Finishing Patterns and Goalkeeper Interventions: A Notational Study of Shot Effectiveness in Europe’s Top Football Leagues

Abstract

Football is a low-scoring sport where a single goal can determine a team’s success. Understanding shot effectiveness and goalkeeper performance is crucial for optimizing match success. This study aimed to evaluate the effectiveness of shots and goalkeeper interventions by identifying the most favorable areas on the field and within the goal. An observational notational analysis was conducted on 15,266 on-target shots from five major European leagues (Premier League, LaLiga, Bundesliga, Serie A, Ligue 1) during the 2022/2023 season. Data were extracted from FotMob and analyzed in SPSS using Pearson’s chi-square test (χ²) and adjusted residuals (AR) to determine significant patterns. Field and goal zones were divided based on previous studies, with the penalty area receiving further subdivisions due to its relevance to the analysis. The results indicated that match context, target areas within the goal, field zones, and previously identified high-effectiveness areas significantly influenced shot success (χ² < 0.001). Similarly, a significant association was found between the shooting foot and the side of attack (χ² < 0.001), while the body part used did not significantly affect the outcome (χ² = 0.077). Understanding these patterns helps coaches and players optimize team performance. Future studies should analyze additional seasons to confirm these results.

1. Introduction

Football is classified as an invasion sport [1], inherently characterized by low-scoring outcomes [2,3]. The game consists of two teams of 11 players engaging in direct, indirect, and simultaneous competition, with the dual aim of scoring and preventing goals [4,5]. The most successful teams excel in both aspects by recovering possession further from their own goal, completing more passes per sequence, and consistently entering the final third of the field. They also outperform lower-ranked teams by producing more crosses, executing more through balls, and sustaining longer possession sequences [4].

Given the low-scoring nature of football, shot production and quality serve as key performance indicators for assessing both team and player effectiveness [2]. To enhance shot evaluation, the expected goals metric was developed, providing an estimation of a shot’s likelihood of resulting in a goal [1,6]. This metric estimates scoring probability based on shot location, highlighting high-probability zones. However, its effectiveness is limited by the inherent randomness of football events [1] and by its poor representation of set pieces—often influenced by refereeing and subjective interpretations [1]. Even studies using longitudinal OPTA data (2008/09–2020/21) [4] or focused on specific seasons, such as 2017/18 [6], face these constraints. Still, teams with higher expected goals values win 73.3% of matches not ending in a draw [2]. Teams aim to impose their style of play on the opponent [7], which is defined as the set of coordinated player behaviors intended to achieve offensive and defensive objectives [8]. Possession-based teams tend to win more often [9], likely due to better match control and shot quality. Despite depending on context (e.g., score, venue, and rival), playing style shapes shot patterns and should inform models of shooting and goalkeeper effectiveness [9,10].

While offensive production is essential, defensive responses are equally critical to match outcomes. Thus, the goalkeeper plays a decisive role in preventing goals and achieving clean sheets [5,11,12], being the only player allowed to use their hands within their own penalty area. Their performance is pivotal, often influencing match outcomes both individually and collectively [5,13,14] Goalkeeping is inherently complex [15], influenced by dynamic player interactions and the challenge of defending a static goal measuring 7.32 m in width and 2.44 m in height.

The effectiveness of a goalkeeper’s interventions largely depends on their positioning along the shot bisector and their depth within the goal area [16,17]. The shot bisector is defined as the straight line that divides the shooting angle into two equal parts, with the ball acting as the vertex in relation to the goalposts. A goalkeeper’s alignment with the available shooting angles is crucial to the success of their interventions [17]. Optimal positioning typically requires aligning with the center of the bisector, thereby minimizing the striker’s available shooting angle and guiding the shot trajectory closer to the goalkeeper. As a result, areas near the goalposts (i.e., where deviation from the bisector is greatest) tend to favor attackers. However, an analysis of the 2008/2009 Premier League season revealed that most goals were conceded in the lower sections of the goal [18], highlighting that penalty situations are among the least favorable scenarios for goalkeeper intervention [6].

Beyond individual positioning, goalkeeper effectiveness is also influenced by contextual variables arising from team interactions. One such variable is the level of defensive pressure. Shot effectiveness decreases when both the defensive line and the goalkeeper apply direct and robust opposition [17]. Another critical variable is player fatigue [18]. Studies indicate that during the 2008/2009 Premier League season, the probability of scoring slightly increases as the match progresses [6], with a higher success rate observed in the second half of the game [18]. Fatigue, direct opposition, and the actions of off-the-ball players should be taken into account when constructing expected goals models. However, some studies exclude the movement of off-the-ball players or the role of the goalkeeper [1], although others do account for elements such as their alignment with the shot bisector and depth positioning [2].

