Corner Kick Characteristics: A Case Study of the 2020/21 Northern Ireland Football League (NIFL) Premiership Season

ABSTRACT

In the 2020/21 NIFL Premiership regular season, 12% (70) of goals scored came from corner kicks. However, the effectiveness of corner kicks at a club level ranged from 5% to 17.5%. Thus, individual coaches ability to create effective strategies to impact corner kick outcomes justifies investigation. The aim of this study was to describe how corner kicks were taken across the 2020/21 (NIFL) Premiership season, and to assess the effectiveness of offensive and defensive corner kick strategies. From 195 matches, 1988 corner kicks from video recordings were analysed, examining 18 corner kick outcome variables. Results were recorded using a hand notation observation instrument and data analysed through Microsoft Excel v16.59 and IBM SPSS v27. 70 goals were scored (3.5% of corners taken), accounting for 12% of goals scored (581). Defending team quality (p = 0.034), venue (p = 0.005), and path of ball (p = 0.002) significantly affected the likelihood of an attempt at goal. Most goals came from inswinging corners (80%) and were most likely (5.4%) to be scored when the ball was delivered into the central area of the 6-yard box (GA2). To better understand individual corner style and contextual factors, further research should focus at team level.

KEYWORDS:

• Performance analysis
• football
• soccer
• corner kick
• set pieces

1. Introduction

Performance analysis is an integral part of the coaching process in football (Beare & Stone, 2019) with advances in technology making statistical and video analysis a much less onerous task (Hughes & Franks, 2015). These developments mean that clubs outside the “Big Five” European footballing nations can now access their own statistics and videos, as well as their competitors, to inform and improve coaching practices. Accordingly, football in these countries can evolve from part-time leagues by offering full-time opportunities to take advantage of new technology and training processes (Kubayi & Larkin, 2019). In recent years, 3 of the 12 (25%) NIFL clubs have turned professional (from semi-pro) as the league grows, through increased attendance and increased financial opportunities garnered through the restructure of European competitions. With full-time teams attempting to gain more on-field training time, the remaining part-time teams need to be able to gain advantages without the luxury of full-time resources. In this situation, the lack of time available to collect and process information has been identified as a limitation to the use of performance analysis (Barker-Ruchti et al., 2021).

Teams at every level are looking for competitive advantages. Set-pieces, and corner kicks in particular, provide the attacking team with time to restart play that is not always available during open play (Maneiro et al., 2019) and thus specific actions can be replicated from a defined starting position in training scenarios. Corner kick analysis across the duration of the season provides comprehensive data and the opportunity for detailed team comparisons (Prieto-Lage et al., 2021) and particularly in smaller leagues where teams play each other more often. However, there is minimal corner kick research that spans a full season.

Of the set-pieces, the corner kick is one of the most researched areas (Casal et al., 2015) due to its high frequency, 10 per game (Maneiro et al., 2019), high uniformity – as corner kicks can only be taken from 2 places on the pitch – and higher scoring probability 2.1% compared to 1.1% from a free kick (Power et al., 2018). Scoring from a corner also had a high impact on the game result, producing in a victory or a draw in 76% of occasions (Casal et al., 2015). Consequently, corner kicks have been identified as a crucial part of offensive performance (Lee & Mills, 2021). The present study, therefore, should provide a unique insight into the behaviours of NIFL Premiership teams at corner kicks while offering insight for coaches more broadly as part of the coaching strategy process to improve performance.

The present study contextualises corner kick research in the NIFL Premiership setting comprising a mix of full- and part-time teams. Based on previous research, match status can significantly influence the technical and tactical behaviours of teams and players (Lee & Mills, 2021), while team quality has demonstrated improved efficiency (3.3% vs 2.9%) from corner kicks by top 6 teams (Strafford et al., 2019). Differing pitch type is becoming more common (Andersson et al., 2008) in leagues outside the “Big Five” such as NIFL which is played on a mix of synthetic 4 G surfaces (25%) and natural grass pitches (75%).

Home advantage has been demonstrated to positively influence match outcome (Fernández-Hermógenes et al., 2021; Lago-Peñas & Lago-Ballesteros, 2011) across a range of sports (Marek & Vávra, 2017). Although, mixed results have been reported concerning the influence of crowds (Van de Ven, 2011), large crowd size has been positively associated with better performances of home teams (Volossovitch et al., 2013) with referee decisions favouring the home team (Nevill et al., 1996), indicating the need to investigate the influence further (Van de Ven, 2011).

Although other studies found no statistical location advantage (Prieto-Lage et al., 2021), match location has been promoted as a variable which requires further study (Pulling, 2015) due to the number of corner kick studies carried out at international competition hosted at neutral venues; with the number of games played by each team resulting in the potential for successful team playing style to be overrepresented (Casal et al., 2015).

Studies related to time period, show that corner kicks are most often taken in the last third of games (Lilić et al., 2020) and that shots on target from corner kicks are most common in the first and last 30 minutes of games; with goals more common in the last 30 minutes (Casal et al., 2015). Recent studies demonstrate a changing trend to corner kicks across the 2010–2018 World Cups (Maneiro et al., 2021). The results from these first five variables create a quandary for coaches – working with limited player contact time – as to where to prioritise match day preparation and in particular corner kick strategies.

The corner kick delivery has generated conflicting results in two aspects. First, whether inswinging (Carling et al., 2005; Power et al., 2018) or outswinging (Schmicker, 2013) corner kicks are more favourable based on corner kicks taken, goals scored or efficiency. Second, whether higher rates of goals have been scored from direct delivery (Pulling, 2015) or short deliveries (Casal et al., 2015).

Previous research highlights inconsistencies related to the delivery area. Some excluded this variable (Carling et al., 2005; Sainz; De Baranda & Lopez-Riquelme, 2012; Pulling et al., 2013), others simplified the delivery area to near and far post (Casal et al., 2015), whilst others split the 18-yard area into distinct boxes (Schmicker, 2013). However, since Taylor et al. (2005) discovery of a “critical area” 6–9 yards from the goal line and width of the goal area, research has tended to use this model as a starting point for investigations (Beare & Stone, 2019; Lee & Mills, 2021; Pulling, 2015). This area was deemed critical for greatest frequency of first contacts generating a high percentage of shots at goal (Beare & Stone, 2019; Pulling, 2015).

