diff --git "a/52ab8dab-df77-4410-a98d-5fd898ff4ed0.json" "b/52ab8dab-df77-4410-a98d-5fd898ff4ed0.json" new file mode 100644--- /dev/null +++ "b/52ab8dab-df77-4410-a98d-5fd898ff4ed0.json" @@ -0,0 +1,40 @@ +{ + "interaction_id": "52ab8dab-df77-4410-a98d-5fd898ff4ed0", + "search_results": [ + { + "page_name": "Analysis of Scoring Sequences in Matches of the Portuguese Premier ...", + "page_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231341/", + "page_snippet": "The aim of this study was to examine the sequences of the first two goals scored in soccer matches in accordance with a range of different match contexts. Data from 1506 matches played in the Portuguese Premier League during six consecutive competitive ...Most of these studies focused only on the analysis of the first goal effect on the match outcome, and did not examine the role of goals subsequently scored. A recent study of Lago-Pe\u00f1as et al. (2016) that analysed games played in the most important European domestic leagues (English FA Premier League, French Ligue 1, Spanish La Liga, Italian Serie A and German Bundesliga) in the 2014/2015 season demonstrated that home teams scored first in 57.8% of games and obtained in total 84.85% of points won in these games. In the 2015/16 season, 20% of matches ended with a total of two goals (i.e. the sum of total goals scored per game by both teams): 10% finished 1-1 (home draw, 38 matches), 7% 2-0 (home win, 21 matches) and 3% 0-2 (home defeat, 10 matches). The home advantage effect was confirmed in these matches. The second goal may be the equalizer (0-1 to 1-1, or 1-0 to 1-1) or the goal, which enables a team to double their advantage (1-0 to 2-0, or 0-1 to 0-2). The anticipation of temporal localization of the second goal associated to its nature (i.e., goal which creates advantage or recovers from score disadvantage) seems to be useful for a timely adaptation of the team's tactics. On the one hand, fatigue, which is greatest at the end of each half, leads to an increase in the number of technical and tactical errors, which may lead to more goal scoring opportunities. On the other hand, the little time remaining until the end of each half encourages players to use their last chances to score a goal that also may influence the match outcome.", + "page_result": "\n \n\n\n\n\n\n\n\n \n \n\n \n \n \n \n\n \n \n \n \n \n\n \n \n \n\n\n\n \n\n \n \n\n\n Analysis of Scoring Sequences in Matches of the Portuguese Premier League - PMC\n\n \n \n \n \n\n \n \n\n \n \n \n \n \n \n \n \n\n\n\n \n \n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n \n\n\n \n\n\n\n\n\n \n \n \n Back to Top\n \n \n\n Skip to main content\n \n
\n
\n
\n
\n \"U.S.\n

An official website of the United States government

\n \n Here's how you know\n \n
\n
\n \n
\n \n
\n

\n The .gov means it\u2019s official.\n
\n Federal government websites often end in .gov or .mil. Before\n sharing sensitive information, make sure you\u2019re on a federal\n government site.\n

\n
\n
\n
\n \n
\n

\n The site is secure.\n
\n The https:// ensures that you are connecting to the\n official website and that any information you provide is encrypted\n and transmitted securely.\n

\n
\n
\n
\n \n
\n
\n
\n\n\t
\n\t\t
\n\n
\n \n \"NIH\n \n
\n\n\t\t\t
\n\t\t\t\tLog in\n\t\t\t\t\n\t\t\t
\n\n\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\n\t\t\t\t\t\t

Account

\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\tLogged in as:
\n\t\t\t\t\t\tusername\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t
\n\n\t\t
\n\t
\n
\n
\nAccess keys\nNCBI Homepage\nMyNCBI Homepage\nMain Content\nMain Navigation\n
\n
\n\t
\n
\n\n\n \n \n\n\n \n \n\n
\n \n
\n
\n
\n

\n \n Preview improvements coming to the PMC website in October 2024.\n Learn More or\n Try it out now.\n \n

\n
\n
\n
\n \n
\n \n\n \n \n \n
\n
\n
\n \n \n \n\n \n \n
\n \n
\n \n\n
\n\n \n \n\n
\n \n
\n
\n
\n \n \n \n\n
\n \n
\n As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with,\n the contents by NLM or the National Institutes of Health.
\n Learn more:\n PMC Disclaimer\n |\n \n PMC Copyright Notice\n \n
\n\n
\n \n \n
\"Logo\"Link
\n \n \n
\n
\n \n
J Hum Kinet. 2018 Sep; 64: 255\u2013263.
Published online 2018 Oct 15. doi:\u00a010.1515/hukin-2017-0199
PMCID: PMC6231341
PMID: 30429916

Analysis of Scoring Sequences in Matches of the Portuguese Premier League

José M. Pratas

1CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa, Lisboa\nPortugal

Find articles by José M. Pratas

Anna Volossovitch

1CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa, Lisboa\nPortugal

Find articles by Anna Volossovitch

Ana I. Carita

2CIPER, Faculdade de Motricidade Humana, BIOLAD, Universidade de Lisboa, Portugal, Estrada da Costa, 1495-688, \nCruz Quebrada, Portugal

Find articles by Ana I. Carita
1CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa, Lisboa\nPortugal
2CIPER, Faculdade de Motricidade Humana, BIOLAD, Universidade de Lisboa, Portugal, Estrada da Costa, 1495-688, \nCruz Quebrada, Portugal
*José M. Pratas Affiliation: CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa Address: Estrada da Costa, 1495-688 Cruz Quebrada, Lisboa, Portugal Tel: +351 965220648 Fax: + 351 214144712 tp.aobsilu.hmf@satarpmj
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Abstract

The aim of this study was to examine the sequences of the first two goals scored in soccer matches in accordance with a range of different match contexts. Data from 1506 matches played in the Portuguese Premier League during six consecutive competitive seasons (2009-10 to 2014-2015) were analysed using descriptive statistics and the chi-square test in order to verify the association between variables and a Cox regression analysis was used to predict the time the second goal was scored in function of the time of the first goal scored in the match and the scoreline. The results revealed a higher frequency of the second goals being scored in the second half of a match (58%) and in the last 5 min periods of each half. A positive association was found for home teams and score-doubling goals (58%), as well as for away teams and score-equalizing goals (56%). For home and away teams the score-doubling goal of a match was strongly and positively associated with a win outcome for home (93%) and away teams (92%), while the score-equalizing goals were associated with a draw (home and away teams: 44%) and loss outcome (home: 33% and away teams: 32%). Finally, the Cox model showed that if the first goal was scored in the second half of the match, the probability of the second goal being scored was three times higher compared to the first half.

Key words: game analysis, soccer, survival analysis

Introduction

In soccer, it has been demonstrated that performance of teams can be influenced by the scoreline (Lago-Peñas, 2012; Gómez et al., 2013). Soccer players perform significantly less high-intensity activity when winning than when losing or when the score is tied (Lago et al., 2010). It was also shown that teams had longer periods of possession in matches when they were losing than when they were winning (Lago-Peñas and Dellal, 2010; Lago-Peñas and Gomez-Lopez, 2014), teams played more in the attack and defensive zones when the score was level (Lago, 2009) and final-third entries were greater when teams were 1 goal down than when they were 1 goal up (Lago-Peñas and Gomez-Lopez, 2014). Findings also showed that shots on goal decreased by 14.1% and 14.45% when teams were 1 goal up and when the scores were level, respectively (Lago-Peñas and Gomez-Lopez, 2014) and when a team was drawing or winning, the probability of reaching the goal decreased by 43 and 53%, respectively (Lago-Ballestero et al., 2012).

The score evolution in time is an important situational factor that may influence the team performance during the match and it also allows to identify the critical moments of the game (Leite, 2013; Njororai, 2014). In low scoring games, each goal can be considered a critical incident that influences the course of the game (Ferreira, 2013). Studies conducted with different professional soccer leagues have shown that the team which scores first in a match has a higher probability of winning, and the home team is more likely to score first than the opposing team (Molinuevo and Bermejo, 2012; Tenga, 2012; Pratas et al., 2016). Most of these studies focused only on the analysis of the first goal effect on the match outcome, and did not examine the role of goals subsequently scored. A recent study of Lago-Peñas et al. (2016) that analysed games played in the most important European domestic leagues (English FA Premier League, French Ligue 1, Spanish La Liga, Italian Serie A and German Bundesliga) in the 2014/2015 season demonstrated that home teams scored first in 57.8% of games and obtained in total 84.85% of points won in these games. On the contrary, when the away team scored first, they obtained only 76.25% of subsequent points.

The average number of goals scored per game in each of the major European soccer leagues is not more than three goals per match. Moreover, scores of 2-0 and 1-1 have been two of the five most frequently recorded full-time scores in the 5 best leagues in Europe (England, France, Germany, Italy and Spain) in recent seasons (Anderson and Sally, 2013). Interestingly, in the 2015-16 season, 1-1 was the most common result in these leagues (http://www.soccerstats.com) The same trend was observed in the Portuguese Premier League. In the 2015/16 season, 20% of matches ended with a total of two goals (i.e. the sum of total goals scored per game by both teams): 10% finished 1-1 (home draw, 38 matches), 7% 2-0 (home win, 21 matches) and 3% 0-2 (home defeat, 10 matches). The home advantage effect was confirmed in these matches. The home teams of the Portuguese Premier League scored 80 goals, while away teams scored 58 goals.

The advantage of playing at home may be related to several factors reported in literature, such as crowd support (Wolfson et al., 2005), travel (Pollard et al., 2008), familiarity with the game environment (Loughead et al., 2003), referees (Brandão et al., 2011) and territoriality aspects (Sampedro and Prieto, 2011). When the local team scores first, it excites fans and increases their interest in the match, while the away team’s early leading may distract the audience from the match (Courneya, 1990). From the socio-psychological point of view, the local public support is considered by own fans as decisive, which can reinforce the self-esteem of players and increase social identity that leads to improvement of team performance and a reduction of the negative effects of stress and anxiety (Wolfson et al., 2005). From the strategic and tactical point of view, scoring first and gaining a score advantage allow the winning team to extend the range of tactical options, for instance by creating more counterattack opportunities against the opposite team, which can opt for more risky strategies in the game.