Shot location on the field is another decisive contextual variable. Shots taken from closer proximity to the goal have a significantly higher likelihood of resulting in goals [6,18], likely due to the greater difficulty of accurate shooting from longer distances and the additional reaction time available to the goalkeeper. Furthermore, centrally positioned shots (ranging from 60 to 120 degrees relative to the goalkeeper’s perspective) are more effective than those taken from narrower angles, such as 40–60 degrees or 120–140 degrees [6,18]. This pattern aligns with previously identified zones of high and moderate shooting effectiveness [17], reinforcing the spatial component of shot quality. The observed spatial trends highlight the need for integrated analyses that jointly consider shooting outcomes and goalkeeper intervention effectiveness. Furthermore, analysis of 178 matches from the 2019/20 Spanish league season revealed that 72.7% of goals were scored with the first touch, 11.5% with two touches, and 15.8% with more than two touches—highly relevant figures despite the fact that the full season was not analyzed [19]. Expected goals models should also take into account shot angle and distance [6], shot direction, origin zone, field laterality, the body part used to strike the ball, and the zones where goalkeeper interventions tend to be most effective.

The present study addresses a current gap in quantitative analyses by simultaneously assessing shot effectiveness and goalkeeper performance in high-level competitions. The absence of such research limits coaches and goalkeeper trainers to design tactical strategies and training exercises based on real-game patterns. Thus, the primary aim of this study was to evaluate the effectiveness of both attacking shots and goalkeepers’ interventions. Additionally, the secondary aim was to identify the field and goal areas that offer the greatest defensive advantage for goalkeepers and the highest scoring probability for attackers. By addressing these gaps, this study seeks to provide practical insights for optimizing tactical decision making and designing specialized training programs in professional football.

2. Methodology

2.1. Desing

A quantitative, observational, cross-sectional cohort design with a correlational approach was used in the present study. Consistent with previous research [20,21,22], this involved a secondary analysis of data from a single season, obtained from the statistical platform FotMob. An observational methodology was selected due to its effectiveness and robustness in conducting scientific analyses within football research [23].

2.2. Sample

To determine the sample size, G*Power was used, considering a large effect (w = 0.5) and a minimum of 785 observations, ensuring sufficient statistical power to detect meaningful differences. The study sample comprised data from the top-tier European football leagues: the Premier League, LaLiga, Bundesliga, Serie A, and Ligue 1, representing the highest levels of competition in England, Spain, Germany, Italy, and France, respectively [24,25,26,27]. These leagues were selected due to their global recognition and competitive intensity, ensuring a robust and representative dataset. In total, 15,266 shots on target were analyzed (See

Table 1. Distribution of teams, matches, goals, and goalkeeper saves across the top-tier European leagues analyzed.

Season	Country	League	Teams	League Matches	Goals	Saves
2022/2023	England	Premier League	20	380	1196	2452
	Spain	LaLiga	20	380	930	2148
	Germany	Bundesliga	17	272	905	1830
	Italy	Serie A	20	380	944	2103
	France	Ligue 1	18	306	811	1947
Total			95	1718	4786	10,480

). It is important to note that the FotMob platform exclusively records shots on target (i.e., those directed between the goalposts), meaning off-target attempts were excluded from the study.

2.3. Instrument

To facilitate data collection and analysis, an ad hoc instrument was developed to record shot events and their corresponding field zones. First, a categorization system was applied to analyze the shots, grounded in both empirical evidence and established theoretical frameworks from prior studies [28,29,30]. Shots were classified as either goals or saves, and several variables were recorded, including the striking surface used (i.e., right foot, left foot, header, and others), the match context (i.e., regular play, individual action, and counterattack), set-piece actions (penalty, corner kick, free kick, and indirect free kicks during the final moments of the game), and the goal area. The goal was divided into twelve zones (Figure 1): four horizontals (i.e., two on the left and two on the right relative to the goalkeeper) and three verticals (i.e., high, middle, and low). Second, a separate categorization system was used to analyze shot locations across different field zones, based on classifications from previous studies [18,31], with additional subdivisions applied within the penalty area due to its high scoring effectiveness (Figure 2). The field was divided into multiple zones, with greater granularity in the attacking third and particularly within the penalty area, including the six-yard box and goal zone. Each zone was labeled using an alphanumeric grid system to ensure consistent coding during the notational analysis.