Despite Page and Robins (2012) reporting that attempts at goal were characterised by a low number of attacking actions, their research does not state whether the defining outcome was performed in this area. It is thus important to record both the delivery area and area of the outcome to provide an accurate representation of where outcomes occur. Pulling (2015) concludes that the delivery area is more important than delivery type for achieving attempts at goal from corner kicks.

Defensive set-up is characterised in two ways: whether teams employ man-to-man or zonal marking strategies, and whether teams have players on the post (near and/or far). Previous studies have found no significant association between the marking set-up and the number of attempts conceded when defending corner kicks; however, those teams employing zonal marking strategies conceded fewer attempts and fewer goals, than those using man-to-man marking (Pulling et al., 2013). While other studies produce conflicting findings in support of zonal marking (Power et al., 2018) or man-to-man marking (Kubayi & Larkin, 2019). Contrasting research also found that by not positioning players on the goalposts teams were more effective in preventing goals (Kubayi & Larkin, 2019).

Finally, interaction context involves the combination and number of players in the box at a corner kick. Although there tend to be more defenders than attackers in the box (Maneiro et al., 2019); there is an increasing trend in which we observe more players in the 18-yard area at corner kicks. The frequencies of having six or more attackers and defenders increased across World Cups between 2010 and 2018 (Maneiro et al., 2021).

It is important to utilise 100% of the matches available (Kubayi & Larkin, 2019), in research to take account of the disparity of set piece effectiveness between teams in the same league rather than a small subset. A point demonstrated when exploring the 2016/17 English Premier League season, for which 16% of all goals were a result of set pieces with a variance of 7% to 37% between teams (Power et al., 2018). Therefore, the present study analysed all games from a full season of a league competition to provide an accurate assessment of the trends from its teams within the competition, Further studies have drawn conclusions related to corner kick efficiency (Beare & Stone, 2019) or offensive and defensive efficacy (Mitrotasios, 2021); however, further individual characteristics can provide actionable evidence to inform coaches decision making.

Previous literature demonstrates inconsistencies in the study design, exploring various variables with differing definitions resulting in a failure to reach consensus on the impact of several key characteristics. This lack of operational definition in performance analysis (Williams, 2012) is perpetuated by the conflicting nature of study design, lack of consistency, ambiguity and repetition in the definitions researched (Williams, 2012) increases the rationale for this bespoke analysis of set pieces in context. Identification and definition of performance behaviours is essential prior to designing a coding system (O’Donoghue, 2007; Williams, 2012).

The present study adds value to this important research area by investigating a full season’s data across all teams within the league with measurement across eighteen research informed and clearly defined variables. By giving due consideration to the contextual nature of variables this study potentially offers an applied science perspective to impact practice (Mackenzie & Cushion, 2013).

The aim of the present study was to describe how corner kicks were taken across the 2020/21 (NIFL) Premiership season, and to assess the effectiveness of offensive and defensive corner kick strategies. By exploring the relationships between the corner kick characteristics, potential cause and effect scenarios were identified, demonstrating the traits of successful corner kicks. In particular, the individual teams’ offensive and defensive efficiency ratios in relation to corner kicks, shots, and goals were established.

2. Methods

2.1. Sample

Secondary data analysis was used (Beare & Stone, 2019; Casal et al., 2015; Lee & Mills, 2021; Pulling, 2015) to explore the 2020/21 NIFL Premiership regular season which consisted of 198 matches, whereby 12 teams played each other on three occasions, either two at “home” and one “away” or vice versa as determined by the fixture schedule (Premiership Rules and Regulations Season 2020/21, NIFL). When all teams completed 33 matches (known as the regular season), the league split into two sections: top 6 and bottom 6. However, during these post-split games, it was noted that several teams in each section had used these matches to rotate their squad ahead of upcoming cup or playoff games. Therefore, to limit any additional contextual interference (Mackenzie & Cushion, 2013), the present study purely focused on the corner kicks from the original 198 matches of the regular season and ignore the post-split matches. Of these 198 matches, three games could not be sampled due to the unavailability of footage. Overall, 1988 of the 2050 corner kicks that were taken during the 195 matches available were analysed in the current study. 7 corner kicks could not be recorded due to video issues, 29 did not enter the field of play, and 26 were excluded as the intention of the corner taking team was to waste time rather than to create a goal scoring opportunity (Pulling, 2015). The current study was approved through the internal ethics filter committee.

2.2. Procedures

Pre-tagged video footage of the corner kicks was accessed through the Wyscout platform, whereby teams voluntarily uploaded match videos. The researcher then created corner kick playlists. This analysis software allowed recordings to be paused, replayed, played in slow-motion, and scrolled through frame by frame to increase tagging accuracy (Lee & Mills, 2021). Data was then input into Excel under the listed variables. Coding was completed in no longer than 2-hour sessions, with a minimum break of 30 minutes between sessions to minimise the risk of errors due to coding fatigue (Beare & Stone, 2019; Lee & Mills, 2021). Corner kicks were considered complete when the ball had either left the field of play or the attacking final third and did not immediately re-enter (Pulling et al., 2013). Prior to data collection, pilot testing was completed on 176 (8.6%) corner kicks to test the functioning of the coding system. This led to the addition of “recycled” into the “outcome” variable.

2.3. Observational designs

Observational designs are configured from three key criteria: Units of study, temporality, and dimensionality (Anguera et al., 2011; Villaseñor et al., 2001). The study of units adopted within this article reflects an idiographic study whereby the (football) team is the unit, the objective is to determine the attacking and defensive effectiveness of the team. The temperality was reflected through tracking, in particular of modifications in the patterns of behaviour along the temporal continuum. The dimensionality involves the joint consideration of different levels of response through multidimensionality. By generating 18 variables and comparing each at a team level this study attempts to assess the effectiveness of offensive and defensive corner kick strategies in the NIFL Premiership. By tracking the patterns of behaviour this study will describe how corner kicks were taken across the 2020/21 (NIFL) Premiership season providing league-level data for comparison, while presenting individual multidimensional data relevant at a practical level denoting interactions between situation variables. The detailed analysis of teams as case studies over a sustained period represents a more detailed approach to analysis, with comparisons between case studies offering specific insight into the characteristics of interest (Garganta et al., 1997).

2.4. Observational instrument (hand notation)

The coding system for the hand notation observational tool (Table 1) to record the characteristics of the corner kicks was adapted from previous empirical research (Beare & Stone, 2019; Casal et al., 2015; Lee & Mills, 2021). The implementation involved inputting data collected into Excel manually. This study used the pitch markings of the attacking area outlined in Figure 1.

