatigue. Journal of Sports Sciences, 2003. 21(7): 519-528.

60.    Nic, J., Notational analysis in soccer: past, present and future. International Journal of Performance Analysis in Sport, 2006. 6(2): 67-81.

61.    O'Donoghue, P.G., Time-motion analysis of work-rate in English FA Premier League soccer. International Journal of Performance Analysis in Sport, 2002. 2(1): 36-43.

62.    Oberstone, J., Differentiating the top English Premier League Football Clubs from the rest of the pack: Identifying the keys to success. Journal of Quantitative Analysis in Sports, 2009. 5(3): Article 10.

63.    Olsen, E., An analysis of goal scoring strategies in the World Championships in Mexico. Science and Football, ed. T. Reilly, et al. 1988, London. 373-376.

64.    Pratas, J., A. Volossovitch, and A.P. Ferreira, The effect of situational variables on teams’ performance in offensive sequences ending in a shot on goal. A case Studs. The Open Sports Sciences Journal, 2012. 5: 193-199.

65.    Pulling, C., R. Matthew, and R. Thomas, Defending corner kicks: Analysis from the English Premier League. International Journal of Performance Analysis in Sport, 2013. 13(1): 135-148.

66.    Rampinini, E., et al., Technical performance during soccer matches of the Italian Serie A league: effect of fatigue and competitive level. Journal of Science and Medicine in Sport, 2009. 12(1): 227-233.

67.    Redwood-Brown, A., Passing patterns before and after goal scoring in FA Premier League Soccer. International Journal of Performance Analysis in Sport, 2008. 8(3): 172-182.

68.    Redwood-Brown, A., C. Bussell, and H.B. Singh, The impact of different standards of opponents on observed player performance in the English Premier League. Journal of Human Sport and Exercise, 2012. 7(2): 341-355.

69.    Reep, C. and B. Benjamin, Skill and chance in ball games. Journal of the royal Statistical Society, 1971. A: 623-629.

70.    Rees, G., et al., The effect of match status on attacking strategies in the English Championship, in Research Methods and Performance Analysis, M. Hughes, et al., Editors. 2011, University of West Hungary. p. 172-177.

71.    Rees, G., et al., The use of zone 14 as a strategic attacking area in the English Championship, in Research Methods and Performance Analysis, M. Hughes, et al., Editors. 2011, University of West Hungary. p. 205-211.

72.    Ridgewell, A., Passing patterns before and after scoring in the 2010 FIFA World Cup. International Journal of Performance Analysis in Sport, 2011. 11(3): 562-574.

73.    Rienzi, E., et al., Investigation of anthropometric and work-rate profiles of elite South American international soccer players. Journal of Sports Medicine and Physical Fitness, 2000. 40(2): 162-169.

74.    Rostgaard, T., et al., A test to evaluate the physical impact on technical performance in soccer. Journal of Strength and Conditioning Research, 2008. 22(1): 283-292.

75.    Russell, M., D. Benton, and M. Kingsley, The effects of fatigue on soccer skills performed during a soccer match simulation. International Journal of Sports Physiology and Performance, 2011. 6(2): 221-233.

76.    Saito, K., M. Yoshimura, and T. Ogiwara, Pass appearance time and pass attempts by teams qualifying for the second stage of FIFA World Cup 2010 in South Africa. Football Science, 2013. 10: 65-69.

77.    Scoulding, A., N. James, and A. Taylor, Passing in the soccer world cup 2002. International Journal of Performance Analysis in Sport, 2004. 4(2): 36-41.

78.    Scoulding, A., N. James, and J. Taylor, Passing the the soccer world cup 2002. International Journal of Performance Analysis in Sport, 2004. 4(2): 36-41.

79.    Seabra, F. and L. Dantas, Space definition for match analysis in soccer. International Journal of Performance Analysis in Sport, 2006. 6(2): 97-113.

80.    Seckin, A. and R. Pollard Home advantage in Turkish professional soccer. MPRA Munich Personal RePEc Archive, 2007.

81.    Shafizadeh, M., M. Taylor, and C.L. Penas, Performance consistency of international soccer teams in euro 2012: a time series analysis. J Hum Kinet, 2013. 38: 213-26.

82.    Sotiropoulos, A., M. Mitrotasios, and A. Traulos. Comparison in goal scoring patterns between Greek professional and amateur teams. in 1st International Scientific Congress in Soccer. 2005. Trikala.

83.    Szarc, A., Efficacy of successful and unsuccessful soccer teams taking part in finals of Champions League. Research Yearbook, 2007. 13(2): 221-225.

84.    Szczepanski, L., Measuring the effectiveness of strategies and quantifying players’ performance in football. International Journal of Performance Analysis in Sport, 2008. 82(2): 55-56.

85.    Taylor, J.B., S.D. Mellalieu, and N. James, Behavioural comparisons of positional demands in professional soccer. International Journal of Performance Analysis in Sport, 2004. 4(1): 81-97.

86.    Taylor, J.B., S.D. Mellalieu, and N. James, A comparison of individual and unit tactical behaviour and team strategy in professional soccer. International Journal of Performance Analysis in Sport, 2005. 5(2): 87-110.

87.    Taylor, J.B., et al., The influence of match location, quality of opposition, and match status on technical performance in professional association football. Journal of Sports Sciences, 2008. 26(9): 885-895.

88.    Tenga, A., et al., Effect of playing tactics on goal scoring in Norwegian professional soccer. Journal of Sports Sciences, 2010. 28(3): 237-244.

89.    Tenga, A. and E. Sigmundstad, Characteristics of goal-scoring possessions in open play: Comparing the top, in-between and bottom teams form professional soccer league. International Journal of Performance Analysis in Sport, 2011. 11(3): 545-552.

90.    Thomas, C., G. Fellingham, and P. Vehrs, Development of a notational analysis system for selected soccer skills of a Women’s college team. Measurement in Physical Education and Exercise Science, 2009. 13: 108-121.

91.    Tucker, W., et al., Game location effects in professional soccer: A case study. International Journal of Performance Analysis in Sport, 2005. 5(2): 23-35.

92.    Turner, B.J. and M.G.L. Sayers, The influence of transition speed on event outcomes in a high performance football team. International Journal of Performance Analysis in Sport, 2010. 10(3): 207-220.

93.    Vilar, L., et al., The role of ecological dynamics in analysing performance in team sports. Sports Medicine, 2012. 42(1): 1-10.

94.    Wisløff, U., J. Helgerud, and J. Hoff, Strength and endurance of elite soccer players. Medicine and Science in Sports & Exercise, 1998. 30(3): 462-467.

95.    Wright, C., et al., Factors associated with goals and goal scoring opportunities in professional soccer International Journal of Performance Analysis in Sport, 2011. 11(3): 438-449.

96.    Yiannakos, A. and V. Aramats, Evaluation of the goal scoring patterns in European Championship in Portugal 2004. International Journal of Performance Analysis in Sport, 2004. 6(1): 178-188.

97.    Yiannakos, A. and V. Armatas, Evaluation of the goal scoring patterns in European Championship in Portugal 2004. International Journal of Performance Analysis in Sport, 2006. 6(1): 178-188.

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