2.4. Procedure

First, the validity of the FotMob website (https://www.fotmob.com) was established by reviewing previously published studies that had used data extracted from this platform for research purposes [20,21,22]. Data were manually extracted from each goalkeeper’s match log available on FotMob, reviewing every on-target shot individually across the season (Supplementary Materials).

A single trained analyst, following a familiarization period, used the ad hoc instrument to code each shot, including contextual variables and spatial zones of the field and goal provided by FotMob. To ensure consistent zone assignment, a shot was coded into a zone if the center of its marker on the FotMob graphic fell within that zone. As the pitch and goal were divided using 90° sector angles, this criterion ensured that more than 50% of the shot marker was located within a single zone. To enhance spatial accuracy, schematic diagrams of the pitch and goal were edited using graphic software (Paint v22H2, Microsoft Corporation, Redmond, WA, USA) to draw reference lines and delimit each zone clearly. Notably, the study categorized outcomes as either goals or goalkeeper saves, without assessing shot effectiveness per se.

2.5. Statistical Analysis

Once data extraction was complete, a comprehensive three-phase statistical analysis was performed using SPSS+ statistical software (v. 20.0, IBM Corp., Armonk, NY, USA): (a) A descriptive analysis was conducted, calculating the frequencies for each category of the variables studied. This step is essential for summarizing categorical data, enabling the identification of dominant patterns, trends, or potential irregularities prior to conducting inferential analyses [32]. (b) To assess the probability that certain categories occur together and to examine relationships between categories showing significant differences, a Pearson’s chi-square test (χ²) was performed [33,34]. This test evaluates whether the observed distribution of frequencies differs significantly from the expected distribution under the assumption of independence. The significance threshold was set at p < 0.05 [33]. (c) Finally, the strength and direction of associations between variables and their respective categories were assessed using adjusted residuals (AR) from the contingency tables. These standardized residuals indicate how much each cell in the table deviates from the expected frequency. The residuals provided insight into the pattern between categories: an excitatory pattern was identified when the AR value exceeded 1.96 and an inhibitory pattern when the AR value was below −1.96 [35]. This methodical approach enabled a nuanced understanding of the relationships and associations within the dataset.

3. Results

A total of 15,266 finishing scenarios were analyzed, comprising 4786 goals and 10,480 saves from 1718 matches (Table 1). The match context significantly influenced the outcome, with significant differences observed (χ² < 0.001) (

Table 2. Descriptive analysis of the goals, saves, and shots on goal according to the match context and their adjusted residuals (AR).

Match Context	Goal	Goal/ Match	AR	Saves	Saves/Match	AR	Total Shots on Goal	Total Shots on Goal/Match
Regular play	3096	1.80	−4.8	7662	4.46	3.2	10758	6.26
Individual play	7	0.00	−1.0	26	0.02	0.7	33	0.02
Counterattack	345	0.20	1.7	657	0.38	−1.2	1002	0.58
Penalty	420	0.24	21.2	77	0.04	−14.3	497	0.29
Corner kick	595	0.35	1.9	1164	0.68	−1.3	1759	1.02
Indirect free kick	263	0.15	0.2	564	0.33	−0.2	827	0.48
Free kick	60	0.03	−5.6	330	0.19	3.8	390	0.23

Adjusted residuals were classified as excitatory trend (AR > 1.96) and inhibitory trend (AR < −1.96).

). While regular plays accounted for the highest number of scenarios, they were not the most effective in terms of goal scoring. Both regular plays and free kicks showed inhibitory patterns for goals and excitatory patterns for saves. In contrast, penalties, corner kicks, and counterattacks showed significant trends in effectiveness. No significant effects were observed for individual plays and indirect free-kick actions.

Figure 1 shows the descriptive analysis of goals and saves across different areas of the goal, revealing a significant relationship between shot direction and success (χ² < 0.001). Vertically, the areas near the posts (i.e., X1, Y1, Z1, X4, Y4, and Z4) showed excitatory patterns for goals and inhibitory patterns for saves, whereas central areas (i.e., X2, X3, Y2, Y3, Z2, and Z3) showed the opposite. Horizontally, an excitatory pattern for goals (AR = 3.4) and an inhibitory pattern for saves (AR = −2.3) were observed in the lower section of the goal (i.e., X1, X2, X3, and X4), whereas the opposite (AR = −4.0 and 2.7, respectively) was observed in the central section (i.e., Y1, Y2, Y3, and Y4). No significant patterns were found in the upper section of the goal.

