| Club | Total Goals | Mean Goals | Total Assists | Mean Assists | Mean Shots | Mean Shots on Target | Mean Conversion Rate |
|---|---|---|---|---|---|---|---|
| Arsenal | 67 | 2.7 | 50 | 2.0 | 21.8 | 5.6 | 6.4 |
| Aston Villa | 61 | 2.3 | 46 | 1.7 | 18.3 | 4.7 | 4.6 |
| Bournemouth | 24 | 0.8 | 28 | 1.0 | 20.1 | 6.5 | 4.7 |
| Brentford | 54 | 1.9 | 33 | 1.2 | 15.7 | 5.5 | 3.0 |
| Brighton & Hove Albion | 63 | 2.2 | 24 | 0.9 | 18.0 | 4.9 | 5.1 |
| Chelsea | 63 | 2.2 | 32 | 1.1 | 21.6 | 6.8 | 6.9 |
| Crystal Palace | 51 | 2.0 | 37 | 1.4 | 20.4 | 4.0 | 4.1 |
| Everton | 41 | 1.6 | 17 | 0.7 | 16.7 | 6.7 | 6.8 |
| Fulham | 41 | 1.6 | 37 | 1.4 | 20.0 | 6.3 | 3.0 |
| Ipswich Town | 23 | 0.8 | 20 | 0.7 | 13.2 | 3.5 | 3.1 |
| Leicester City | 28 | 0.9 | 21 | 0.7 | 9.9 | 5.2 | 5.9 |
| Liverpool | 72 | 3.0 | 60 | 2.5 | 27.0 | 6.9 | 4.8 |
| Manchester City | 71 | 2.3 | 31 | 1.0 | 19.8 | 4.4 | 3.2 |
| Manchester United | 38 | 1.3 | 27 | 0.9 | 17.1 | 5.7 | 5.0 |
| Newcastle United | 66 | 2.9 | 37 | 1.6 | 22.7 | 9.1 | 5.9 |
| Nottingham Forest | 57 | 2.5 | 39 | 1.7 | 20.1 | 6.5 | 6.3 |
| Southampton | 23 | 0.7 | 10 | 0.3 | 9.2 | 4.9 | 4.1 |
| Tottenham Hotspur | 50 | 1.6 | 36 | 1.2 | 16.0 | 5.6 | 4.9 |
| West Ham United | 31 | 1.1 | 25 | 0.9 | 17.4 | 5.1 | 5.0 |
| Wolverhampton Wanderers | 39 | 1.2 | 34 | 1.1 | 13.5 | 4.3 | 3.0 |
Premier League Insights from the 2024 2025 Season
1. Introduction
The Premier League is widely regarded as one of the most competitive and unpredictable football leagues in the world. With a blend of elite talent, broad ranges of tactics and high intensity matches, it offers a unique environment in which small differences in performance can have a significant impact over the course of a season. The 2024/2025 Premier League season provides a rich opportunity to explore how various concepts such as attacking efficiency, defensive performance and goalkeeping shape success. By analysing performance data across the league, this report aims to highlight patterns, trends and standout contributions that help explain the dynamics of one of the most watched football leagues in the world.
2. Club Statistics
The overall club attacking statistics from the 2024/2025 Premier League season highlights some clear differences in attacking performances across the league. Clubs like Liverpool and Manchester City stand out with some of the highest totals of goals and assists, indicating both prolific scoring and creative output from their squads. Interestingly, while Newcastle United may not have the highest total goals or assists, their mean goals and assists are among the leagues highest, suggesting that this teams attacking contributions are more evenly distributed across the squad rather than reliant on a single standout performer.
Mean shots and mean shots on target further illustrate such patterns, with top performing teams not only attempting more shots per player but also demonstrating greater precision, reflected in higher shot accuracy percentages. Conversion rates provide a further emphasis on this: clubs with higher conversion rates are more efficient, turning fewer opportunities into goals effectively. These combined statistics offer a deeper understanding of attacking efficiency, revealing which teams generate both volume and quality in their offensive play. They highlight the balance between overall output and per-player contribution, providing insight into why some clubs outperform others even when raw totals are similar.