The second goal might have a decisive impact on the match outcome, which is not less than the influence of the first goal (Anderson and Sally, 2013). The second goal may be the equalizer (0-1 to 1-1, or 1-0 to 1-1) or the goal, which enables a team to double their advantage (1-0 to 2-0, or 0-1 to 0-2). The anticipation of temporal localization of the second goal associated to its nature (i.e., goal which creates advantage or recovers from score disadvantage) seems to be useful for a timely adaptation of the team's tactics. However, there is a lack of data in the literature to the second goal of a match. One of the few studies which analysed this goal has been conducted by Nevo and Ritov (2012). The interaction between two random goal-scoring times (of the first and second goals) during a soccer match was examined in 760 games played from 2008 to 2010 (two full seasons) in the English Premier League. Using survival analysis methods the authors reported that the first goal occurrence could either expedite or impede the next goal, depending on the time it was scored.

In order to provide a better understanding of which factors influence the second goal being scored, it would be useful to examine how the time of the second goal is associated with a range of different match contexts. A soccer match is a complex dynamic process, in which certain events influence the subsequent course of the match, and this influence must be considered in analysis. In order to explain the relationship between different events, it is necessary to extract information regarding match progress using time as a variable of interest (Venturelli et al., 2011). Several studies have suggested using survival (also known as time-event) analysis for this purpose (Castilla, 2007; Nevo and Ritov, 2012). This tool involves the use of regression methods for explaining the relationship between independent variables and the time of an event of interest and it is considered to be the most suitable means for characterizing and explaining match progress compared to other tools commonly used in soccer performance analysis (Barros et al., 2009; Del Corral et al., 2008).

Thus, the first aim of this study was to analyse the association between the type of the second goal scored in a match (i.e. goal that increased the leading team's advantage or the goal that re-established equality in the scoreline) and the match venue, as well as the final match outcome. Secondly, the study aimed to examine the influence of the time when the first goal was scored and the current scoreline on the probability of the second goal being scored in a match. This knowledge could help coaches anticipate match scenarios and adopt in a timely manner the most appropriate tactics for the remaining part of the match.

Methods

Sample

The sample consisted of 1506 matches played in the Portuguese Premier League during six consecutive competitive seasons (from 2009-10 to 2014-2015). All data were collected from the official League website (http://www.ligaportugal.pt)

Statistical Analysis

Descriptive statistics and chi-square analysis were performed to examine second goals scored during the game period and the association between the type of the second goal being scored (score-doubling or score-equalizing) and the match venue as well as the final match outcome. In 29% of matches (443 out of 1506), the second goal was not scored. About 9% of matches (135 out of 1506) ended goalless and in 20% of matches (308 out of 1506) just one goal was scored. Thus, data were collected from 1063 matches in which the second goal was scored by a home team (586).

A Cox proportional hazards (PH) model was used to estimate the time of the second goal as a function of the time of the first goal in a match and the scoreline.

In survival analysis, the home team was considered as the reference team and the second goal of the match, when it was scored by the home team, was considered as the event of interest. If the away team scored the second goal of the match, this goal was considered as a censored observation. The response variable in the Cox Model was the time elapsed from the time when the first goal in a match was scored to the occurrence of the second goal, considered as the event of interest. Second goals scored in additional time in the first and second halves were recorded at the 45th and 90th min, respectively. Matches in which no goals or only one goal was scored were not considered. Almost half of 1063 matches (477) were censored because the away team scored the second goal of the match.

The Cox model relies on the assumption of the proportionality of hazards, implying that the factors analysed have a constant impact on the hazard over time (Broström, 2012). The proportionality assumption of data was checked to ensure a non-violation of the proportionality assumption. For this purpose the function cox.zph in the survival package, version 2.37-7 was used (Therneau, 2015). The p-value obtained in this function was significant (p < 0.05) and indicated that the proportionality assumption was not met for the variable time of the first goal in a match. Since the time of the first goal is a continuous covariate, it was necessary to categorize it in order to ensure the proportionality assumption. First, the distribution of the time of first goals was checked using a histogram, which showed that the interval of time during which first goals were scored may reasonably be split into four equal-length intervals using the cut function. The time of the first goal in a match is expressed as time in minutes from the start of the match and categorized in accordance with four classes: first period [0-15 min], second period [16-30 min], third period [31-45 min] and second half [46-90 min]. The current scoreline was also considered as a categorical variable in accordance with two classes: a score-doubling goal (the second goal that doubled the advantage) and an equalizing goal.

All statistical analysis was performed using Software R, version 3.0.2. For all analyses, statistical significance was set at p < 0.05.

Results

Data analyses showed that significantly more second goals were scored in the second half of matches (χ2 = 28.81, p < 0.05) compared to the first half (58% v. 42%, respectively). The highest frequency of the second goal being scored was recorded in the last 5 min periods of each half (Figure 1).

\"An

Frequency of the second goal of the match

As it can be seen in Table 1, 55% of second goals were scored by home teams and 45% by away teams. Home teams presented a greater percentage (58%) of second goals that doubled score advantage (1-0 to 2-0, or 0-1 to 0-2) as compared with away teams (44%). On the other hand, away teams scored a higher percentage (56%) of goals, which restored the score equality (1-0 to 1-1, or 0-1 to 1-1) in comparison with home teams (42%). The results of the chi-square test (χ2 = 20.23, p < 0.05) established a significant association between the match venue and the type of the second goal scored.

Table 1

Frequency, percentage and chi-square value for the second goal scored by home and away teams cross-referenced with the type of the second goal

Type ofsecond goal
Second goal of match1Score--0 to 2-doubling 0, or 0-1 to 0-2Score-equalizing 1-0 to 1-1, or 0-1 to 1-1nχ2
Home Team338 (58%)b248 (42%)a586 (55%)
Away Team209 (44%)a268 (56%)b477 (45%)20.23*
Total1063

Statistical significance

bPositive association adjusted residual >1.96
aNegative association adjusted residual <-1.96
*p < 0.05

Table 2 shows a significant association between the type of the second goal scored and the match outcome (χ2 = 521.08, p < 0.05). The team, which scored the second goal, won the match in 59% of cases. The score-doubling goal was strongly positively associated with a win outcome and the equalizing goals with a draw and loss outcome.

Table 2

Frequency, percentage, and chi-square value for the type of the second goal cross-referenced with the outcome of a match

Type of the secondOutcomeTotalχa
goalWinDrawLoss
Score-doubling506 (93%)b33 (6%)a8 (1%)a547
Score-equalizing123 (24%)a225 (44%)b168 (32%)b516521.08*
629 (59%)258 (24%)176 (17%)1063

Statistical significance

aNegative association adjusted residual <-1.96
*p < 0.05;

Table 3 displays a statistically significant association between the match outcome and the type of the second goal scored by home teams (χ2= 298.85, p < 0.05) as well as by away teams (χ2 = 218.55, p < 0.05).

Table 3

Frequency, percentage and chi-square value for the type of the second goal scored by home and away teams cross-referenced with the match outcome

Type of second goalWinOutcome DrawLossTotalχ2
Score-doubling314 (93%)b17 (5%)b7 (2%)b338
HomeScore-equalizing58 (23%)b108 (44%)b82 (33%)b248298.85*
teamTotal37212589586
AwayScore-doubling192 (92%)b16 (7%)b1 (1%)b209
Score-equalizing65 (24%)b117 (44%)b86 (32%)b268218.55*
teamTotal25713387477
1063

Statistical significance

bPositive association (adjusted residual >1.96)
bNegative association (adjusted residual <-1.96)
*p < 0.05

When home teams scored the score-doubling goal, they won 93% of matches, and when they scored the score-equalizing goal, they won 23%, drew 44% and lost 33% of matches. Away teams, when they scored the score-doubling goal, achieved victory in 92% of matches, and after scoring the equalizing goal they won 24%, drew 44% and lost 32% of matches.

Additionally, the frequency of the score-doubling goal of a match scored by home and away teams was positively associated with a win outcome and negatively associated with draw and loss outcomes. Draw and loss outcomes were significantly and positively associated with the equalizing goal of a match scored by both home and away teams and negatively associated with a win outcome.

The variables estimated using the Cox proportional hazard regression model (Table 4) revealed a significant positive effect of the time of the first goal on the next goal occurrence, i.e. first goal occurrence in later game periods steadily increased the probability of the second goal in a match being scored. At the same time, for home teams the current scoreline had no significant effect on the second goal occurrence in a match.

Table 4

Cox proportional hazard regression model

VariableCoefficientHazard Ratiop
Time of the first goal
0-151.00
16-300.3491.4190.001*
31-450.6451.906<0.001*
Second half1.1313.099<0.001*
Scoreline
Score-equalizing goal1.00
Score-doubling goal0.00011.000.998

Statistical significance:

*p<0.05

Discussion

In the present study, the time of the second goal scored in soccer matches was analysed. As it can be seen in Figure 1, in general, teams scored a larger number of second goals in the second half of matches, and the highest number of goals was scored during the last minutes of each half. Previous studies reported that the frequency of goals scored during a match was time-dependent, more goals were scored in the second half of matches and in the last 10- and 15-min periods of each half (Armatas et al., 2009; Dobson and Goddard, 2010). The tendency for increasing scoring rates over the time of a match could be attributed to physiological and tactical factors that influence teams’ performance. On the one hand, fatigue, which is greatest at the end of each half, leads to an increase in the number of technical and tactical errors, which may lead to more goal scoring opportunities. On the other hand, the little time remaining until the end of each half encourages players to use their last chances to score a goal that also may influence the match outcome.

In low-scoring team games such as soccer, scoring the second goal in a match could be crucial for winning. The results of this study confirm the effect of home advantage on the second goal being scored and subsequent victory in matches in the Portuguese professional Football League (Table 1). It was also found that the match venue had an impact on the second type of the goal scored. Score-doubling goals were positively associated with home matches, while equalizing goals were associated with away matches. Courneya and Carrón (1992) and Wolfson et al. (2005) suggested that an early lead in a match caused greater excitement and involvement of fans when the home team scored first. Score advantage reduces the negative effects of stress and anxiety and positively influences team’s performance, which could help home teams to enhance their score advantage.

The higher number of equalizing goals scored by away teams may be related to the defensive strategic behaviour adopted by home teams when they are winning and trying to maintain their score advantage. This tendency was reported by Dobson and Goddard (2010) for matches played in the English Premier League and by Lago-Peñas and Gómez-López (2014) for the Spanish Professional League matches, where teams used defensive strategy when winning and attacked more when losing in order to maintain the score advantage or to change the current result, respectively. A team that switches from a defensive to attacking style usually increases their own and also opponent’s probabilities to score (Armatas et al., 2009; Dobson and Goddard, 2010).

Home and away teams, which scored a doubling goal, won the majority of matches. Additionally, the doubling goals were positively associated with a winning match outcome. Since soccer is a low-scoring team sport, this result was expected. At the same time, the equalizing goals were positively associated with the draw and loss outcome; however, home teams and away teams both avoided defeat in approximately 68% of matches after scoring an equalizing goal, thus this goal was extremely important.