Figure 2 illustrates the goals and saves across field zones, highlighting a clear relationship between shot location and action success (χ² < 0.001). Excitatory patterns for goals were observed for shots into the six-yard box and its extension into the penalty area (except for boxes DL4, DC5, and DR3). In contrast, excitatory patterns for saves were identified in the lateral zones of the penalty area (except for boxes AL2 and BR2) as well as in at the front of the penalty area. The remaining field zones did not show significant trends.

Figure 3 shows a significant relationship between goal zones from the penalty spot and goal success (χ² = 0.004). Most shots were directed toward the lower corners (X1 and X4), followed by mid-height zones near the post (Y1 and Y4). Although some zones showed different trends, overall, only an excitatory pattern for goals was observed across height levels (i.e., Z1, Z2, Z3, and Z4; χ² = 0.011 and AR = 3.0) but not across columns (χ² = 0.944).

Figure 4 illustrates a significant relationship between goal zones from free-kick shots and goal success (χ² = 0.003), but no such relationships were observed between shot effectiveness and free-kick attempts based on field areas (χ² = 0.795). An excitatory pattern for goals was exclusively observed from EC3, where shots were more likely to result in goals than saves (AR = 1.9). Most shots were directed toward the upper sections of the goal, with excitatory patterns for goals in the top corners of the goal and excitatory patterns for saves in the inner columns (left: AR = 3.0; right: AR = 2.7). No significant relationship between shot height and goal success was found (χ² = 0.55), but a strong correlation with columns was observed (χ² < 0.001), with excitatory patterns for goals identified in zones near the left post (AR = 3.2).

Table 3. Descriptive analysis of goals and saves according to the striking surface used and their adjusted residuals (AR).

Shots on Goal	Goal	AR	Saves	AR	Total
Head	838	1.8	1673	−1.2	2511
Right foot	2426	−0.2	5349	0.2	7775
Left foot	1501	−1.1	3419	0.7	4920
Other	21	0.5	39	−0.3	60

Adjusted residuals were classified as excitatory trend (AR > 1.96) and inhibitory trend (AR < −1.96).

shows no significant excitatory or inhibitory patterns between the body parts used to strike the ball and goal success (χ² = 0.077). However, a notable trend emerged in goals scored with headers (AR = 1.8), with significant relationships observed between goal area and field zones with header success (χ² < 0.001). Related to the goal zones, excitatory patterns for goals were observed near the left and right posts (AR = 9.2 and 9.1, respectively), while excitatory patterns for saves were found in the inner right and inner left columns (AR = 9.3 and 8.3, respectively). Related to the field zones, excitatory patterns for goals were observed within the six-yard box (AR from 2.0 to 7.4) and inhibitory patterns for goals outside this zone and into the penalty area (AR from −0.3 to −5.5).

Table 4. Descriptive analysis of goals and saves according to the field zones, the striking leg, and the goal zone and their adjusted residuals (AR).