Figure 1. Corner kick delivery areas (Beare & Stone, 2019).

Table 1. Operational definitions for the corner kick characteristics (adapted from Lee & Mills, 2021; Beare & Stone, 2019; Pulling, 2015; Casal et al., 2015).

Variable	Definition
Match number	Chronological order of games for the attacking team (1–33).
Corner taking team	Rank of the attacking team from 1–12 in where they lay in the table after 33 matches.
Final position of attacking team	Top6: Finished in the Championship Group (1–6). Bottom6: Finished in the Relegation Group (7–12).
Defending team	Rank of the defending team from 1–12 in where they lay in the table after 33 matches.
Final position of defending team	Top6: Finished in the Championship Group (1–6). Bottom6: Finished in the Relegation Group (7–12).
Venue	Home: The corner taking team played at home. Away: The corner taking team played away.
Surface	Grass: The match was played on grass. 4 G: The match was played on a synthetic surface.
Time	T15: 0’-15’ T30: 15’-30’ T45: 30’-Half Time. T60: 45’-60’ T75: 60’-75’ T90: 75’-Full Time.
Match status	Win: The corner taking team is ahead. Draw: The game’s score is level. Lose: The corner taking team is behind.
Position	Right: The corner is taken from the attacking teams’ right-hand side. Left: The corner is taken from the attacking teams’ left-hand side.
Laterality	Natural: Right-foot kick from the right or left-foot kick from the left. Switched: Right-foot kick from the left or left-foot kick from the right.
Short option	Static: Two players are standing over the ball immediately before the corner is taken. Dynamic: One player stands over the ball, while another player runs towards the ball looking for a pass. No: No players go looking for a short pass immediately before the corner is taken.
Delivery	Direct: The ball is kicked into the 18 yd box with just one touch. Short: The ball is kicked to an attacking player who is in short proximity to the initial corner kick taker.
Path of ball	Inswinger: The ball was kicked and moved through the air in a curve towards the goal. Outswinger: The ball was kicked and moved through the air in a curve away from the goal. Other: The ball was kicked with no curve or did not enter the 18 yd box aerially.
Interaction context	EQ: The attacking team had the same number of players as the defending team in the attacking area. INF1: The attacking team had 1 fewer player than the defending team in the attacking area. INF2: The attacking team had 2+ fewer players than the defending team in the attacking area.
Posts	Near: 1 player within touching distance of the nearest post to the corner. Far: 1 player within touching distance of the furthest post to the corner. Both: 2 players within touching distance of each of the goalposts. None: No players within touching distance of either of the goalposts.
Zone of pass/ Action area (See Figure 1)	Nine zones located inside and at the edge of the 18 yd box (Figure 1) The goal area (6 yd box) was divided into 3 zones: The goal area 1 (GA1), goal area 2 (GA2) and goal area 3 (GA3). The critical area (located between the 6 yd box and penalty spot and covering the width of the 6 yd box) was also divided into 3 zones: critical area 1 (CA1), critical area 2 (CA2) and critical area 3 (CA3). The two central zones (GA2 and CA2) cover the width of the goal. Short: The front zone covers the area outside the 6 yd box closest to the corner taker and is the length of the 18 yd box. Long: The back zone covers the area outside the 6 yd box furthest from the corner taker and is the length of the 18 yd box. Edge: An area the width of the 6 yd box located between the penalty spot and the edge of the semi-circle of the 18 yd box.
outcome	Goal: Corner-taking team scores a goal. On Target: Any goal attempt that was heading towards the goal which was saved by the goalkeeper or blocked in the goal area by a defensive player. Off Target: Any attempt by the attacking team that was either not directed within the dimensions of the goal, contacted the crossbar or either of the posts, or blocked by a defensive player away from the goal area. Recycled: The attacking team retained possession but did not produce and attempt at goal. Corner: The defensive team concedes another corner. DefFoul: The defensive team concede a penalty (if contact in the 18 yd box) or free kick (if outside of the 18 yd box). AttFoul: The referee awards a free kick to the defensive team. GKPunch: The goalkeeper contacted the ball by using a punching action, and subsequently the ball is cleared. GKCatch: The goalkeeper gained possession of the ball by catching or diving on top of the ball. Cleared: The attacking team lost possession of the ball as a result of the corner kick. This was defined when the ball exited the attacking third and was not re-delivered by the attacking team.

2.5. Reliability

Intra-observer (Viera & Garrett, 2005) and inter-observer (Beare & Stone, 2019) reliability tests were conducted – across 227 corner kicks (11.4% of corners taken) six-week post analysis to assess the reliability of data collection methods and subsequent data collected. Limitations in access and time meant that intra rater observer was not carried out for observer 2. Observer 1 was UEFA B qualified coach and performance analyst with over 20 years’ experience. Observer 2 was NCC qualified and 6-month experience as a performance analyst with level 4 performance analysis award.

Intra- and inter-observer reliability of the data was quantified through the Kappa statistic. Reliability of each variable is presented in Table 2. Mean kappa statistics of k = 0.90 and k = 0.73 corresponding to near perfect intra-observer agreement, and substantial inter-observer agreement (Altman, 1999).

Table 2. Intra-observer and inter-observer reliability values.

Variable	Intra-rater Oberserver1-Observer1	Inter-rater Oberserver1-Observer2
Position	1.0	0.91
Laterality	1.0	0.91
Short option	0.86	0.79
Delivery	0.95	0.79
Path of ball	0.86	0.71
Interaction context	0.87	0.75
Posts	0.83	0.64
Zone of pass	0.85	0.54
Action area	0.84	0.48
Outcome	0.91	0.75
Ktotal	0.90	0.73

2.6. Data analysis

Data were recorded in an observation sheet in Microsoft Excel to calculate the relative frequencies of each corner characteristic and corner outcome. The data were analysed further in SPSS (v27) with Pearson’s Correlations used to examine the relationships between variables. Bivariate analyses with contingency tables (X² and r) were used to analyse goals scored and all attempts on goal (goal, attempts on target, attempts off target) (Casal et al., 2015). Significance was noted at p < 0.05 and p < 0.01 levels. Cramer’s V (V) effect sizes were calculated and described as small (V = 0.10), medium (V = 0.30) or large (V ≥0.50) (Beare & Stone, 2019).