Regardless of the type of a goal (score-doubling or equalizing), scoring in soccer always has an impact on the subsequent course of the game, influencing players mentally and frequently leading to tactical adjustments of team’s play. Survival analysis demonstrated that the first goal scored in a match had a significant positive effect on the probability of the next goal being scored, and this probability was dependent on time, when the first goal of the match was scored (Table 4). Cox model variables revealed that the probability of the second goal of the match being scored by home teams gradually increased as a match progressed. When the first goal of the match was scored in the second or third 15-min period of the first half, the probability of home teams scoring the second goal increased by 42% and 190.6% respectively, as compared with the situation when the first goal of a match was scored in the first 15-min period of the first half.

Moreover, if the first goal occurred only in the second half, the probability of the home team scoring the second goal increased threefold (309.9%) as compared with cases where the first goal of the match was scored in the first 15 minutes. A similar tendency was reported for the Spanish Football League by Nevo and Ritov (2012), who suggested that, depending on the time when the first goal was scored, it could accelerate or delay the time when the next goal was scored. When a goal is scored before the 52nd minute, its effect on the probability of the next goal being scored is negative, while when the first goal is scored after that time the effect is positive. Furthermore, the results of the study demonstrate that once a goal is scored, another goal is less likely to be scored as compared with the situation where no goal has been scored (Nevo and Ritov, 2012).

This tendency can be explained by the influence of contextual factors on teams’ performance during the match, which has been demonstrated by several studies (Collet, 2013; Pratas et al., 2016). For instance, Heuer and Rubner (2012) showed that during the last ten minutes of matches of the German Premier Football League (Bundesliga) players’ behaviour depends significantly on the current score, representing an increasing offensive (or decreasing defensive) behavior (Heuer and Rubner, 2012).

Practical implications

The findings of the present study could prove useful for soccer coaches, as knowing that the occurrence of the first goal in later match periods steadily increases the probability of the second goal of a match being scored by the home team; therefore, coaches may adjust their decisions related to substitutions or tactical options in terms of attack and defence. During soccer practice players should be prepared for scenarios of mental pressure and physical fatigue, without reducing their self-efficacy in the last periods of training sessions.

Conclusions

The results of the present study demonstrate that the highest number of second goals (both score-doubling and equalizing) in a match was scored in the last 5-min period of each half. Different types of the second goal (score-doubling or equalizing) had a different impact on the match outcome for home and away teams. The time of the first goal in a match had a significant effect on the time of the next goal scored by home teams. This paper clearly demonstrates the influence of the match context (i.e. match venue, scoreline, and time of the first goal) on the probability of the second goal of a match being scored and also on the effect of the second goal on the match outcome. Further research is needed to identify performance indicators which are related to the time of the second goal being scored during soccer matches in different European leagues.

Acknowledgements

The first author received a PhD grant from the Portuguese Foundation for Science and Technology (SFRH/BD/80719/2011).

References

  • Anderson C, Sally D. The numbers game. New York: Penguin Books; 2013. [Google Scholar]
  • Armatas V, Yiannakos A, Papadopoulou S, Skoufas D. Evaluation of goals scored in top ranking soccer matches: Greek “Superleague” 2006-07. Serbian J Sport Sci. 2009;3:39. –. [Google Scholar]
  • Barros CP, Frick B, Passos J. Coaching for survival: the hazards of head coach careers in the German ‘Bundesliga’ Appl Econ. 2009;41:3303. –. [Google Scholar]
  • Brandão R, Sidónio S, Krebs R, Araújo D, Machado AA. The meaning of refereeing: perception of professional soccer referees. Rev Psicol Deporte. 2011;20:275. –. [Google Scholar]
  • Broström G. Event History Analysis with R. Boca Raton: CRC Press; 2012. [Google Scholar]
  • Castilla EJ. Dynamic Analysis in the Social Sciences, 1st Edition. USA: Elsevier, Inc; 2007. [Google Scholar]
  • Collet C. The possession game? A comparative analysis of ball retention and team success in European and international football, 2007–2010. J Sport Sci. 2013;31:123. –. [PubMed] [Google Scholar]
  • Courneya KS. Importance of game location and scoring first in college baseball. Percept Motor Skill. 1990;71:624. –. [Google Scholar]
  • Courneya KS, Carrón AV. The home advantage in sport competitions: A literature review. J Sport Exerc Psychol. 1992;14:13. –. [Google Scholar]
  • Cox DR. Regression models and life tables. J Roy Stat Soc B. 1972;34:187. –. [Google Scholar]
  • Del Corral J, Barros CP, Prieto-Rodríguez J. The Determinants of Soccer Player Substitutions: A Survival Analysis of the Spanish Soccer League. J Sports Econ. 2008;9:160. –. [Google Scholar]
  • Dobson S, Goddard J. Optimizing strategic behaviour in a dynamic setting in professional team sports. Eur J Oper Res. 2010;205:661. –. [Google Scholar]
  • Heuer A, Rubner O. How Does the Past of a Soccer Match Influence Its Future? Concepts and Statistical Analysis. PLoS ONE. 2012. p. 7. [PMC free article] [PubMed]
  • Lago C. The influence of match location, quality of opposition, and match status on possession strategies in professional association football. J Sport Sci. 2009;27:1463. –. [PubMed] [Google Scholar]
  • Lago C, Casais L, Dominguez E, Sampaio J. The effects of situational variables on distance covered at various speeds in elite soccer. Eur J Sport Sci. 2010;10:103. –. [Google Scholar]
  • Lago-Ballesteros J, Lago-Peñas C, Rey E. The effect of playing tactics and situational variables on achieving score-box possessions in a professional soccer team. J Sport Sci. 2012;30:1455. –. [PubMed] [Google Scholar]
  • Lago-Peñas C. The role of situational variables in analysing physical performance in soccer. J Hum Kinet. 2012;35:89. –. [PMC free article] [PubMed] [Google Scholar]
  • Lago-Peñas C, Dellal A. Ball possession strategies in elite soccer according to the evolution of the match-score: the influence of situational variables. J Hum Kinet. 2010;25:93. –. [Google Scholar]
  • Lago-Peñas C, Gomez-Lopez M. How important is it to score a goal? The influence of the scoreline on match performance in elite soccer. Percept Motor Skill. 2014;119:774. –. [PubMed] [Google Scholar]
  • Lago-Peñas C, Gómez-Ruano M, Megías-Navarro D, Pollard R. Home advantage in football: Examining the effect of scoring first on game outcome in the five major European leagues. Int J Per An Sport. 2016;16(2):411. –. [Google Scholar]
  • Leite WSS. Analysis of goals in soccer World Cups and the determination of the critical phase of the game. Phys Educ Sport. 2013;11(3):247. –. [Google Scholar]
  • Loughead TM, Carrón AV, Bray SR, Kim A. Facility familiarity and the home advantage in professional sports. Int J Sport Psychol Exerc Psychol. 2003;1:264. –. [Google Scholar]
  • Molinuevo JS, Bermejo JP. The effect os scoring first and home advantage in professional spanish football and indoor soccer leagues. Rev Psicol Deporte. 2012;21:301. –. [Google Scholar]
  • Nevo R, Ritov Y. Around the goal: Examining the effect of the first goal on the second goal in soccer using survival analysis methods. J Quant An Sports. 2012;9:65. –. [Google Scholar]
  • Njororai W. Timing of Goals Scored in Selected European and South American Soccer Leagues, FIFA and UEFA Tournaments and the Critical Phases of a Game. Int J Sports Sci. 2014;4(6A):56. –. [Google Scholar]
  • Pollard R, da Silva CD, Nísio CM. Home advantage in football in Brazil: Differences between teams and the effect of distance traveled. Brazilian J Soccer Sci. 2008;1:3. –. [Google Scholar]
  • Pratas JM, Volossovitch A, Carita AI. The effect of performance indicators on the time the first goal is scored in football matches. Int J Per An Sports. 2016;16:347. –. [Google Scholar]
  • Sampedro J, Prieto J. The territoriatility as a factor associated to the advantage of playing at home. A comparative study by regions in the Spanish Football League and the in the Spanish Futsal League. Motricidad. Eur J Hum Movement. 2011;26:93. –. [Google Scholar]
  • Tenga A. World Congress of Performance Analysis of Sport IX. London & New York: Routledge Taylor & Francis Group; 2012. First goal and home advantage at different levels of play in professional soccer; pp. 47\u201351. Editors: D. Peters, P. G. O’Donoghue. –. [Google Scholar]
  • Therneau T. A Package for Survival Analysis in S. R package version 2.37-7. 2015. http://CRAN.R-project.org/package=survival; Available at. accessed on 01.08.2016.
  • Venturelli M, Schena F, Zanolla L, Bishop D. Injury risk factors in young soccer players detected by a multivariate survival model. J Sci Med Sport. 2011;14:293. –. [PubMed] [Google Scholar]
  • Wolfson S, Wakelin D, Lewis M. Football supporters' perceptions of their role in the home advantage. J Sport Sci. 2005;23:365. –. [PubMed] [Google Scholar]

Articles from Journal of Human Kinetics are provided here courtesy of Academy of Physical Education in Katowice, Poland

\n \n
\n
\n \n
\n\n
\n
\n \n
Cite
\n
\n
\n
\n \n Copy\n \n\n \n Download .nbib\n .nbib\n \n\n\n \n\n
\n \n \n
\n
\n
\n
\n
\n\n \n \n \n \n \n \n\n\n\n \n \n \n \n \n \n \n \n\n \n\n\n\n\n\n\n\n\n \n \n \n\n \n \n\n \n \n\n\n \n \n \n\n\n \n \n \n\n\n\n", + "page_last_modified": "" + }, + { + "page_name": "Statistically Ranking the World's Top 10 Football Leagues | News, ...", + "page_url": "https://bleacherreport.com/articles/2033754-statistically-ranking-the-worlds-top-10-football-leagues", + "page_snippet": "Claims that one league is better than another have become ever more common in the social media-dominated world of football fandom, so here at Bleacher Report we have decided to take a statistics-based look at the topic...More goals scored does not, then, necessarily mean more clinical finishing, merely more chances created. ... Just how spread-out are the points totals of sides within the division? The standard deviation gives us a clear indication of which leagues are more balanced in level than others. A more extensive way of measuring the statistic would be to use the total number of passes, rather than each team's average, which would bolster Spanish and German figures. It would, though, hide the number of sides with poor completion percentages and take a substantially increased time period to calculate. ... As revealed earlier on, there is little correlation between goals scored per game and average shot accuracy, as confirmed by a Pearsons coefficient of 0.33. Perhaps the most surprising result of the sample is that the stereotypically defensive Italian Serie A comes in third statistically, while the Premier League averages less goals than both Spain and Italy. Perhaps English defences are not quite as bad as reports suggest. There is, though, little difference between the three traditionally strong leagues. Ligue 1 and the Brasileirao are well known for their frequency of low-scoring games and do not disappoint, as two of just three leagues to average under 2.5 goals per game. England and Germany have struck by far the best balance and, in general, boast the best facilities in which to showcase their respective leagues. Attending fixtures is a major part of the culture in both countries. ... Personally, I am not a fan of ranking leagues and making comparisons regarding general quality between competitions. It is difficult to do and, to be accurate, would require many more factors than analysed here. Based on the number of goals, best discipline, best pass-completion rates, most accurate finishing, competitive balance and attendance figures, though, it is the Eredivisie that comes out of our rough experiment as the best performing competition.", + "page_result": "Statistically Ranking the World's Top 10 Football Leagues | News, Scores, Highlights, Stats, and Rumors | Bleacher Report
  • Facebook Logo
  • \"X.com
  • Copy Link Icon

Statistically Ranking the World's Top 10 Football Leagues

Christopher Atkins@@chris_elastico\"X.comContributor IApril 18, 2014

Statistically Ranking the World's Top 10 Football Leagues

0 of 8

    \"\"
    Shaun Botterill/Getty Images

    Claims that one league is better than another have become ever more common in the social media-dominated world of football fandom, so here at Bleacher Report we have decided to take a statistics-based look at the topic.