			Field Zones									Field Zones
Striking Leg	Goal Zone		Right	AR	Central	AR	Left	AR	Striking Leg	Goal Zones		Right	AR	Central	AR	Left	AR
Left leg		Goal	230	−3.1	84	2.1	200	−1.1	Right leg		Goal	257	−4.4	130	−2.7	329	3.3
(N = 4920)		Saves	487	2.5	157	−1.7	239	0.9	(N = 7775)		Saves	543	3.7	259	2.3	321	−2.8
		Total	717		241		439				Total	800		389		650
		Goal	120	0.7	38	−0.7	58	−1.2			Goal	129	−1.9	60	−2.6	158	1.6
		Saves	498	−0.3	196	0.3	315	0.6			Saves	602	1	339	1.3	509	−0.8
		Total	618		234		373				Total	731		399		667
		Goal	108	1.8	18	−2.5	62	−1.7			Goal	101	−1.7	58	−0.3	166	−0.2
		Saves	349	−0.9	144	1.2	328	0.9			Saves	510	0.9	250	0.2	694	0.1
		Total	457		162		390				Total	611		308		860
		Goal	202	2.6	81	−1.3	162	−3.3			Goal	290	1.6	153	−0.6	312	−3.4
		Saves	201	−2.2	143	1.1	339	2.8			Saves	374	−1.3	251	0.5	642	2.8
		Total	403		224		501				Total	664		404		954
		Goal	107	0.2	39	−1.1	87	−0.3			Goal	121	−2	82	−0.7	148	0.2
		Saves	203	−0.2	99	0.8	180	0.2			Saves	310	1.4	181	0.5	283	−0.2
		Total	310		138		267				Total	431		263		431
		Goal	188	−1.1	64	−1.1	157	−0.5			Goal	253	−1.6	126	−1.2	269	−1.0
		Saves	593	0.7	218	0.7	468	0.3			Saves	808	1.0	407	0.7	817	0.6
		Total	781		282		625				Total	1061		533		1086
		Goal	365	0.2	118	−2.2	238	−1.7			Goal	403	−2.1	193	−3	548	0
		Saves	739	−0.1	323	1.5	573	1.2			Saves	911	1.5	511	2.1	1066	0
		Total	1104		441		811				Total	1314		704		1614

Adjusted residuals were classified as excitatory trend (AR > 1.96) and inhibitory trend (AR < −1.96).

illustrates a significant relationship between field zones (grouped into left, right, and central lanes) and goal success (χ² < 0.001) according to the striking leg and the goal zones. In the vertical analysis of the goal, shots from the left lane by left-footed shots targeting the near post exhibited inhibitory patterns for goals and excitatory patterns for saves. Conversely, aiming at the far post showed the opposite trend. Despite these patterns, near-post shots were more frequent. Similar trends were observed for right-footed shots from the right flank, reinforcing the near post as a more effectively defended area for goalkeepers. Left-footed cross shots from the right flank targeting the near post generally exhibited inhibitory patterns for goals and excitatory patterns for saves. This trend mirrors that of right-footed shots from the left flank. Conversely, shots aimed at the far post showed a positive trend for goal success despite a higher frequency of attempts directed at the near post. For shots from the central lane, left-footed shots aimed toward the right post of the goalkeeper show excitatory patterns for goals. In the horizontal analysis of the goal, no significant trends were observed in the left and right lanes. However, in the central lane, low attempts tended to be less effective, exhibiting inhibitory patterns for goals and excitatory patterns for saves, regardless of the foot used.

4. Discussion

This study presents insights into the effectiveness of both goalkeepers’ and outfield players’ actions in football, identifying the most favorable field and goal zones for both defending and finishing attacks. By analyzing various phases of the game (i.e., match context) and player behavior within these phases (i.e., field zones, striking leg, and goal zones), the study highlights key patterns in the dynamics between attacking and defending actions, contributing to our understanding of strategic decision making during matches.

Football can be divided into five phases or “moments of play”, each of which contributes to a team’s overall playing style [36]. Two of these moments occur when a team is in possession: the “established attacking phase” corresponds to the opponent’s “established defensive phase” [7]. In the present study, these are referred to as “regular play”, and the data reveal that this phase is associated with inhibitory patterns for goals and excitatory patterns for goalkeeper saves (Table 2). An average of 1.8 goals and 6.29 shots on target per match was observed, indicating that goalkeepers made approximately 4.46 saves per game (Table 1). These values, collected from the five major European leagues during the 2023/2024 season, clearly exceed the 0.81 goals per match reported between the 2009/2010 and 2018/2019 seasons in one of the few studies to analyze all five top European leagues collectively [24] as well as the 1.28 ± 0.42 recorded in LaLiga during the 2017/2018 and 2018/2019 seasons [37]. These findings suggest an evolution of the game toward higher offensive volume and underscore the increasing tactical workload and significance of the goalkeeper in modern football.

In addition to regular play, two other key moments for team success [9] are the “defensive” and “offensive” transitions [7]. These moments are considered critical because they occur at maximum speed, with both teams competing for the ball possession [38]. The present study analyzed these moments within the context of “counterattacks”, revealing excitatory trends for goals (Table 2). The average of 0.2 goals per match from counterattacks across the five major European leagues surpasses those reported in previous research [24], especially in the Spanish top division (i.e., 0.099 ± 0.082) and Serie A (i.e., 0.09 ± 0.074). These results underscore the growing importance of transitions as decisive moments in the game, reflecting their strong association with goal-scoring opportunities.