3. Results and discussion

The findings presented below analysed the statistics of corner kicks delivered in the 2020/21 NIFL Premiership season. A total of 1988 corner kicks were analysed, with an average of 10.2 corner kicks per game (see Table 3), comparable to previous research (10.2) by Casal et al. (2015).

Table 3. Descriptive analysis of corner kicks (n = 1988) during the 2020–21 season.

Variable	Frequency	Percentage
Venue Home Away	1078 910	54.2% 45.8%
Pitch Type Grass 4 G	1518 470	76.4% 23.6%
Time 0–15 15–30 30–45+ 45–60 60–75 75–90+	314 291 318 316 323 426	15.8% 14.6% 16.0% 15.9% 16.2% 21.4%
Match Status Win Draw Lose	543 920 525	27.3% 46.3% 26.4%
Position Left Right	961 1027	48.3% 51.7%
Laterality Natural Switched	408 1580	20.5% 79.5%
Short option Static Dynamic No	257 261 1470	12.9% 13.1% 73.9%
Delivery Direct Short	1808 180	90.9% 9.1%
Path of ball Inswinging Outswinging Other	1493 403 92	75.1% 20.3% 4.6%
Interaction context EQ INF1 INF2	20 363 1605	1.0% 18.3% 80.7%
Posts Near Far Both None	710 482 297 499	35.7% 24.2% 14.9% 25.1%
Zone of pass GA1 GA2 GA3 CA1 CA2 CA3 Short Long Edge	371 554 151 91 389 144 188 64 36	18.7% 27.9% 7.6% 4.6% 19.6% 7.2% 9.5% 3.2% 1.8%
Action area GA1 GA2 GA3 CA1 CA2 CA3 Short Long Edge	193 423 144 62 308 106 159 165 428	9.7% 21.3% 7.2% 3.1% 15.5% 5.3% 8.0% 8.3% 21.5%
Outcome Goal OnTarget OffTarget Recycled Corner DefFoul AttFoul GKPunch GKCatch Cleared	70 119 345 243 151 11 74 76 152 747	3.5% 6.0% 17.4% 12.2% 7.6% 0.6% 3.7% 3.8% 7.6% 37.6%

There were a total of 534 attempts at goal (26.9% of corners taken) from the corner kicks analysed, of which, 345 (17.4%) were attempts off target, 119 (6%) attempts on target (excluding goals) and 70 (3.5%) resulting in a goal. This is higher than previous efficiency values reported which range from 2.1% to 3.1% (Casal et al., 2015; Power et al., 2018; Pulling, 2015; Pulling & Newton, 2017; Strafford et al., 2019). Therefore, this finding suggests that corner kicks are more effective at producing goals in the NIFL Premiership and should be an important area for teams to focus on offensively and defensively during the match preparation. Goals from corner kicks accounted for 12% of the 581 goals scored across the 2020/21 NIFL Premiership regular season.

The most frequent corner kick characteristics were taken at home (54.2%), grass pitch (76.4%), match was level (46.3%), after the 75^th minute (21.4%), taken on the right side of the pitch (51.7%), switched laterality (79.5%), direct deliveries (90.9%), inswinging (75.1%), an inferior interaction context of 2+ (80.7%), a defender only positioned at the near post (35.7%), delivered into area GA2 (27.9%), action area of the edge (21.5%) and the corner being cleared (37.6%).

These figures describe corner kick characteristics across the season and provide limited insight for a coach. To test the relationships between variables a summary Pearson’s r Correlation is presented in Table 4.

Table 4. Summary Pearson's r correlation highlighting relationships between variables (significance highlighted at the 0.05 level (*) and 0.01 level (**)).

		Match Status	Position	Laterality	Short Option	Delivery	Path of Ball	Interaction Context	Posts	Zone of Pass
Venue	Pearson Correlation	.086**	−.065**	−.016	.027	.013	−.001	−.042	−.036	.026
	Sig. (2-tailed)	<.001	.004	.487	.231	.572	.954	.064	.107	.245
Pitch Type	Pearson Correlation	.010	−.018	.022	−.149**	.130**	.018	−.044	.017	.125**
	Sig. (2-tailed)	.653	.410	.330	<.001	<.001	.429	.052	.460	<.001
Time	Pearson Correlation	.033	−.021	−.034	.105**	−.035	.012	−.013	−.007	.000
	Sig. (2-tailed)	.143	.351	.129	<.001	.123	.593	.565	.742	.995
Match Status	Pearson Correlation		−.016	−.011	.062**	−.051*	−.026	.039	.006	−.039
	Sig. (2-tailed)		.474	.612	.005	.023	.249	.081	.792	.081
Position	Pearson Correlation			−.272**	.039	−.021	.214**	−.007	.059**	.079**
	Sig. (2-tailed)			<.001	.081	.349	<.001	.767	.009	<.001
Laterality	Pearson Correlation				−.023	.000	−.694**	−.002	−.042	−.265**
	Sig. (2-tailed)				.304	.991	<.001	.927	.063	<.001
Short Option	Pearson Correlation					−.400**	−.138**	.429**	−.242**	−.201**
	Sig. (2-tailed)					<.001	<.001	<.001	<.001	<.001
Delivery	Pearson Correlation						.396**	−.224**	.148**	.476**
	Sig. (2-tailed)						<.001	<.001	<.001	<.001
Path of Ball	Pearson Correlation							−.075**	.096**	.421**
	Sig. (2-tailed)							<.001	<.001	<.001
Interaction Context	Pearson Correlation								−.290**	−.109**
	Sig. (2-tailed)								<.001	<.001
Posts	Pearson Correlation									.068**
	Sig. (2-tailed)									.002

**Correlation is significant at the 0.01 level (2-tailed).

*Correlation is significant at the 0.05 level (2-tailed).

3.1. Relationship between variables

There was a significant association for match week against the quality of the attacking (r = −0.064, p = 0.004) and defending (r = 0.065, p = 0.004) teams. As the season progressed, the better-quality teams took more corner kicks, whilst the weaker teams defended more. This may have been a result of the higher quality of team resulting in more possession in games and thus more opportunities to generate corners. Team quality is important in determining technical and tactical performances in matches (Lago-Peñas & Lago-Ballesteros, 2011).

Similarly, the higher ranking of the full-time teams in the league – who have more contact time with players – may have provided additional time integrate analysis and plan to play against the same lower opposition in their second and third league games.