    Rather than look at simply \"which has the best players,\" the hope is to look at a range of factors that will help demonstrate how appealing a division is to the spectator. Does it offer goals, good football, high levels of competition etc.?

    Over the next eight pages, we take initial strides into what could be a massively in-depth area of research, comparing 10 of the world's best leagues over a number of factors.

    The results are, at times, somewhat surprising.

How It Works

1 of 8

    \"\"
    Michael Dodge/Getty Images

    The leagues nominally chosen by B/R to represent the top 10 in world football, while open for debate in itself have been ranked according to the following statistical methods:

    1. Goals per game

    Which league has the most free-scoring football. While not necessarily an indicator of quality, it gives us an impression of which leagues give the fans best entertainment on a regular basis.

    2. Disciplinary records

    By ranking each league by the number of yellow and red cards received per game, with red cards counting as three times the value, we can compare competitions by their concepts of \"fair play.\" Of course, it is a statistic that relies heavily on refereeing consistency, which cannot be in any way guaranteed.

    3. Average pass accuracy

    Which leagues boast the best levels of accuracy with their passing? In theory, this statistic should enable us to see which competitions try to play passing-based football and possess the best technical players. Differing styles of defending and attack-building, though, affect this method of judgement.

    4. Average shot accuracy

    Which competition boasts the sharpest shooters? By comparing the percentage of shots on target in each competition, we get a good impression of striking ability and the quality of chance created. In that respect, it can also be seen as an indication of slack defensive standards.

    It is interesting to note that the Pearson Product-Moment correlation coefficient between the rankings of leagues with the best shot accuracy and number of goals scored is just 0.33, indicating a negligible correlation. More goals scored does not, then, necessarily mean more clinical finishing, merely more chances created.

    5. Standard Deviation of points totals

    Just how spread-out are the points totals of sides within the division? The standard deviation gives us a clear indication of which leagues are more balanced in level than others. The larger the coefficient, the bigger the gulf in points totals.

    6. Attendance figures

    Just how many people bother to show up to the stadiums and watch each competition? After all, good football is fairly pointless if nobody is watching.

    Note: All data collected is for the 2013-14 season, with the exception of the Campeonato Brasileiro and MLS for which 2013 data is used. All statistics are compiled from WhoScored.com data, with the exception of attendance figures, for which transfer market was used.

    Card data for the Portuguese Primeira Liga is also taken from Transfermarkt, while reliable figures for some categories were not available for the division.

Goals Per Game: Eredivisie Leads the Way for Goals

2 of 8

    \"\"
    Dean Mouhtaropoulos/Getty Images

    It is perhaps of little surprise to anybody who has tracked the remarkable scoring figures amassed by strikers in the Netherlands over the years that the Eredivisie is the highest scoring of our monitored leagues.

    LeagueGoals per GameRank
    Eredivisie3.181
    Bundesliga3.142
    \nSerie A2.813
    La Liga2.784
    Premier League2.765
    MLS2.626
    Russian PL2.537
    Brasileirao2.468
    \nLigue 12.429
    \nPrimeira Liga2.4110

    The Dutch top-flight averages well in excess of three goals per game this season, placing it and the Bundesliga well ahead of all other divisions analysed.

    Perhaps the most surprising result of the sample is that the stereotypically defensive Italian Serie A comes in third statistically, while the Premier League averages less goals than both Spain and Italy. Perhaps English defences are not quite as bad as reports suggest.

    There is, though, little difference between the three traditionally strong leagues.

    Ligue 1 and the Brasileirao are well known for their frequency of low-scoring games and do not disappoint, as two of just three leagues to average under 2.5 goals per game.

    Bottom of the pile, though, is the Portuguese Primeira Liga, stealing the title of least entertaining league from Ligue 1 by just one decimal point.

Discipline: Premier League Leads the Way in Fair Play

3 of 8

    \"\"
    Shaun Botterill/Getty Images

    It is a statistic that can be interpreted in one of two ways. Either some leagues simply have a better concept of fair play than others and rely less on physical, high-risk defending. Or, simply, referees have vastly different standards of what constitutes a booking from country to country.

    Interestingly, it is the Premier League which leads the way in this category with comfortably the least red cards shown and a below-average track record for cautions. Many would suggest it is refereeing leniency which influences the result on this occasion.

    LeagueYC/GRC/GDiscipline CoefficientRank
    Premier League3.240.143.671
    MLS3.040.243.762
    Eredivisie3.170.243.893
    \nLigue 13.270.233.964
    Bundesliga3.610.194.185
    Russian PL3.790.244.516
    Brasileirao4.290.285.137
    \nSerie A4.670.275.488
    La Liga4.930.275.749
    \nPrimeira Liga5.220.416.4510

    Portugal, meanwhile, once more scores badly. The Primeira Liga's red card statistics, per Transfermarkt, are comfortably the highest, while the league also boasts the most cautions per game of the 10 divisions.

    Are Portuguese referees operating by a different rule book, or is the league in need of a fair play revolution?

    The Bundesliga performs notably well in terms of disciplinary record, with the least red cards per game of the remaining leagues. La Liga and Serie A, meanwhile, are near the bottom of the rankings, with high levels of cautions in each game.

Average Pass Completion: Italy Boasts Europe's Most Successful Distributors

4 of 8

    \"\"
    Massimo Pinca

    Spain is often seen as the modern home of passing football, but it is the Italians and Serie A that leads the way in terms of percentages of passes completed this season.

    Italy's famous slower pace of playing and more tactically-minded defending may contribute, but the frantic Premier League's second-place ranking indicates that pace of play is not the only factor.

    LeagueAverage Club Pass Accuracy (%)Rank
    \nSerie A80.891
    Premier League79.622
    Eredivisie78.793
    Brasileirao78.44
    \nLigue 177.955
    Bundesliga77.536
    La Liga77.137
    MLS76.928
    Russian PL75.869

    Russia and the MLS score poorly in terms of pass completion, indicating that both tend to opt for a more direct style that raises risk. Further analysis regarding average pass length would be the next stage of investigation.

    What mitigating factors could Spanish and German football offer for their poor performance? The gulf in class between clubs no doubt ensures that many sides near the bottom of the table have much poorer passing figures.

    A more extensive way of measuring the statistic would be to use the total number of passes, rather than each team's average, which would bolster Spanish and German figures. It would, though, hide the number of sides with poor completion percentages and take a substantially increased time period to calculate.

Average Shot Accuracy: Eredivsie Strikers on Target Most Often

5 of 8

    \"\"
    Dean Mouhtaropoulos/Getty Images

    As revealed earlier on, there is little correlation between goals scored per game and average shot accuracy, as confirmed by a Pearsons coefficient of 0.33. The Eredivisie, though, tops the charts for both.

    What the lack of correlation would suggest, then, is that goals scored is almost entirely linked to the number of chances created rather than the ability to hit the target.

    LeagueShot Accuracy (%)Rank
    Eredivisie37.561
    Bundesliga36.942
    La Liga35.343
    \nLigue 134.984
    Russian PL34.385
    Brasileirao33.836
    MLS33.817
    Premier League33.268
    \nSerie A32.989

    That the Serie A is bottom of our ranking in terms of percentage of shots on target, yet third in terms of goals per game would suggest that Italian defences are conceding far more chances than they ever did.

    That the Eredivisie is top of both, meanwhile, would indicate that the quality of chance created is high, once more casting aspersions on defensive quality.

    Ligue 1 and the Russian Premier League, meanwhile, were two of the bottom three leagues in terms of scoring goals. Both, though, see their strikers hit the target with a reasonable amount of their chances.

    Shooting opportunities, then, are not created as often as they could be in either country.

    To further the analysis, the next step would be to analyse the location and quantity of shots and then attempt to correlate those figures with the percentages. Only then would it be truly clear as to what is caused by striking ability and what is caused by slack defending.

Variation of Points Totals: MLS Leads the Way

6 of 8

    \"\"
    Mike Stobe/Getty Images

    In terms of equality within divisions, it is the MLS and the Brasileirao that provide the most competitive leagues of those analysed.

    Across 34 and 38 matches respectively, the two divisions both boast standard deviation coefficients of less than 12. The implication, then, is that the mean number of points between a team and the league's average (mean) points total is just 11-12 points.

    LeagueVariationRank
    MLS11.431
    Brasileirao11.652
    Eredivisie12.153
    Russian PL12.194
    \nLigue 114.035
    Bundesliga14.156
    \nPrimeira Liga14.517
    Premier League16.898
    La Liga17.349
    \nSerie A17.5910

    At the other end of the scale, meanwhile, are Europe's powerhouse leagues. Italy, Spain and England all perform badly in terms of competitiveness in what is an indication of the financial imbalance within the leagues.

    The Bundesliga performs relatively well for a division with several sides acknowledged to be of a very high standard, with a standard deviation of just over 14.

    Portugal and France, meanwhile, see their figures altered by the presence of two or three clubs that are substantially better than the rest. The other sides, though, are relatively competitive.

    Despite all the criticism of La Liga's imbalance, it is Serie A that performs the worst this season in terms of competitive balance.