“Set-piece” actions (i.e., the last moment of the game) [7], which contribute to 30–40% of goals [39,40], are also essential in generating goal-scoring chances [41]. Our results showed an average of 1.02 corner kicks per match, resulting in 0.35 goals per match across the five major European leagues (Table 2). These numbers exceed historical averages (i.e., ranging from 0.14 to 0.26 goals per match in top divisions of countries like Spain, England, Germany, Italy, and France during the 2008/2009 to 2018/2019 seasons) [18,24,37].

Free kicks showed (Table 2) much lower effectiveness than corner kicks (0.03 vs. 0.35 goals per match), and the number of saves from free kicks was 5–6 times higher than the number of goals (0.19 vs. 0.03 per match). Free-kick effectiveness is in line with the results of previous studies and ranged from 0.036 to 0.043 in the top divisions of countries like Spain, England, Germany, Italy, and France during seasons 2009/2010 and 2018/2019 [9,24]. Most free kicks were directed toward the upper sections of the goal, with limited success, as excitatory patterns were observed only in the top corners (Figure 4). EC3 was the only field zone to exhibit an excitatory trend in goal scoring.

On the other hand, an average of 0.15 goals per match was found from indirect free-kick actions, with 0.48 shots on target and 0.33 saves per match. These results are lower than 0.27 ± 0.11 goals per match in the Spanish top division 2018/2019 session [37], but higher than the averages reported across the top five European leagues between the 2009/2010 and 2018/2019 seasons, which ranged from 0.083 to 0.113 goals per match [24]. However, in both cases, indirect free-kick actions are most effective than free kicks, which may reflect evolving defensive and indirect free-kick tactics.

Penalties are crucial in determining match outcomes and eliminations [42,43], representing the highest probability of scoring in professional football [44,45], with success rates close to 70% [39]. Present results showed that penalties were found to be the most effective action, with an average of 0.24 goals per match, demonstrating strong excitatory patterns for goals and highly inhibitory patterns for saves (Table 2). These findings exceed the historical averages reported between the 2009/2010 and 2018/2019 seasons in the top five European leagues, which ranged from 0.097 to 0.123 goals per match [24]. Results also showed that most penalties are directed towards the lower corners (Figure 3), with the most effective scores sones being the upper corners, although these zones also carry a higher probability of failure [46]. Additionally, goalkeeper effectiveness is notably higher in the lower central zones, which supports previous findings [46]. Interestingly, they key to a shooter’s success lies in deceiving the goalkeeper, as zone Y2, while still reachable by the goalkeeper, demonstrates high goal-scoring effectiveness in this study.

The effectiveness of shots is significantly influenced by the goalkeeper’s positioning, particularly within the six-yard box, where they typically intervene [13,31]. As observed in the literature, the lower section of the goal tends to exhibit higher scoring effectiveness [18]. The present study found that goalkeepers are more successful in saving shots directed toward the central columns of the goal (Figure 1), exhibiting excitatory patterns for saves and inhibitory patterns for goals. In contrast, shots aimed near the posts tend to result in goals, showing excitatory patterns for goals and inhibitory patterns for saves. This aligns with the high-risk areas identified in the bisector theory, which guides goalkeeper positioning [17], as the posts represent the most challenging zones for goalkeepers due to their later accessibility.

Regarding the field zones (Figure 2), the results of the present study also aligned with previous research that classified the zones as high, medium, and low effectiveness [17], confirming that the central areas of the field, particularly the shots within the six-yard box and its extension into the penalty area, are both the most frequently used [31] and the most effective [18]. In contrast, shots taken from the lateral areas just outside the six-yard box but still within the penalty area (zones AL2, BL2, CL2, DL2, AR2, BR2, CR2, and DR2) exhibited excitatory patterns for saves and inhibitory patterns for goals, especially when directed toward the lower part of the goal, as also reported in the literature [18]. As shots move toward more lateral positions, their effectiveness decreases [6,18], a trend also reflected in the present study through excitatory patterns for saves.

The present study also showed that shots taken from the edge of the penalty area are less effective, with excitatory patterns for saves (Figure 2). This trend becomes more pronounced as shots are taken from further distances toward midfield, supporting findings from previous research that shots taken from within 20 m of the goal have a higher likelihood of resulting in goals compared to those taken from beyond 20 m [6]. This is consistent with data from the 2006 FIFA World Cup, where 51.3% of goals were scored inside the penalty area, 32.2% from the edge of the penalty area, and only 16.5% from outside this area [31]. Therefore, we can confirm that the shot depth plays a critical role in determining the likelihood of scoring.