3.2. Team quality

The top 6 teams had significant associations with laterality, taking more corner kicks with switched delivery (r = −0.094, p < 0.001). This could imply that the top 6 teams have more players capable of taking corner kicks from either side, rather than relying on single players taking them from both sides of the pitch. Having a set piece specialist that takes from both sides would limit the inswingingers that teams are able to deliver. Top 6 teams also provide more short options (r = 0.091, p < 0.001), and play short more often (r = −0.118, p < 0.001), than their bottom 6 counterparts. They include those teams that are full time and train more often, so could use that advantage to work on set piece routines that involve working the ball into a dangerous area, rather than delivering directly.

Weaker teams had significant associations when defending in their interaction context (r = −0.108, p < 0.001) with less numerical supremacy than their top 6 counterparts, and how they defended the posts (r = −0.05, p = 0.027). By using more short corners, top 6 teams force the opposition teams to react by moving players from the posts to close the nearest players with the ball. This takes players out of the area, reducing the number of players defending in the area, negatively affecting their interaction context. There was also a significant negative correlation between defending team’s strength and outcome (r = −0.067, p = 0.003), with weaker teams more likely to concede shots on goal.

Overall, top 6 teams took 53.1% of the corner kicks and defended only 41.7%. Whilst previous research found team quality to not be significantly associated to corner outcomes (Lee & Mills, 2021), this study found that the quality of the defending team was significant in corner outcomes and likelihood of an attempt on goal. Therefore, with weaker teams more likely to concede a corner, and more likely to concede an attempt on goal, defending corner kicks should be an area that NIFL Premiership teams in the lower half of the league concentrate on as part of their preparation for matches to improve their results.

3.3. Venue and pitch type

Home teams delivered more corner kicks (54.2%) and were more effective in conversion into goals (4.2% vs 2.7%). This supports research by Fernández-Hermógenes et al. (2021) who found home teams in Spain took 55.6% of corner kicks. Considering that home teams are said to have higher attacking variables such as possession, entries into the box, crosses and shots (Lago-Peñas & Lago-Ballesteros, 2011; Seçkin & Pollard, 2008; Tucker et al., 2005), this may generate increased opportunity to be awarded a corner. Home corner taking teams had significant associations with match status (r = 0.086, p < 0.001), so they were more likely to be taking corner kicks while winning or drawing compared to the away teams. This could be attributed to the influence of the crowd which has been positively associated with referee decisions favouring the home team (Nevill et al., 1996). The outcome of the corner was also significant (r = 0.068, p = 0.002) with home teams more likely to get a positive outcome, which could be explained by pitch familiarity as many teams in the league also train on their pitch.

Corner kicks taken on 4 G were significantly associated with having a short option (r = −0.149, p < 0.001) and more likely to be played short (r = 0.130, p < 0.001). Considering that artificial pitches can be used more frequently throughout the season with less maintenance compared to grass pitches (Zanetti et al., 2013). The pressure on resources within the NIFL semi-professional league could negatively impact the preparation of pitches, subsequently, 4 G surface presents a lower risk of turnover for the corner taking team. This is of particular importance in the NIFL with the recent increase of teams using 4 G as their home pitch surface (25% to 42%).

3.4. Situational variables

Time of corner kick was significantly associated with having a short option available (r = 0.105, p < 0.001), but not on the delivery method. This would suggest that short corner options are more prevalent earlier in the match, as teams use predetermined corner routines as soon as they can. This finding supports the trend of a more offensive tactical approach to corner kicks from the start of matches (Maneiro et al., 2021). However, this routine may or may not be used at that time as delivery method is not significantly correlated.

Most goals were scored in 75’-90’+ (18) supporting previous studies related to the most efficient period for conversion to goals (Lilić et al., 2020). A rationale for which could be physical and mental fatigue of the defensive team (Casal et al., 2015). This is of relevance in the NIFL Premiership which consists of full- and part-time teams with a diversity of fitness levels which may impact concentration. All teams, whether full- or part-time, should therefore have strategies in place to counteract or exploit corner kicks taken in the last fifteen minutes under these circumstances.

3.5. Match status

Corner kicks were mostly taken with the game state level (46.3%) and resulted in the most goals (29), supporting previous studies (Sainz Casal et al., 2017; De Baranda & Lopez-Riquelme, 2012; Lee & Mills, 2021; Prieto-Lage et al., 2021; Strafford et al., 2019). However, the conversion ratio to a goal (3.2%) was lower when compared with when teams were winning (3.7%) or losing (4.0%). These results differed from Strafford et al. (2019) who found teams winning or drawing to be significantly more likely to score. Whilst this study’s results were not statistically significant, it could still imply that teams in the NIFL Premiership demonstrate less caution when losing to get back in the game or are being overwhelmed by the opposition when defending.

Match status was found to be significantly associated with having a short option (r = 0.062, p = 0.005) and delivery style (r = −0.051, p = 0.023) for teams that were winning, supporting the findings of previous research (Sainz De Baranda & Lopez-Riquelme, 2012; Lee & Mills, 2021). Winning teams are under less pressure to deliver directly into the area.

3.6. Delivery method

The most frequent delivery type was the inswinger (75.1%), which supports, and is significantly higher, than previous research (Beare & Stone, 2019; Power et al., 2018; Strafford et al., 2019). Delivery type was also associated with an attempt on goal, with “other” deliveries generating a higher conversion rate (40.2%), than outswingers (29.8%) or inswingers (25.3%); however, inswingingers were more likely to result in a goal (3.8%) and contributed to 56 of the 70 goals (80%). As inswingers also had a significant correlation with zone of pass (r = 0.476, p < 0.001), it suggests that these findings concur with Power et al. (2018) that the likelihood of scoring from an inswinging cross is greater as the delivery area is closer to the goal. As inswingers are more prevalent in the NIFL Premiership, teams and coaches should consider appropriate defensive measures to increase their likelihood of defending such corner kicks.

The position of the corner kick was significantly associated with laterality (r = −0.272, p < 0.001). Switched laterality (79.5) was far superior to natural laterality (20.5%), with corner kicks taken from the left more likely to be taken with the right foot, than corner kicks taken from the right, with the left. Perhaps because there are more right-footed players than left-footed players, so finding an appropriate left-footed corner kick taker can prove challenging for teams with limited resources. This rationale could also explain why position (r = 0.214, p < 0.001) and laterality (r = −0.694, p < 0.001) were both significantly associated with the path of the ball.