Average Attendance: Bundesliga and Premier League

7 of 8

    \"\"
    Christof Koepsel/Getty Images

    Unsurprisingly, the best-supported leagues in world football are in England and Germany, where spectators flock in their tens of thousands to watch games each weekend.

    What the figures do highlight, though, is the relative poverty of the attendances in Brazil, Portugal and Russia, despite long-standing football cultures.

    LeagueAv. AttendanceRank
    Bundesliga432211
    Premier League363042
    La Liga268143
    \nSerie A230944
    \nLigue 1206635
    Eredivisie194646
    MLS180147
    Brasileirao149518
    Russian PL116269
    \nPrimeira Liga781810

    Serie A and La Liga also perform far below what one would expect of such esteemed footballing countries, with economic realities and the lack of stadium development both major influencing factors.

    In Brazil, meanwhile, the lack of spectators is often put down to the lack of middle-class attendance, with crumbling stadiums and frequent fan violence off-putting to those from middle class backgrounds.

    England and Germany have struck by far the best balance and, in general, boast the best facilities in which to showcase their respective leagues. Attending fixtures is a major part of the culture in both countries.

Overall Ranking: Eredivisie, Bundesliga and Premier League Most Enticing

8 of 8

    \"\"
    Dean Mouhtaropoulos/Getty Images

    Personally, I am not a fan of ranking leagues and making comparisons regarding general quality between competitions. It is difficult to do and, to be accurate, would require many more factors than analysed here.

    Based on the number of goals, best discipline, best pass-completion rates, most accurate finishing, competitive balance and attendance figures, though, it is the Eredivisie that comes out of our rough experiment as the best performing competition.

    It is worth reiterating that the aim of the investigation was not to find which league boasts the highest standard of player, but which is the best competition for spectators.

    LeagueRank
    Eredivisie1
    Bundesliga2
    Premier League3
    MLS4
    \nLigue 15
    \nSerie A6=
    Brasileirao6=
    La Liga8
    Russian PL9

    Spain, meanwhile, suffers in comparison. The sizeable spread in quality distorts several of our parameters, and the league also performs badly in terms of cards awarded and attendances. With better analysis of more areas, it would be little surprise to see La Liga perform better.

    Much less surprising, meanwhile, is that the Bundesliga and Premier League also perform very well compared to their rivals. Both are well managed competitions on many levels.

    The rankings above are simply based upon the areas chosen for comparison and are by no means a comprehensive study. Even within those areas, there is room for further research.

    They do, though, offer some indication of how various leagues perform in different facets and how some competitions could look to improve. In a world where spontaneous judgements are increasingly common, further evidence-based analysis and cross-comparison is a must.

    Note: Portugal has been omitted due to an incomplete statistical data set.

  • Facebook Logo
  • \"X.com
  • Copy Link Icon
X
", + "page_last_modified": "" + }, + { + "page_name": "Lorient 2 live score, schedule & player stats | Sofascore", + "page_url": "https://www.sofascore.com/team/football/lorient-2/314249", + "page_snippet": "Lorient 2 live score, fixtures, player ratings and statistics.The current Lorient 2 roster, stats and player performance can be found on this page. There are also statistics for each player in all competitions with all total played and started matches, minutes played, number of goals scored, number of cards and much more. There are also statistics for each player in all competitions with all total played and started matches, minutes played, number of goals scored, number of cards and much more. Lorient 2 top scorers list is updated live during every match. The height of the column represents match difficulty at the time, based on odds. ... Lorient 2 live scores, players, season schedule and today\u2019s results are available on Sofascore. We may have video highlights with goals and news for some Lorient 2 matches, but only if they play their match in one of the most popular football leagues. The height of the column represents match difficulty at the time, based on odds. Lorient 2 live scores, players, season schedule and today\u2019s results are available on Sofascore. We may have video highlights with goals and news for some Lorient 2 matches, but only if they play their match in one of the most popular football leagues.", + "page_result": "Lorient 2 live score, schedule & player stats | Sofascore

Lorient 2

\"France\"France
Receive notifications for all games of this team
349 followers
Recent form
Hover over the form graph to see event details.
The height of the column represents match difficulty at the time, based on odds.
Team info

Latest transfers
Arrivals 4
Exauce Mpembele Boula
Carmel Mabanza
Arthur Avom Ebong
Departures 12
Bassirou N'Diaye
Kamal Bafounta
Eddy Ehlinger

Info
Foundation date
2 Apr 1926
Country
\"FR\"/
France

Venue
Stadium
Stade Jean-Charter
Capacity
4500
City
Lorient, France
Latest transfers
Arrivals 4
Exauce Mpembele Boula
Carmel Mabanza
Arthur Avom Ebong
Departures 12
Bassirou N'Diaye
Kamal Bafounta
Eddy Ehlinger

About Lorient 2

Lorient 2 live scores, players, season schedule and today\u2019s results are available on Sofascore.

Lorient 2 next match

We may have video highlights with goals and news for some Lorient 2 matches, but only if they play their match in one of the most popular football leagues.

Lorient 2 previous match

Lorient 2 fixtures tab is showing the last 100 football matches with statistics and win/draw/lose icons.

There are also all Lorient 2 scheduled matches that they are going to play in the future.

Lorient 2 performance and form graph is a Sofascore unique algorithm that we are generating from the team's last 10 matches, statistics, detailed analysis and our own knowledge.

This graph may help predict future Lorient 2 matches.

Current Lorient 2 players

Arthur Avom Ebong, Exauce Mpembele Boula, Carmel Mabanza, Royce Openda, Paul Bellon

The current Lorient 2 roster, stats and player performance can be found on this page.

There are also statistics for each player in all competitions with all total played and started matches, minutes played, number of goals scored, number of cards and much more.

Lorient 2 top scorers list is updated live during every match.

You can click on players from the roster above and see available personal information such as nationality, date of birth, height, preferred foot, position, player value, transfer history etc.

For today\u2019s football schedule and results visit our football live score page.

Lorient 2

\"France\"France
Standings
All
Home
Away
Loading...
Loading...
Matches
Loading...
Team info

Latest transfers
Arrivals 4
Exauce Mpembele Boula
Carmel Mabanza
Arthur Avom Ebong
Departures 12
Bassirou N'Diaye
Kamal Bafounta
Eddy Ehlinger

Info
Foundation date
2 Apr 1926
Country
\"FR\"/
France

Venue
Stadium
Stade Jean-Charter
Capacity
4500
City
Lorient, France
Latest transfers
Arrivals 4
Exauce Mpembele Boula
Carmel Mabanza
Arthur Avom Ebong
Departures 12
Bassirou N'Diaye
Kamal Bafounta
Eddy Ehlinger
Recent form
Hover over the form graph to see event details.
The height of the column represents match difficulty at the time, based on odds.
Loading...
Loading...
Loading...

About Lorient 2

Lorient 2 live scores, players, season schedule and today\u2019s results are available on Sofascore.

Lorient 2 next match

We may have video highlights with goals and news for some Lorient 2 matches, but only if they play their match in one of the most popular football leagues.

Lorient 2 previous match

Lorient 2 fixtures tab is showing the last 100 football matches with statistics and win/draw/lose icons.

There are also all Lorient 2 scheduled matches that they are going to play in the future.

Lorient 2 performance and form graph is a Sofascore unique algorithm that we are generating from the team's last 10 matches, statistics, detailed analysis and our own knowledge.

This graph may help predict future Lorient 2 matches.

Current Lorient 2 players

Arthur Avom Ebong, Exauce Mpembele Boula, Carmel Mabanza, Royce Openda, Paul Bellon

The current Lorient 2 roster, stats and player performance can be found on this page.

There are also statistics for each player in all competitions with all total played and started matches, minutes played, number of goals scored, number of cards and much more.

Lorient 2 top scorers list is updated live during every match.

You can click on players from the roster above and see available personal information such as nationality, date of birth, height, preferred foot, position, player value, transfer history etc.

For today\u2019s football schedule and results visit our football live score page.

About
Live scores service at Sofascore livescore offers sports live scores, results and tables. Follow your favourite teams right here live! Live score on Sofascore.com livescore is automatically updated and you don't need to refresh it manually. With adding games you want to follow in "My games" following your matches livescores, results and statistics will be even more simple.
When the fun stops, STOP
Download Sofascore
Livescore app
Visit us
\u00a9 2024 Sofascore \u2013\u00a0All Rights Reserved.
", + "page_last_modified": "" + }, + { + "page_name": "Lorient Ranking History", + "page_url": "https://www.footballcritic.com/fc-lorient/team-ranking-history/589", + "page_snippet": "See the performance ranking of Lorient week by week.Lorient's FC Ranking is based over their last 20 matches played, including the standard of the competition in which they feature, and a number of performance bonuses related to their playing style. Our algorithm is updated each Monday to take into account all matches played by a team in the last seven days. You can track how a team has risen or fallen on a weekly basis. ... In Lorient's last match, they fielded the below line-up. Our algorithm is updated each Monday to take into account all matches played by a team in the last seven days. You can track how a team has risen or fallen on a weekly basis. ... In Lorient's last match, they fielded the below line-up. The formation displayed highlights the player name, position, and their FootballCritic rating.", + "page_result": "\r\n\r\n\n\n\n\nLorient Form history (Rankings per week)\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n\n\n\n
\n
\n
\n
\n
\n\"FootballCritic\"\n
\n
\n
\"FC
\n
\n\n
\n
\n\n
\n
\n\n\n
\n
\n
\n
 
\n
 
\n
 
\n
\n
\n
\n
\n
\n\n
\n
\nWelcome Guest\n\n
\n

Thank you for using Footballcritic.
\nStart by talking about your audience, not yourself.\n

\n

Logout

\n
\n\n
\n\n
\n
\nx\n
\n
\n\n\n\n\n
\n
\n
\n
\n
\"Lorient
\n\n
\n

LORIENT

\n\nLorient, France \n
\n
\n
\n
\n\n69\n
\n
\n
\n\n\n\"The\n\n
\n
\n
\n
\n
\n\n
\n
\n
\n
\n
\n\n
\n
\n
\n\n
\n
\n
\n
\n
\n
\n
\n
\n
\n
\n

Ranking history in weeks

\n
\n
\n

\nLorient's FC Ranking is based over their last 20 matches played, including the standard of the competition in which they feature, and a number of performance bonuses related to their playing style. Our algorithm is updated each Monday to take into account all matches played by a team in the last seven days. You can track how a team has risen or fallen on a weekly basis.\n