Attacking Summary of Top/Bottom 3 Teams
The scatter plot of mean shots versus mean conversion rate highlights how team attacking efficiency relates to league performance. Liverpool sits along the horizontal average line to the far right, showing very high shot volume but only average conversion and they ultimately won the league. These findings suggest their overall attacking success was driven by creating many opportunities, even if finishing was not exceptional. Arsenal is positioned in the top-right quadrant, combining above average shot volume with high conversion efficiency, yet they finished second in the league. This indicates strong attacking output but slightly less consistency compared to the champions. Manchester City is in the bottom-right quadrant, with high shot volume but below average conversion rate. This highlights inefficiencies in turning chances into goals despite creating a lot of opportunities.
At the other end of the spectrum, Ipswich Town and Southampton are both in the bottom-left quadrant, reflecting very low shot volume and conversion which is consistent with their second-last and last place finishes. Interestingly, Leicester City is found in the upper-left quadrant, indicating clinical finishing despite low shot numbers. They finished 18th, showing that efficiency alone was insufficient to compensate for a lack of attacking opportunities. Overall, the plot demonstrates that while high shot volume and conversion efficiency often align with better league performance, other factors can also play a key role in final standings.
Defensive Summary of Top/Bottom 3 Teams
To further understand the differences between successful and less successful teams within the Premier League, it is also important to look at the defensive differences. In this scatter plot, the top 3 teams in the league are found in the upper-left quadrant, indicating strong defensive performance with relatively few goals conceded and a high number of clean sheets. Notably, Arsenal and Manchester City conceded a similar mean number of goals, however, Arsenal are positioned higher on the graph which shows they achieved a higher number of clean sheets than their counterparts. Liverpool, while conceding a higher number of goals than Arsenal and City, maintained a comparable number of clean sheets. This demonstrates the consistency of their defense throughout the season.
Southampton, Ipswich Town and Leicester City are clustered together in the bottom-right quadrant, highlighting weak defensive performance with both a high number of goals conceded and few clean sheets. Out of the three bottom teams, Southampton recorded a marginally better goal prevention, while Leicester conceded the highest number of goals in the league. These defensive patterns closely align with the final league standings for the 2024/2025 season, where Liverpool were crowned champions and Leicester, Ipswich and Southampton were relegated. These findings emphasise the strong connection between defensive effectiveness and the overall success of teams in a Premier League season.
2. Attacking Statistics
| Name | Club | Position | Goals | Assists | Goal Contributions | Shots | Progressive Carries |
|---|---|---|---|---|---|---|---|
| Mohamed Salah | Liverpool | MID | 29 | 18 | 47 | 130 | 231 |
| Bryan Mbeumo | Brentford | MID | 20 | 7 | 27 | 85 | 192 |
| Erling Haaland | Manchester City | FWD | 22 | 3 | 25 | 108 | 108 |
| Ollie Watkins | Aston Villa | FWD | 16 | 8 | 24 | 84 | 83 |
| Cole Palmer | Chelsea | MID | 15 | 8 | 23 | 126 | 116 |
| Alexander Isak | Newcastle United | FWD | 23 | 0 | 23 | 99 | 132 |
| Chris Wood | Nottingham Forest | FWD | 20 | 3 | 23 | 68 | 55 |
| Matheus Cunha | Wolverhampton Wanderers | MID | 15 | 6 | 21 | 110 | 157 |
| Jacob Murphy | Newcastle United | MID | 8 | 12 | 20 | 43 | 134 |
| Yoane Wissa | Brentford | FWD | 19 | 0 | 19 | 90 | 180 |
| Morgan Rogers | Aston Villa | MID | 8 | 10 | 18 | 55 | 187 |
| Bruno Fernandes | Manchester United | MID | 8 | 10 | 18 | 96 | 254 |
| Anthony Elanga | Nottingham Forest | MID | 6 | 11 | 17 | 44 | 209 |
| Bukayo Saka | Arsenal | MID | 6 | 10 | 16 | 67 | 69 |
| Eberechi Eze | Crystal Palace | MID | 8 | 8 | 16 | 102 | 73 |
| Jean-Philippe Mateta | Crystal Palace | FWD | 14 | 2 | 16 | 70 | 115 |
| James Maddison | Tottenham Hotspur | MID | 9 | 7 | 16 | 39 | 128 |
| Son Heung-Min | Tottenham Hotspur | MID | 7 | 9 | 16 | 57 | 177 |
| Leandro Trossard | Arsenal | MID | 8 | 7 | 15 | 72 | 135 |
| Nicolas Jackson | Chelsea | FWD | 10 | 5 | 15 | 76 | 242 |
The above table of the top 20 attacking players in the league, ranked by total goal contributions (goals + assists), highlights individuals who had the greatest offensive impact amongst midfielders and forwards who played over 1500 minutes in the season. At the top of the table, Mo Salah stands out as the most productive attacker in the league combining a high goal tally with a significant number of assists, underling both scoring ability and creative influence. Closely following are Bryan Mbeumo and Erling Haaland, whose strong output reflect consistent end-product in the final third.