Having a short option was significant at p < 0.001 level for delivery (r = −0.400), interaction context (r = 0.429), how the posts were defended (r = −0.242) and zone of pass (r = −0.201). These results all signify that the attacking team can affect the defending team’s defensive strategy by having short options. This highlights a potential focus area for coaches with limited resources, by working on a short corner option and being aware of the attacking threat from short corners (Kubayi & Larkin, 2019), teams can disrupt the well-prepared defensive strategies of the full-time teams in the league. In particular, the short option may require coaches to make decisions concerning who to send out to defend the short corner.

Interaction context and defending the posts were also significantly associated with each other (r = −0.290, p < 0.001), as there is a limited number of defenders free in the area, defending teams must prioritise where they can best utilise any players that aren’t marking attackers. Defending teams should quickly send two players to defend the short corner to avoid a 2v1 (Parker 2008); however, which players are chosen to defend the short corner may be determined by the data related to delivery area of the opposition team.

In summary, having a short option significantly effects, or is significantly affected by the pitch type, delivery, interaction context, defending the posts and the zone of pass. Therefore, having a short option affects the interaction context and how the defending team defend their posts. This in turn affects the delivery and zone of pass. Playing on a 4 G pitch increased the likelihood of having short options, but only significantly affected the delivery and zone of pass. Defending team quality (r = −0.067, p = 0.003) and venue (r = 0.068, p = 0.002) were the significant (p < 0.01) factors in the outcome of corner kicks, however, to analyse outcomes in more detail, a bivariate analysis testing associations via chi-squared is required.

3.7. Defensive set-up

The most popular set-up for defending corner kicks in the NIFL Premiership was guarding the near post only (35.7%), followed by no one on the posts (25.1%), far post only (24.2%) and both (14.9%). The defensive set-up was significantly correlated with interaction context (.290), short option (.242), delivery (.148) and path of ball (.096). This is in contrast with Pulling et al. (2013) who noted more defenders set up at the “far post only” (47.3%) in the EPL. Furthermore, NIFL Premiership teams who did set up by positioning players on the “far post only” were the least efficient at preventing goals being scored (4.6%), whilst the most efficient defensive set-up in the NIFL Premiership was defending both posts (2.4%). These findings are in direct contrast with Power et al. (2018) who found EPL teams with players on both posts concede more goals, whilst having a player on the “back post only” concedes the least. In addition, more direct, inswingingers towards area GA2 are being defended with differing efficiency to other leagues and tournaments. These conflicting results highlight the importance of bespoke research into each league, taking account of context and performance influencing factors. To investigate these contextual differences further, one must examine the individual teams' offensive and defensive efficiencies.

3.8. Interaction context

Most corner kicks were defended with a superiority of 2+ (80.7%), with only 20 (1%) being taken when the interaction context between defence and attack was equal. In line with the 3.1% found by Maneiro et al. (2021). There was no significant association between interaction context and outcome, however interaction context was significantly associated with short options, path of the ball, delivery and defending the posts. The link between characteristics due to the fact a player providing a static or dynamic short option generates a defensive team reaction.

3.9. Corner kick success

Of most interest to coaches and teams is how to score goals and how to prevent goals. Table 5 displays the influence of corner kick characteristic variables on success, defined as a goal, or attempt on goal.

Table 5. Corner kick success analysed by goals and attempts.

Variable	Goal: Yes			Goal: No			X^2		Sig.		Attempt on goal: Yes			Attempt on goal: No			X^2		Sig.
Attacking Team Top6 Bottom6 Defending Team	38. 32.	(3.6%) (3.4%)	1017 901		(96.4%) (96.6%)	.043		.835		297 237		(28.2%) (25.4%)	758 696		(71.8%) (74.6%)	1.906		.167
Top6 Bottom6	28. 42.	(3.4%) (3.6%)	801 1117		(96.6%) (96.4%)	.086		.769		202 332		(24.4%) (28.6%)	627 827		(75.6%) (71.4%)	4.504		.034*
Venue Home Away	45. 25.	(4.2%) (2.7%)	1033 885		(95.8%) (97.3%)	2.958		.085		317 217		(29.4%) (23.8%)	761 693		(70.6%) (76.2%)	7.765		.005**
Pitch Type Grass 4 G	53. 17.	(3.5%) (3.6%)	1465 453		(96.5%) (96.4%)	.017		.897		410 124		(27.0%) (26.4%)	1108 346		(73.0%) (73.6%)	.072		.789
Time 0–15 15–30 30–45+ 45–60 60–75 75–90+	7. 8. 12. 11. 14. 18.	(2.2%) (2.7%) (3.8%) (3.5%) (4.3%) (4.2%)	307 283 306 305 309 408		(97.8%) (97.3%) (96.2%) (96.5%) (95.7%) (95.8%)	3.365		.644		81 76 80 80 95 122		(25.8%) (26.1%) (25.2%) (25.3%) (29.4%) (28.6%)	233 215 238 236 228 304		(74.2%) (73.9%) (74.8%) (74.7%) (70.6%) (71.4%)	2.872		.720
Match Status Win Draw Lose	20. 29. 21.	(3.7%) (3.2%) (4.0%)	523 891 504		(96.3%) (96.8%) (96.0%)	.765		.682		163 238 133		(30.0%) (25.9%) (25.3%)	380 682 392		(70.0%) (74.1%) (74.7%)	3.839		.147
Position Left Right	36. 34.	(3.7%) (3.3%)	925 993		(96.3%) (96.7%)	.277		.599		254 280		(26.4%) (27.3%)	707 747		(73.6%) (72.7%)	.175		.675
Laterality Natural Switched	13. 57.	(3.2%) (3.6%)	395 1523		(96.8%) (96.4%)	.169		.681		124 410		(30.4%) (25.9%)	284 1170		(69.6%) (74.1%)	3.258		.071
Short option Static Dynamic No	11. 5. 54.	(4.3%) (1.9%) (3.7%)	246 256 1416		(95.7%) (98.1%) (96.3%)	2.516		.284		81 77 376		(31.5%) (29.5%) (25.6%)	176 184 1094		(68.5%) (70.5%) (74.4%)	4.994		.082
Delivery Direct Short	68. 2.	(3.8%) (1.1%)	1740 178		(96.2%) (98.9%)	3.384		.066		481 53		(26.6%) (29.4%)	1327 127		(73.4%) (70.6%)	.672		.412
Path of ball Inswinging Outswinging Other	56. 12. 2.	(3.8%) (3.0%) (2.2%)	1437 391 90		(96.2%) (97.0%) (97.8%)	1.074		.585		377 120 37		(25.3%) (29.8%) (40.2%)	1116 283 55		(74.7%) (70.2%) (59.8%)	12.067		.002**
Interaction context EQ INF1 INF2	0. 12. 58.	(0.0%) (3.3%) (3.6%)	20 351 1547		(100%) (96.7%) (96.4%)	.820		.664		3 109 422		(15.0%) (30.0%) (26.3%)	17 254 1183		(85.0%) (70.0%) (73.7%)	3.549		.170
Posts Near Far Both None	23. 22. 7. 18.	(3.2%) (4.6%) (2.4%) (3.6%)	687 460 290 481		(96.8%) (95.4%) (97.6%) (96.4%)	2.906		.406		185 127 74 148		(26.1%) (26.3%) (24.9%) (29.7%)	525 355 223 351		(73.9%) (76.7%) (75.1%) (70.3%)	2.859		.414
Zone of pass GA1 GA2 GA3 CA1 CA2 CA3 Short Long Edge	10. 30. 7. 4. 10. 5. 2. 2. 0.	(2.7%) (5.4%) (4.6%) (4.4%) (2.6%) (3.5%) (1.1%) (3.1%) (0.0%)	361 524 144 87 379 139 186 62 36		(97.3%) (94.6%) (95.4%) (95.6%) (97.4%) (96.5%) (98.9%) (96.9%) (100%)	13.072		.109		61 134 54 26 146 37 56 9 11		(16.4%) (24.2%) (35.8%) (28.6%) (37.5%) (25.7%) (29.8%) (14.1%) (30.6%)	310 420 97 65 243 107 132 55 25		(83.6%) (75.8%) (64.2%) (71.4%) (62.5%) (74.3%) (70.2%) (85.9%) (69.4%)	57.792		<.001**
Action area GA1 GA2 GA3 CA1 CA2 CA3 Short Long Edge	3. 41. 7. 2. 10. 2. 1. 1. 3.	(1.6%) (9.7%) (4.9%) (3.2%) (3.2%) (1.9%) (0.6%) (0.6%) (0.7%)	190 382 137 60 298 104 158 164 425		(98.4%) (90.3%) (95.1%) (96.8%) (96.8%) (98.1%) (99.4%) (99.4%) (99.3%)	69.365		<.001**		30 110 49 26 150 38 21 14 96		(15.5%) (26.0%) (34.0%) (41.9%) (48.7%) (35.8%) (13.2%) (8.5%) (22.4%)	163 313 95 36 158 68 138 151 332		(84.5%) (74.0%) (66.0%) (58.1%) (51.3%) (64.2%) (86.8%) (91.5%) (77.6%)	150.542		<.001**