\n
\n\n
\n\n
\n
\n
\n
\n
\n
\nDo Not Sell My Personal Information\n
\n
\n
\n\"footballcritic\"\n\n
\n
\n
\n
Change Consent
\n#Trending Players:\n
\n
\n\n
\nCorporate & Media\n

\n\nRealtimes - Publishing Network
\nInnovatieweg 20C
\n7007 CD, Doetinchem, Netherlands
\n+31(315)-764002\n
\n
\n
\n
\n
\nFootballCritic (FC) has one main purpose - to help football fans of every level of obsession\nunderstand and enjoy the game just a little more.\n

\nWe provide exclusive analysis and live match performance reports of soccer players and teams,\nfrom a database of over 225.000 players, 14.000 teams, playing a total of more then 520.000 matches.\n

\nUsing our unique search, comparison and ranking tools, FC wants to make it easier for a fan of any team to access the\nfacts and figures that drive the sport.\n
\n
\nPartners\n
\n\"DSG\n\"Cloud\n
\n
\n
\n
\n
\nCopyright 2018 - 2024, Footballcritic Inc. All right reserved.
Kick-off (KO) times are in your local time. Europe/Berlin 03/28/2024 03:37:37
\n\n
\n
\n\n
\n
\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\n\n\n", + "page_last_modified": "" + }, + { + "page_name": "Analysis of Scoring Sequences in Matches of the Portuguese Premier ...", + "page_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6231341/", + "page_snippet": "The aim of this study was to examine the sequences of the first two goals scored in soccer matches in accordance with a range of different match contexts. Data from 1506 matches played in the Portuguese Premier League during six consecutive competitive ...Most of these studies focused only on the analysis of the first goal effect on the match outcome, and did not examine the role of goals subsequently scored. A recent study of Lago-Pe\u00f1as et al. (2016) that analysed games played in the most important European domestic leagues (English FA Premier League, French Ligue 1, Spanish La Liga, Italian Serie A and German Bundesliga) in the 2014/2015 season demonstrated that home teams scored first in 57.8% of games and obtained in total 84.85% of points won in these games. In the 2015/16 season, 20% of matches ended with a total of two goals (i.e. the sum of total goals scored per game by both teams): 10% finished 1-1 (home draw, 38 matches), 7% 2-0 (home win, 21 matches) and 3% 0-2 (home defeat, 10 matches). The home advantage effect was confirmed in these matches. The second goal may be the equalizer (0-1 to 1-1, or 1-0 to 1-1) or the goal, which enables a team to double their advantage (1-0 to 2-0, or 0-1 to 0-2). The anticipation of temporal localization of the second goal associated to its nature (i.e., goal which creates advantage or recovers from score disadvantage) seems to be useful for a timely adaptation of the team's tactics. On the one hand, fatigue, which is greatest at the end of each half, leads to an increase in the number of technical and tactical errors, which may lead to more goal scoring opportunities. On the other hand, the little time remaining until the end of each half encourages players to use their last chances to score a goal that also may influence the match outcome.", + "page_result": "\n \n\n\n\n\n\n\n\n \n \n\n \n \n \n \n\n \n \n \n \n \n\n \n \n \n\n\n\n \n\n \n \n\n\n Analysis of Scoring Sequences in Matches of the Portuguese Premier League - PMC\n\n \n \n \n \n\n \n \n\n \n \n \n \n \n \n \n \n\n\n\n \n \n\n\n\n\n\n\n\n\n \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n \n\n\n \n\n\n \n\n\n\n\n\n \n \n \n Back to Top\n \n \n\n Skip to main content\n \n
\n
\n
\n
\n \"U.S.\n

An official website of the United States government

\n \n Here's how you know\n \n
\n
\n \n
\n \n
\n

\n The .gov means it\u2019s official.\n
\n Federal government websites often end in .gov or .mil. Before\n sharing sensitive information, make sure you\u2019re on a federal\n government site.\n

\n
\n
\n
\n \n
\n

\n The site is secure.\n
\n The https:// ensures that you are connecting to the\n official website and that any information you provide is encrypted\n and transmitted securely.\n

\n
\n
\n
\n \n
\n
\n
\n\n\t
\n\t\t
\n\n
\n \n \"NIH\n \n
\n\n\t\t\t
\n\t\t\t\tLog in\n\t\t\t\t\n\t\t\t
\n\n\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\n\t\t\t\t\t\t

Account

\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\tLogged in as:
\n\t\t\t\t\t\tusername\n\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t
\n\n\t\t
\n\t
\n
\n
\nAccess keys\nNCBI Homepage\nMyNCBI Homepage\nMain Content\nMain Navigation\n
\n
\n\t
\n
\n\n\n \n \n\n\n \n \n\n
\n \n
\n
\n
\n

\n \n Preview improvements coming to the PMC website in October 2024.\n Learn More or\n Try it out now.\n \n

\n
\n
\n
\n \n
\n \n\n \n \n \n
\n
\n
\n \n \n \n\n \n \n
\n \n
\n \n\n
\n\n \n \n\n
\n \n
\n
\n
\n \n \n \n\n
\n \n
\n As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with,\n the contents by NLM or the National Institutes of Health.
\n Learn more:\n PMC Disclaimer\n |\n \n PMC Copyright Notice\n \n
\n\n
\n \n \n
\"Logo\"Link
\n \n \n
\n
\n \n
J Hum Kinet. 2018 Sep; 64: 255\u2013263.
Published online 2018 Oct 15. doi:\u00a010.1515/hukin-2017-0199
PMCID: PMC6231341
PMID: 30429916

Analysis of Scoring Sequences in Matches of the Portuguese Premier League

José M. Pratas

1CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa, Lisboa\nPortugal

Find articles by José M. Pratas

Anna Volossovitch

1CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa, Lisboa\nPortugal

Find articles by Anna Volossovitch

Ana I. Carita

2CIPER, Faculdade de Motricidade Humana, BIOLAD, Universidade de Lisboa, Portugal, Estrada da Costa, 1495-688, \nCruz Quebrada, Portugal

Find articles by Ana I. Carita
1CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa, Lisboa\nPortugal
2CIPER, Faculdade de Motricidade Humana, BIOLAD, Universidade de Lisboa, Portugal, Estrada da Costa, 1495-688, \nCruz Quebrada, Portugal
*José M. Pratas Affiliation: CIPER, Faculdade de Motricidade Humana, SpertLab, Universidade de Lisboa Address: Estrada da Costa, 1495-688 Cruz Quebrada, Lisboa, Portugal Tel: +351 965220648 Fax: + 351 214144712 tp.aobsilu.hmf@satarpmj
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Abstract

The aim of this study was to examine the sequences of the first two goals scored in soccer matches in accordance with a range of different match contexts. Data from 1506 matches played in the Portuguese Premier League during six consecutive competitive seasons (2009-10 to 2014-2015) were analysed using descriptive statistics and the chi-square test in order to verify the association between variables and a Cox regression analysis was used to predict the time the second goal was scored in function of the time of the first goal scored in the match and the scoreline. The results revealed a higher frequency of the second goals being scored in the second half of a match (58%) and in the last 5 min periods of each half. A positive association was found for home teams and score-doubling goals (58%), as well as for away teams and score-equalizing goals (56%). For home and away teams the score-doubling goal of a match was strongly and positively associated with a win outcome for home (93%) and away teams (92%), while the score-equalizing goals were associated with a draw (home and away teams: 44%) and loss outcome (home: 33% and away teams: 32%). Finally, the Cox model showed that if the first goal was scored in the second half of the match, the probability of the second goal being scored was three times higher compared to the first half.

Key words: game analysis, soccer, survival analysis

Introduction

In soccer, it has been demonstrated that performance of teams can be influenced by the scoreline (Lago-Peñas, 2012; Gómez et al., 2013). Soccer players perform significantly less high-intensity activity when winning than when losing or when the score is tied (Lago et al., 2010). It was also shown that teams had longer periods of possession in matches when they were losing than when they were winning (Lago-Peñas and Dellal, 2010; Lago-Peñas and Gomez-Lopez, 2014), teams played more in the attack and defensive zones when the score was level (Lago, 2009) and final-third entries were greater when teams were 1 goal down than when they were 1 goal up (Lago-Peñas and Gomez-Lopez, 2014). Findings also showed that shots on goal decreased by 14.1% and 14.45% when teams were 1 goal up and when the scores were level, respectively (Lago-Peñas and Gomez-Lopez, 2014) and when a team was drawing or winning, the probability of reaching the goal decreased by 43 and 53%, respectively (Lago-Ballestero et al., 2012).

The score evolution in time is an important situational factor that may influence the team performance during the match and it also allows to identify the critical moments of the game (Leite, 2013; Njororai, 2014). In low scoring games, each goal can be considered a critical incident that influences the course of the game (Ferreira, 2013). Studies conducted with different professional soccer leagues have shown that the team which scores first in a match has a higher probability of winning, and the home team is more likely to score first than the opposing team (Molinuevo and Bermejo, 2012; Tenga, 2012; Pratas et al., 2016). Most of these studies focused only on the analysis of the first goal effect on the match outcome, and did not examine the role of goals subsequently scored. A recent study of Lago-Peñas et al. (2016) that analysed games played in the most important European domestic leagues (English FA Premier League, French Ligue 1, Spanish La Liga, Italian Serie A and German Bundesliga) in the 2014/2015 season demonstrated that home teams scored first in 57.8% of games and obtained in total 84.85% of points won in these games. On the contrary, when the away team scored first, they obtained only 76.25% of subsequent points.

The average number of goals scored per game in each of the major European soccer leagues is not more than three goals per match. Moreover, scores of 2-0 and 1-1 have been two of the five most frequently recorded full-time scores in the 5 best leagues in Europe (England, France, Germany, Italy and Spain) in recent seasons (Anderson and Sally, 2013). Interestingly, in the 2015-16 season, 1-1 was the most common result in these leagues (http://www.soccerstats.com) The same trend was observed in the Portuguese Premier League. In the 2015/16 season, 20% of matches ended with a total of two goals (i.e. the sum of total goals scored per game by both teams): 10% finished 1-1 (home draw, 38 matches), 7% 2-0 (home win, 21 matches) and 3% 0-2 (home defeat, 10 matches). The home advantage effect was confirmed in these matches. The home teams of the Portuguese Premier League scored 80 goals, while away teams scored 58 goals.