Looking deeper into the supporting variables helps us better understand how these players make an impact:
- Mo Salah pairs high goal contributions with a large number of total shots. This shows a player who is heavily involved in the final third and consistently looking to create goal scoring opportunities.
- Bryan Mbuemo records a slightly fewer number of shots but maintains a strong goals and notable creative return, suggesting a player who is both a primary finisher and provider.
- Erling Haaland scored 22 goals but only recorded 3 assists, indicating a more direct , goal-focused role within his team.
- Players such as Bruno Fernandes and Anthony Elanga may not lead in raw goal numbers but demonstrate high progressive carry totals, suggesting that their attacking influence extends beyond just finishing and included ball progression and chance creation.
Overall, the table shows that attacking effectiveness is not defined solely by goals and assists. While total goal contributions determine the ranking, metrics such as number of shots and progressive carries reveal different attacking profiles - from direct goal scorers to dynamic-ball progressing play makers. This broader perspective provides a more complete understanding of how midfielders and forwards contribute to their team’s attacking success.
Do Progressive Carries Affect Overall Goal Contribution?
The scatter plot of progressive carries versus total goal contributions highlights the attacking styles of midfielders and forwards who played over 1500 minutes. Most players cluster near the league averages, but the top 5 performers, highlighted in blue and labeled, stand out. Players like Mo Salah and Bryan Mbuemo combine high goal contributions with above average progressive carries, indicating they are both direct scorers while also being heavily involved in advancing the ball into dangerous areas. Other players like Erling Haaland, achieve high goal contributions with slightly fewer progressive carries, suggesting a more efficient or goal-focused attacking style. This is understandable as Haalands position as a forward emphasises goal scoring, while Salah and Mbeumo playing as midfielders, have greater opportunities to advance the ball through progressive areas. Overall, this plot reveals differences in attacking profiles; some players drive the team forward while finishing less, others focus on both and the top performers combine both elements to maximise their impact. This shows progressive carries may have more of an impact on goal contributions for midfielders than for forwards.
Players With the Most Efficient Finishing
The above bar chart shows the top 10 most efficient finishers in the league, considering players who only registered 40 or more shots to ensure a reliable sample size. Each bar represents a players goals per shot, highlighting how effective they are at converting shooting opportunities into goals. Players at the top of the chart, such as Chris Wood and Bryan Mbuemo, achieve high goals per shot ratio while maintaining a substantial number of attempts, demonstrating both consistency and good finishing. Lower ranked players in the top 10 still show strong efficiency, but with slightly less goals per shot. Overall, the chart provides a clear view of the leagues most clinical attackers, separating those who consistently convert chances from those with lower finishing efficiency or smaller sample sizes.
3. Defensive Statistics
The above scatter plot illustrates the relationship between overall defensive involvement, measured by defensive index (tackles, interceptions, blocks and clearances) and ground duel success rate. Players positioned in the upper right quadrant, such as Murillo and Lacroix, demonstrate both high defensive activity and strong duel efficiency. This indicates well-rounded and highly effective defensive performances. These individuals not only engage frequently in defensive actions but also win a high proportion of their ground duels, making them particularly impactful. Players such as Tarkowski positioned in the lower-right quadrant, show high defensive involvement but lower efficiency, suggesting they are active but less successful in 1v1 situations. Overall, the graph highlights the distinction between high-volume defenders and those who combine volume with effectiveness, helping identify the leagues most defensively dominant players.