Attempts on goal were found to be significantly associated with the quality of defending team (X²1 = 4.504, p = 0.034, V = 0.048), venue (X²1 = 7.765, p = 0.005, V = 0.062), path of ball (X²2 = 12.067, p = 0.002, V = 0.078), zone of pass (X²8 = 57.792, p < 0.001, V = 0.171) and action area (X²8 = 150.542, p < 0.001, V = 0.275). This suggests more variance in the defending team’s effectiveness in preventing shots than the attacking team, with attempts on goal more likely to occur when corner kicks were defended by a team in the bottom 6 (28.6% vs 24.4% for the top 6). For coaches, this intimates that there are teams who have managed to improve their effectiveness at defending corner kicks and are therefore gaining a competitive advantage. Familiar surroundings via home advantage also appear to be a factor, with home teams showing a better shot conversion (29.4% vs 23.8% for the away team).

Attempts on goal were mostly generated (40.2%) from short or driven delivery defined as “other” compared to outswinging (29.8%) and inswinging (25.3%). However, goals were less likely from short or driven delivery (2.2% conversion rate), rather inswinging corners resulted in the highest goal conversion rate (3.8%) followed by outswinging corners (3% conversation rate). This could be due to short, driven or outswinging corner kicks being delivered further away from goal, making it easier to shoot from, but harder to score.

Analysing the influence of corner characteristics variables on scoring a goal in Table 5 shows that goals were only significantly associated with the action area (X²8 = 69.365, p < 0.001, V = 0.187), with goals more likely to occur in GA2 (58.6% of total goals from corners). Short corners had a lower conversion rate to goals (1.1%) than direct corners (3.8%).

3.10. Delivery area and action area conversion rates

The area of the pitch a corner was directed to, as well as the area of final action have been shown to be important for shot creation and goal scoring. Figure 2 shows the volume of goals and conversion rate from shots from each area the corner kick is delivered to, whilst Figure 3 shows the same for the final action area. These heat mapped representations could aid coaches as to where success may lie from corner kicks in the NIFL Premiership.

Figure 2. Goal conversion rates (%) with absolute values of goals (n = 70) in the corner kick area of delivery.

Figure 3. Goal conversion rates (%) with absolute values of goals (n = 70) in the corner kick’s final action area.

The deliveries into “critical area” CA2, did not have the greatest frequency of first contacts which contradicts previous research (Pulling, 2015; Taylor et al., 2005). As discussed earlier, inswinging corner kicks were much more prevalent than previous studies. Therefore, as the “path of ball” has significant correlation with “zone of pass”, the affect this has is that more first contacts are taken nearer the goal (GA2) rather than the “critical area” in the NIFL Premiership. The most goals were scored from deliveries into GA2 (n = 30) which also had the highest conversion rate (5.43%), with attempts on goal increased with deliveries into CA2, which support previous findings (Beare & Stone, 2019).

The next most goals came from GA1 and CA2 (both n = 10), however their conversion rates (2.70% and 2.57% respectively) were lower than four other areas (GA3, CA1, CA3, and long). With over half (51.6%) of the teams defending their near posts, GA1 is an area that is usually well defended which could explain the low conversion rates. The same applies to CA2, with this known to be a prominent area of delivery. Corner kicks in this area resulted in a high number of goals, however there were more efficient goals scoring areas.