In line with previous research [47], foot shots were the most common finishing method following an attacking situation (Table 3). Additionally, in the present study, 17.5% of the goals were scored with headers. Although playing styles vary between teams [7], these results were consistent with the 17.7% observed in the English Premier League during the 2008/2009 season [18]. Header shots exhibited excitatory patterns for goals near the posts and inhibitory patterns for saves in the inner columns, and they were most effective within the six-yard box. This should be considered both when choosing the direction of the shot and when delivering crosses into the box.

The analysis of shot laterality revealed notable trends based on the foot used (Table 4). Shots taken from the left flank with the left foot and from the right flank with the right foot showed lower effectiveness when aimed at the near post, but higher effectiveness when directed toward the far post. Conversely, shots taken from the left flank with the right foot and from the right flank with the left foot also showed low effectiveness when aimed at the near post. These insights can help to optimize finishing strategies and inform goalkeepers’ defensive actions. This is the first study to jointly analyze the field zones, the striking leg, and the goal zone. Previous studies only examined the latter two variables [19]. However, further research is needed to fully understand the nuances of shot placement and goalkeeper positioning. Although this pattern may be due to the skewed distribution of right- and left-footed players (i.e., in this study, 4920 left-footed and 7775 right-footed shots were analyzed, indicating an imbalance in the number of shots taken with each foot).

The present study provides insights into the effectiveness of goalkeeper and forward actions, yet there are several limitations. The primary one is that it only considers shots on target recorded by FotMob, excluding missed attempts, which restricts a comprehensive evaluation of shot effectiveness. Future research should incorporate all shooting attempts to provide a more thorough understanding. Another limitation is the cross-sectional design; a longitudinal approach would enhance robustness, reduce seasonal variations, and yield more consistent results over time. However, the inclusion of data from five European leagues strengthens the generalizability of the findings, mitigating the reliance on the characteristics of a single league.

Additionally, the study does not differentiate the lateral origin of corner kicks, an element that could provide crucial insights into tactical preferences and their effectiveness. Lastly, incorporating data on the goalkeeper’s position at the moment of the shot—specifically whether they are aligned with the shot’s bisector—could improve the analysis. Examining how goalkeepers adjust their positioning could improve the understanding of defensive effectiveness and their reactions to different shot situations. Future research should consider these variables to further enrich the tactical analysis of finishing situations.

5. Conclusions

This study examines the effectiveness of shots and goalkeeper performance across various positions and game situations. The main findings revealed that the context of the game significantly impacts the outcome of the action. In this regard, penalties proved to be the most effective situation for scoring goals, while, although regular plays and free kicks create more opportunities, they present lower success rates and higher save percentages. On the other hand, corner kicks and counterattacks showed a higher tendency to result in goals, highlighting their strategic relevance.

The direction of the shot towards different areas of the goal is closely related to the success of the action. Shots directed near the posts, especially in the lower corners, were the most effective. Goalkeepers, in turn, demonstrated greater effectiveness in the central areas and at medium height.

The shooting zones on the field are directly linked to the success of the shot. The six-yard area and its vertical extensions were identified as high-effective zones.

No significant relationships were found between the body surface used and shot success. However, excitatory trends were observed for goals from header shots, with a higher probability of scoring when executed from the six-yard area and to the posts.

Finally, the effectiveness of shots depended on the relationship between the attacking side and the striking foot, with far-post shots being more successful when the foot matched the wing and near-post shots being more easily saved when it did not. These results highlight the key role of shooting angles and goalkeeper positioning in shot success.

6. Practical Applications

The present approach allows for a systematic analysis of in-game actions, focusing on attacking patterns and both offensive and defensive performance. This information is highly beneficial for coaches, analysts, and performance staff. Identifying high-effectiveness zones and play types that maximize scoring potential can develop targeted offensive strategies and optimize finishing drills. Moreover, this analysis will help to monitor player’s performance, identify weaknesses, and track improvements over time, therefore tailoring training sessions accordingly. These findings are particularly useful for goalkeepers and their specialized coaching staff, offering critical insights into shot-stopping tendencies and positioning strategies. This can lead to improve decision making and enhance response effectiveness in match situations.