The advantage of playing at home may be related to several factors reported in literature, such as crowd support (Wolfson et al., 2005), travel (Pollard et al., 2008), familiarity with the game environment (Loughead et al., 2003), referees (Brandão et al., 2011) and territoriality aspects (Sampedro and Prieto, 2011). When the local team scores first, it excites fans and increases their interest in the match, while the away team’s early leading may distract the audience from the match (Courneya, 1990). From the socio-psychological point of view, the local public support is considered by own fans as decisive, which can reinforce the self-esteem of players and increase social identity that leads to improvement of team performance and a reduction of the negative effects of stress and anxiety (Wolfson et al., 2005). From the strategic and tactical point of view, scoring first and gaining a score advantage allow the winning team to extend the range of tactical options, for instance by creating more counterattack opportunities against the opposite team, which can opt for more risky strategies in the game.

The second goal might have a decisive impact on the match outcome, which is not less than the influence of the first goal (Anderson and Sally, 2013). The second goal may be the equalizer (0-1 to 1-1, or 1-0 to 1-1) or the goal, which enables a team to double their advantage (1-0 to 2-0, or 0-1 to 0-2). The anticipation of temporal localization of the second goal associated to its nature (i.e., goal which creates advantage or recovers from score disadvantage) seems to be useful for a timely adaptation of the team's tactics. However, there is a lack of data in the literature to the second goal of a match. One of the few studies which analysed this goal has been conducted by Nevo and Ritov (2012). The interaction between two random goal-scoring times (of the first and second goals) during a soccer match was examined in 760 games played from 2008 to 2010 (two full seasons) in the English Premier League. Using survival analysis methods the authors reported that the first goal occurrence could either expedite or impede the next goal, depending on the time it was scored.

In order to provide a better understanding of which factors influence the second goal being scored, it would be useful to examine how the time of the second goal is associated with a range of different match contexts. A soccer match is a complex dynamic process, in which certain events influence the subsequent course of the match, and this influence must be considered in analysis. In order to explain the relationship between different events, it is necessary to extract information regarding match progress using time as a variable of interest (Venturelli et al., 2011). Several studies have suggested using survival (also known as time-event) analysis for this purpose (Castilla, 2007; Nevo and Ritov, 2012). This tool involves the use of regression methods for explaining the relationship between independent variables and the time of an event of interest and it is considered to be the most suitable means for characterizing and explaining match progress compared to other tools commonly used in soccer performance analysis (Barros et al., 2009; Del Corral et al., 2008).

Thus, the first aim of this study was to analyse the association between the type of the second goal scored in a match (i.e. goal that increased the leading team's advantage or the goal that re-established equality in the scoreline) and the match venue, as well as the final match outcome. Secondly, the study aimed to examine the influence of the time when the first goal was scored and the current scoreline on the probability of the second goal being scored in a match. This knowledge could help coaches anticipate match scenarios and adopt in a timely manner the most appropriate tactics for the remaining part of the match.

Methods

Sample

The sample consisted of 1506 matches played in the Portuguese Premier League during six consecutive competitive seasons (from 2009-10 to 2014-2015). All data were collected from the official League website (http://www.ligaportugal.pt)

Statistical Analysis

Descriptive statistics and chi-square analysis were performed to examine second goals scored during the game period and the association between the type of the second goal being scored (score-doubling or score-equalizing) and the match venue as well as the final match outcome. In 29% of matches (443 out of 1506), the second goal was not scored. About 9% of matches (135 out of 1506) ended goalless and in 20% of matches (308 out of 1506) just one goal was scored. Thus, data were collected from 1063 matches in which the second goal was scored by a home team (586).

A Cox proportional hazards (PH) model was used to estimate the time of the second goal as a function of the time of the first goal in a match and the scoreline.

In survival analysis, the home team was considered as the reference team and the second goal of the match, when it was scored by the home team, was considered as the event of interest. If the away team scored the second goal of the match, this goal was considered as a censored observation. The response variable in the Cox Model was the time elapsed from the time when the first goal in a match was scored to the occurrence of the second goal, considered as the event of interest. Second goals scored in additional time in the first and second halves were recorded at the 45th and 90th min, respectively. Matches in which no goals or only one goal was scored were not considered. Almost half of 1063 matches (477) were censored because the away team scored the second goal of the match.

The Cox model relies on the assumption of the proportionality of hazards, implying that the factors analysed have a constant impact on the hazard over time (Broström, 2012). The proportionality assumption of data was checked to ensure a non-violation of the proportionality assumption. For this purpose the function cox.zph in the survival package, version 2.37-7 was used (Therneau, 2015). The p-value obtained in this function was significant (p < 0.05) and indicated that the proportionality assumption was not met for the variable time of the first goal in a match. Since the time of the first goal is a continuous covariate, it was necessary to categorize it in order to ensure the proportionality assumption. First, the distribution of the time of first goals was checked using a histogram, which showed that the interval of time during which first goals were scored may reasonably be split into four equal-length intervals using the cut function. The time of the first goal in a match is expressed as time in minutes from the start of the match and categorized in accordance with four classes: first period [0-15 min], second period [16-30 min], third period [31-45 min] and second half [46-90 min]. The current scoreline was also considered as a categorical variable in accordance with two classes: a score-doubling goal (the second goal that doubled the advantage) and an equalizing goal.

All statistical analysis was performed using Software R, version 3.0.2. For all analyses, statistical significance was set at p < 0.05.

Results

Data analyses showed that significantly more second goals were scored in the second half of matches (χ2 = 28.81, p < 0.05) compared to the first half (58% v. 42%, respectively). The highest frequency of the second goal being scored was recorded in the last 5 min periods of each half (Figure 1).

\"An

Frequency of the second goal of the match

As it can be seen in Table 1, 55% of second goals were scored by home teams and 45% by away teams. Home teams presented a greater percentage (58%) of second goals that doubled score advantage (1-0 to 2-0, or 0-1 to 0-2) as compared with away teams (44%). On the other hand, away teams scored a higher percentage (56%) of goals, which restored the score equality (1-0 to 1-1, or 0-1 to 1-1) in comparison with home teams (42%). The results of the chi-square test (χ2 = 20.23, p < 0.05) established a significant association between the match venue and the type of the second goal scored.

Table 1

Frequency, percentage and chi-square value for the second goal scored by home and away teams cross-referenced with the type of the second goal

Type ofsecond goal
Second goal of match1Score--0 to 2-doubling 0, or 0-1 to 0-2Score-equalizing 1-0 to 1-1, or 0-1 to 1-1nχ2
Home Team338 (58%)b248 (42%)a586 (55%)
Away Team209 (44%)a268 (56%)b477 (45%)20.23*
Total1063

Statistical significance

bPositive association adjusted residual >1.96
aNegative association adjusted residual <-1.96
*p < 0.05

Table 2 shows a significant association between the type of the second goal scored and the match outcome (χ2 = 521.08, p < 0.05). The team, which scored the second goal, won the match in 59% of cases. The score-doubling goal was strongly positively associated with a win outcome and the equalizing goals with a draw and loss outcome.

Table 2

Frequency, percentage, and chi-square value for the type of the second goal cross-referenced with the outcome of a match

Type of the secondOutcomeTotalχa
goalWinDrawLoss
Score-doubling506 (93%)b33 (6%)a8 (1%)a547
Score-equalizing123 (24%)a225 (44%)b168 (32%)b516521.08*
629 (59%)258 (24%)176 (17%)1063

Statistical significance

aNegative association adjusted residual <-1.96
*p < 0.05;

Table 3 displays a statistically significant association between the match outcome and the type of the second goal scored by home teams (χ2= 298.85, p < 0.05) as well as by away teams (χ2 = 218.55, p < 0.05).

Table 3

Frequency, percentage and chi-square value for the type of the second goal scored by home and away teams cross-referenced with the match outcome

Type of second goalWinOutcome DrawLossTotalχ2
Score-doubling314 (93%)b17 (5%)b7 (2%)b338
HomeScore-equalizing58 (23%)b108 (44%)b82 (33%)b248298.85*
teamTotal37212589586
AwayScore-doubling192 (92%)b16 (7%)b1 (1%)b209
Score-equalizing65 (24%)b117 (44%)b86 (32%)b268218.55*
teamTotal25713387477
1063

Statistical significance

bPositive association (adjusted residual >1.96)
bNegative association (adjusted residual <-1.96)
*p < 0.05

When home teams scored the score-doubling goal, they won 93% of matches, and when they scored the score-equalizing goal, they won 23%, drew 44% and lost 33% of matches. Away teams, when they scored the score-doubling goal, achieved victory in 92% of matches, and after scoring the equalizing goal they won 24%, drew 44% and lost 32% of matches.

Additionally, the frequency of the score-doubling goal of a match scored by home and away teams was positively associated with a win outcome and negatively associated with draw and loss outcomes. Draw and loss outcomes were significantly and positively associated with the equalizing goal of a match scored by both home and away teams and negatively associated with a win outcome.

The variables estimated using the Cox proportional hazard regression model (Table 4) revealed a significant positive effect of the time of the first goal on the next goal occurrence, i.e. first goal occurrence in later game periods steadily increased the probability of the second goal in a match being scored. At the same time, for home teams the current scoreline had no significant effect on the second goal occurrence in a match.

Table 4

Cox proportional hazard regression model

VariableCoefficientHazard Ratiop
Time of the first goal
0-151.00
16-300.3491.4190.001*
31-450.6451.906<0.001*
Second half1.1313.099<0.001*
Scoreline
Score-equalizing goal1.00
Score-doubling goal0.00011.000.998

Statistical significance:

*p<0.05

Discussion

In the present study, the time of the second goal scored in soccer matches was analysed. As it can be seen in Figure 1, in general, teams scored a larger number of second goals in the second half of matches, and the highest number of goals was scored during the last minutes of each half. Previous studies reported that the frequency of goals scored during a match was time-dependent, more goals were scored in the second half of matches and in the last 10- and 15-min periods of each half (Armatas et al., 2009; Dobson and Goddard, 2010). The tendency for increasing scoring rates over the time of a match could be attributed to physiological and tactical factors that influence teams’ performance. On the one hand, fatigue, which is greatest at the end of each half, leads to an increase in the number of technical and tactical errors, which may lead to more goal scoring opportunities. On the other hand, the little time remaining until the end of each half encourages players to use their last chances to score a goal that also may influence the match outcome.

In low-scoring team games such as soccer, scoring the second goal in a match could be crucial for winning. The results of this study confirm the effect of home advantage on the second goal being scored and subsequent victory in matches in the Portuguese professional Football League (Table 1). It was also found that the match venue had an impact on the second type of the goal scored. Score-doubling goals were positively associated with home matches, while equalizing goals were associated with away matches. Courneya and Carrón (1992) and Wolfson et al. (2005) suggested that an early lead in a match caused greater excitement and involvement of fans when the home team scored first. Score advantage reduces the negative effects of stress and anxiety and positively influences team’s performance, which could help home teams to enhance their score advantage.