The most goals were scored in GA2 (41 of 70 goals scored; 58.57%), and GA2 also had the best conversion rate (9.69%). The higher number of goals and stronger conversion rate suggest that goals in this area are not only from first contacts, but from second contacts or second phases. The takeaway appearing to be that there is no one-size-fits-all method of scoring a goal. The next highest conversion rate was from area GA3 (4.86%) where 7 goals were scored. The far post area was not protected as much as the near post, with 39.1% of corner kicks being defended by a player in this area. Creating an opportunity for competitive advantage. There were 10 goals scored from CA2, however the conversion rate was lower from this area (3.25%) and similar to CA1 (3.23%) where 2 goals were scored. Examining corner kick action areas, edge was the most frequent (21.5%) followed by GA2 (21.3%) and CA2 (15.5%). This suggests that whilst attacking and defending in central areas of the penalty area is important, so too is making sure there is cover on the edge of the box to prevent/start a counterattack or to recycle/prevent the ball being returned into a more dangerous area.

3.11. Team efficiency

Attacking efficiency for goals to corner kicks for each team varied from 6.03% to 1.32%, whilst defensive efficiency varied from 0.83% to 6.7%, recognition that corner kick effectiveness varies between individual teams within a competition, requiring further breakdown than is available from previous studies (Beare & Stone, 2019; Casal et al., 2015; Prieto-Lage et al., 2021; Pulling & Newton, 2017),

With respect to offensive efficiency, Portadown were the most efficient team (6.03% conversion rate) scoring 7 goals from their 116 corner kicks. Portadown were also the most efficient at generating shots from their corner kicks (38.79%). Whilst Glenavon were one of the least efficient in terms of shots to corners (21.32%), they were one of the most efficient in turning the shots they did have into goals (16.67%). Dungannon were the least effective scoring only 2 goals at a conversion rate of 1.32%.

Defensively, Larne were the most efficient team in preventing goals being scored from corners (0.83%). While Dungannon were the least effective conceding the highest number of goals (12) at the highest rate (6.70%). Glentoran were the most efficient at preventing shots from corners (18.10%); however, they had the highest goals to shots ratio (26.32%) which implies that whilst they didn’t give away many shots, those that they did were more likely to convert into goals for the opposition.

Dungannon finished bottom of the table in the 2020/21 NIFL Premiership regular season, 4 points behind Carrick with −5 worse goal difference (−54 vs −49). Dungannon’s net goal difference from corner kicks was −10 vs Carrick’s −3. If Dungannon had been able to be more effective from attacking and defending corner kicks, they may have had a better chance at avoiding finishing bottom.

At the opposite end of the table, leaders Linfield’s net goal difference from corner kicks was + 4, whilst the team in third, Glentoran had a net goal difference of −2. Had Glentoran (one of the full-time teams in the league) been more effective at attacking and defending corner kicks, they may have closed the gap on the leaders. Linfield delivered the highest percentage of inswinging corner kicks (93.8%) using left and right-footed players technically capable of delivering quality balls from either corner, which were attacked by naturally tall, aggressive centre backs who could challenge for the ball and have good goal scoring records. On the other hand, Glentoran delivered the lowest proportion of inswinging corner kicks (53.9%), the highest outswinging (38.8%) and second most short corners (7.2%). The 3 goals they did score were all from inswinging corner kicks. As one of the full-time teams in the league, they ranked 10^th in both offensive and defensive efficiency.

3.12. Limitations

The Kappa statistic for inter-observer reliability highlighted that whilst intra-observer reliability showed near perfect agreement (K_total = 0.91), inter-observer was found to only rank as substantial (K_total = 0.73), with some variables showing only moderate agreement (K_total <0.60). One explanation of this could be that whilst searching for objective variables to analyse corner kicks, some of the defined characteristics are open to subjective interpretation. The five variables that were in least agreement were the action area (0.48), zone of pass (0.54), posts (0.64), path of ball (0.71) and outcome (0.75). These could be open to subjective interpretation, perpetuated by the lower viewing angle or limited training of the inter-observer. Limitation of time available with the inter-observer and a lack of clarity of definition added to this low level of reliability result in these variables.

4. Conclusion

The aim of the present study was to described how corner kicks were taken across the 2020/21 (NIFL) Premiership season – a European league outside of the Big Five – and to assess the effectiveness of offensive and defensive corner kick strategies. Providing actionable recommendations for coaches that can be used to increase offensive and defensive efficiencies at corner kicks.

The present study has demonstrated that corner kicks in the NIFL occur frequently and are relatively efficient at producing goals, underlying their importance in this context. Furthermore, weaker teams were more likely to concede corner kicks, and be less efficient in preventing attempts at goal, and should be an area to address for coaches of bottom 6 teams in the NIFL.

Home sides delivered more corner kicks and had a more efficient conversion rate, suggesting that if not already doing so, teams should practice corner kick strategies on their home pitch to increase familiarity with the dimensions and surface. Teams utilised short corners more on 4 G pitches, however there was no statistical significance in pitch surface and outcome. As there will be an increase in teams using 4 G as their home pitch surface in the coming seasons, this makes it an area for future research. With reference to match time and corner kick effectiveness, attacking efficiency is increased later in a game, suggesting that coaches should prepare their players tactically for these moments.

When analysing corner kick success and delivery type, the current study identified a trend whereby inswinging corner kicks are the most frequent and efficient in terms of scoring goals, advising coaches to better prepare defensively for these types of deliveries. Results demonstrated an increase in the volume of inswinging corner kicks as also being significant when discussing delivery area. The most frequent and efficient was GA2. Inswinging corner kicks resulted in the delivery area being nearer to the goal than the previously discussed “critical area” (CA2). The implications for coaches are two-fold. Firstly, for defensive teams to increase players in this area to prevent conceding, and secondly for offensive teams to create strategies to be even more effective in these areas. The edge was the most frequent action area, highlighting the importance of cover in this area to prevent/start a counterattack or to recycle/prevent the ball being returned into a more dangerous area.

The results demonstrated variations from previous studies (Power et al., 2018) particularly in relation to defensive cover on posts and the impact on goals scored. These conflicting results highlight the importance of bespoke research into each league, taking account of context and performance influencing factors.

At a team level offensive and defensive efficiency varied greatly and was not directly related to league position. This is an important finding in the understanding of corner kick strategies. Instead of focusing on a league or competition, researchers should focus on the teams within that league or competition individually. The result of which would give a better understanding of teams’ set-piece style, and their contextual factors for it. This, in turn, would be more translatable for coaches to act upon with the aim of improving offensive and defensive performance at corner kicks, based on the context of their own team’s characteristics, of great importance for smaller leagues with a greater repetition of league games.

Ethics

The main components of this study have been reviewed via the relevant Research Ethics Committee to ensure that all elements of the research study were conducted appropriately adhering to the highest ethical standards.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The author(s) reported there is no funding associated with the work featured in this article.