Top 10 Defenders
The bar chart presents the top 10 players in the league ranked by their defensive index, which combines tackles, interceptions, blocks and clearances to measure overall defensive involvement. Players at the top of the chart demonstrate the highest volume of defensive actions across the season, highlighting their consistent contribution to their teams defensive stability. The clear ranking format makes it easy to distinguish the most defensively active players from those slightly below them, while still within the top tier.
Comparison of Top 5 Defenders
The radar charts above highlight stylistic differences among the top five defenders despite all ranking highly in overall defensive index. While each player shows strong contributions across tackles, interceptions, blocks and clearances, the shapes of the radars reveal where their strengths differ. Some defenders, such as Lacroix, display a more balanced profile, with consistently high values across all five metrics, indicating well-rounded defensive performance. Others show pronounced spikes in specific areas - such as Murillo in tackles and Milenkovic in possession won, suggesting strong reading of the game and ability to regain control of the all for their team. Meanwhile players like Collins and Tarkowski tend to reflect a more traditional , last-line defensive role. Including possession won adds an important dimension, as it highlights defenders who not only stop attacks but actively recover the ball and initiate transitions. Overall, the radar charts demonstrate that although the players share high defensive output, they achieve it through slightly different defenisve styles and strengths.
4. Goalkeeping Statistics
The scatter plot above highlights the relationship between goalkeeper efficiency and overall shot-stopping impact. Goalkeepers positioned in the upper right quadrant, such as Pickford and Sels, combine a high saves percentage with strong positive goals prevented, indicating they not only stop a large proportion shots but also outperform the expected goals they are expected to concede. Those with high saves rate but lower or negative goals prevented may be facing lower-quality shots, suggesting that save percentage alone does not capture a full performance. Conversely, keepers positioned in the lower-left quadrant with lower save rates and negative goals prevented, such as Verbruggen and Leno, are under-performing relative to expectation. Overall, the graph demonstrates that the most effective goalkeepers are those who pair strong efficiency with the ability to prevent more goals than expected, separating true elite performers from those benefiting primarily from team defensive structure.
Comparison of Top 5 Goalkeepers Based on Goals Prevented
The radar charts above illustrate both clear stylistic differences and similarities among the leagues top 5 goalkeepers (based on goals prevented). Although all five rank highly based on saves rate, the visual profiles show that they achieve success in different ways. Some keepers, such as Pickford and Henderson, display a strong balance across saves rate, goals prevented, high claims and punches, suggesting a well rounded presence in both shot-stopping and aerial command. Others show pronounced strength in areas such as goals prevented, while facing a relatively lower number of goals conceded, indicating their ability to outperform expected outcomes despite heavier defensive pressure. Ederson and Alisson stand out as the keepers having conceded the least number of goals within this group, which aligns with the fact their teams finished third and first in the league that season, respectively. Overall, the radar charts reveal that while these goalkeepers are united by shot-stopping efficiency, their broader contributions vary, reflecting different tactical roles, team contexts and goalkeeping profiles.
6. Conclusion
This analysis provides a detailed examination of both team and individual performances across the 2024/2025 Premier League season. By exploring attacking, defensive and goalkeeping statistics, the report highlights not only which clubs and players achieved the highest raw outputs, but also how efficiency and per-player contributions shaped overall success. Attacking analyses revealed the balance between prolific scorers and evenly distributed squad contributions, while defensive metrics underscored the importance of collective defensive actions and ground duel success. Goalkeeper performance, which was examined using variables such as save rates, goals prevented and aerial involvement, further illustrated how individual excellence can influence team outcomes. Overall, the findings demonstrate that success in modern football is rarely determined by single statistics; rather it emerges from a combination of volume, efficiency and consistent contributions across the squad, emphasising the interplay between individual and collective performance in determining league outcomes.