The higher number of equalizing goals scored by away teams may be related to the defensive strategic behaviour adopted by home teams when they are winning and trying to maintain their score advantage. This tendency was reported by Dobson and Goddard (2010) for matches played in the English Premier League and by Lago-Peñas and Gómez-López (2014) for the Spanish Professional League matches, where teams used defensive strategy when winning and attacked more when losing in order to maintain the score advantage or to change the current result, respectively. A team that switches from a defensive to attacking style usually increases their own and also opponent’s probabilities to score (Armatas et al., 2009; Dobson and Goddard, 2010).

Home and away teams, which scored a doubling goal, won the majority of matches. Additionally, the doubling goals were positively associated with a winning match outcome. Since soccer is a low-scoring team sport, this result was expected. At the same time, the equalizing goals were positively associated with the draw and loss outcome; however, home teams and away teams both avoided defeat in approximately 68% of matches after scoring an equalizing goal, thus this goal was extremely important.

Regardless of the type of a goal (score-doubling or equalizing), scoring in soccer always has an impact on the subsequent course of the game, influencing players mentally and frequently leading to tactical adjustments of team’s play. Survival analysis demonstrated that the first goal scored in a match had a significant positive effect on the probability of the next goal being scored, and this probability was dependent on time, when the first goal of the match was scored (Table 4). Cox model variables revealed that the probability of the second goal of the match being scored by home teams gradually increased as a match progressed. When the first goal of the match was scored in the second or third 15-min period of the first half, the probability of home teams scoring the second goal increased by 42% and 190.6% respectively, as compared with the situation when the first goal of a match was scored in the first 15-min period of the first half.

Moreover, if the first goal occurred only in the second half, the probability of the home team scoring the second goal increased threefold (309.9%) as compared with cases where the first goal of the match was scored in the first 15 minutes. A similar tendency was reported for the Spanish Football League by Nevo and Ritov (2012), who suggested that, depending on the time when the first goal was scored, it could accelerate or delay the time when the next goal was scored. When a goal is scored before the 52nd minute, its effect on the probability of the next goal being scored is negative, while when the first goal is scored after that time the effect is positive. Furthermore, the results of the study demonstrate that once a goal is scored, another goal is less likely to be scored as compared with the situation where no goal has been scored (Nevo and Ritov, 2012).

This tendency can be explained by the influence of contextual factors on teams’ performance during the match, which has been demonstrated by several studies (Collet, 2013; Pratas et al., 2016). For instance, Heuer and Rubner (2012) showed that during the last ten minutes of matches of the German Premier Football League (Bundesliga) players’ behaviour depends significantly on the current score, representing an increasing offensive (or decreasing defensive) behavior (Heuer and Rubner, 2012).

Practical implications

The findings of the present study could prove useful for soccer coaches, as knowing that the occurrence of the first goal in later match periods steadily increases the probability of the second goal of a match being scored by the home team; therefore, coaches may adjust their decisions related to substitutions or tactical options in terms of attack and defence. During soccer practice players should be prepared for scenarios of mental pressure and physical fatigue, without reducing their self-efficacy in the last periods of training sessions.

Conclusions

The results of the present study demonstrate that the highest number of second goals (both score-doubling and equalizing) in a match was scored in the last 5-min period of each half. Different types of the second goal (score-doubling or equalizing) had a different impact on the match outcome for home and away teams. The time of the first goal in a match had a significant effect on the time of the next goal scored by home teams. This paper clearly demonstrates the influence of the match context (i.e. match venue, scoreline, and time of the first goal) on the probability of the second goal of a match being scored and also on the effect of the second goal on the match outcome. Further research is needed to identify performance indicators which are related to the time of the second goal being scored during soccer matches in different European leagues.

Acknowledgements

The first author received a PhD grant from the Portuguese Foundation for Science and Technology (SFRH/BD/80719/2011).

References

  • Anderson C, Sally D. The numbers game. New York: Penguin Books; 2013. [Google Scholar]
  • Armatas V, Yiannakos A, Papadopoulou S, Skoufas D. Evaluation of goals scored in top ranking soccer matches: Greek “Superleague” 2006-07. Serbian J Sport Sci. 2009;3:39. –. [Google Scholar]
  • Barros CP, Frick B, Passos J. Coaching for survival: the hazards of head coach careers in the German ‘Bundesliga’ Appl Econ. 2009;41:3303. –. [Google Scholar]
  • Brandão R, Sidónio S, Krebs R, Araújo D, Machado AA. The meaning of refereeing: perception of professional soccer referees. Rev Psicol Deporte. 2011;20:275. –. [Google Scholar]
  • Broström G. Event History Analysis with R. Boca Raton: CRC Press; 2012. [Google Scholar]
  • Castilla EJ. Dynamic Analysis in the Social Sciences, 1st Edition. USA: Elsevier, Inc; 2007. [Google Scholar]
  • Collet C. The possession game? A comparative analysis of ball retention and team success in European and international football, 2007–2010. J Sport Sci. 2013;31:123. –. [PubMed] [Google Scholar]
  • Courneya KS. Importance of game location and scoring first in college baseball. Percept Motor Skill. 1990;71:624. –. [Google Scholar]
  • Courneya KS, Carrón AV. The home advantage in sport competitions: A literature review. J Sport Exerc Psychol. 1992;14:13. –. [Google Scholar]
  • Cox DR. Regression models and life tables. J Roy Stat Soc B. 1972;34:187. –. [Google Scholar]
  • Del Corral J, Barros CP, Prieto-Rodríguez J. The Determinants of Soccer Player Substitutions: A Survival Analysis of the Spanish Soccer League. J Sports Econ. 2008;9:160. –. [Google Scholar]
  • Dobson S, Goddard J. Optimizing strategic behaviour in a dynamic setting in professional team sports. Eur J Oper Res. 2010;205:661. –. [Google Scholar]
  • Heuer A, Rubner O. How Does the Past of a Soccer Match Influence Its Future? Concepts and Statistical Analysis. PLoS ONE. 2012. p. 7. [PMC free article] [PubMed]
  • Lago C. The influence of match location, quality of opposition, and match status on possession strategies in professional association football. J Sport Sci. 2009;27:1463. –. [PubMed] [Google Scholar]
  • Lago C, Casais L, Dominguez E, Sampaio J. The effects of situational variables on distance covered at various speeds in elite soccer. Eur J Sport Sci. 2010;10:103. –. [Google Scholar]
  • Lago-Ballesteros J, Lago-Peñas C, Rey E. The effect of playing tactics and situational variables on achieving score-box possessions in a professional soccer team. J Sport Sci. 2012;30:1455. –. [PubMed] [Google Scholar]
  • Lago-Peñas C. The role of situational variables in analysing physical performance in soccer. J Hum Kinet. 2012;35:89. –. [PMC free article] [PubMed] [Google Scholar]
  • Lago-Peñas C, Dellal A. Ball possession strategies in elite soccer according to the evolution of the match-score: the influence of situational variables. J Hum Kinet. 2010;25:93. –. [Google Scholar]
  • Lago-Peñas C, Gomez-Lopez M. How important is it to score a goal? The influence of the scoreline on match performance in elite soccer. Percept Motor Skill. 2014;119:774. –. [PubMed] [Google Scholar]
  • Lago-Peñas C, Gómez-Ruano M, Megías-Navarro D, Pollard R. Home advantage in football: Examining the effect of scoring first on game outcome in the five major European leagues. Int J Per An Sport. 2016;16(2):411. –. [Google Scholar]
  • Leite WSS. Analysis of goals in soccer World Cups and the determination of the critical phase of the game. Phys Educ Sport. 2013;11(3):247. –. [Google Scholar]
  • Loughead TM, Carrón AV, Bray SR, Kim A. Facility familiarity and the home advantage in professional sports. Int J Sport Psychol Exerc Psychol. 2003;1:264. –. [Google Scholar]
  • Molinuevo JS, Bermejo JP. The effect os scoring first and home advantage in professional spanish football and indoor soccer leagues. Rev Psicol Deporte. 2012;21:301. –. [Google Scholar]
  • Nevo R, Ritov Y. Around the goal: Examining the effect of the first goal on the second goal in soccer using survival analysis methods. J Quant An Sports. 2012;9:65. –. [Google Scholar]
  • Njororai W. Timing of Goals Scored in Selected European and South American Soccer Leagues, FIFA and UEFA Tournaments and the Critical Phases of a Game. Int J Sports Sci. 2014;4(6A):56. –. [Google Scholar]
  • Pollard R, da Silva CD, Nísio CM. Home advantage in football in Brazil: Differences between teams and the effect of distance traveled. Brazilian J Soccer Sci. 2008;1:3. –. [Google Scholar]
  • Pratas JM, Volossovitch A, Carita AI. The effect of performance indicators on the time the first goal is scored in football matches. Int J Per An Sports. 2016;16:347. –. [Google Scholar]
  • Sampedro J, Prieto J. The territoriatility as a factor associated to the advantage of playing at home. A comparative study by regions in the Spanish Football League and the in the Spanish Futsal League. Motricidad. Eur J Hum Movement. 2011;26:93. –. [Google Scholar]
  • Tenga A. World Congress of Performance Analysis of Sport IX. London & New York: Routledge Taylor & Francis Group; 2012. First goal and home advantage at different levels of play in professional soccer; pp. 47\u201351. Editors: D. Peters, P. G. O’Donoghue. –. [Google Scholar]
  • Therneau T. A Package for Survival Analysis in S. R package version 2.37-7. 2015. http://CRAN.R-project.org/package=survival; Available at. accessed on 01.08.2016.
  • Venturelli M, Schena F, Zanolla L, Bishop D. Injury risk factors in young soccer players detected by a multivariate survival model. J Sci Med Sport. 2011;14:293. –. [PubMed] [Google Scholar]
  • Wolfson S, Wakelin D, Lewis M. Football supporters' perceptions of their role in the home advantage. J Sport Sci. 2005;23:365. –. [PubMed] [Google Scholar]

Articles from Journal of Human Kinetics are provided here courtesy of Academy of Physical Education in Katowice, Poland

\n \n
\n
\n \n
\n\n
\n
\n \n
Cite
\n
\n
\n
\n \n Copy\n \n\n \n Download .nbib\n .nbib\n \n\n\n \n\n
\n \n \n
\n
\n
\n
\n
\n\n \n \n \n \n \n \n\n\n\n \n \n \n \n \n \n \n \n\n \n\n\n\n\n\n\n\n\n \n \n \n\n \n \n\n \n \n\n\n \n \n \n\n\n \n \n \n\n\n\n", + "page_last_modified": "" + } + ] +} \ No newline at end of file