Kama.Sport, a leading provider of software solutions and data analysis for the world of football, continues its international expansion with the launch of a new partnership with Al-Shamal Sports Club, a prominent team competing in the Qatar Stars League, the top tier of Qatari football.

Founded in 1980 and driven by growing ambition within the Middle Eastern football scene, Al-Shamal has embarked on a strategic journey focused on data and innovation. To support this vision, the club has chosen Kama.Sport as its official technology partner for the 2025/26 season.

**The shared goal**: to provide the technical staff and performance department with a complete digital platform, built around highly specialized modules, including:
- Pre & Post Match Analysis – for detailed analysis of matches and opponents
- Training Manager – for planning, managing, and monitoring training sessions

Thanks to its cloud-based, multilingual, and scalable architecture, Kama is now a solution accessible to clubs all over the world, delivering the know-how developed alongside top European football professionals.

_“We are excited to start this partnership with Al-Shamal Sports Club,”_ says Davide Ragazzi, CEO of Kama.Sport. _“Kama is a tool built together with the world’s best, designed for those who truly want to make a difference.”_

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Kama.Sport and Al-Shamal Sports Club together, driven by innovation.

Kama is international: welcome Al-Shamal Sports Club

Kama.Sport, a leading provider of software solutions and data analysis for the world of football, is pleased to announce the start of its collaboration with Pisa Sporting Club, newly promoted to Serie A.

Founded in 1909, with seven appearances in the top flight and an eighth on the horizon, Pisa SC has built a strong and recognizable identity both on and off the pitch. As the club prepares for its new journey among Italy’s football elite, it has chosen Kama.Sport to support its technical and medical staff with cutting-edge technology.

**The shared goal**: to centralize and optimize all activities within the performance and medical departments through a single integrated platform — enhancing the club’s existing technological infrastructure and complementing it with the most advanced innovations in the sport-tech industry.

_“We are proud to have been chosen by Pisa Sporting Club and excited to begin this new Serie A season together,_”
says Davide Ragazzi, CEO of Kama.Sport.
_“We’ll provide the staff with a data-driven tool that is both practical and immediately effective”_.

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Kama.Sport and Pisa Sporting Club announce a new partnership as they join forces in Serie A.

Kama.Sport is the new technology partner of Pisa Sporting Club

Bologna FC claims the 2024/25 Coppa Italia – congratulations!

A victory that rewards the quality of the daily work of a club that has grown with consistency and strength, both on and off the pitch.

As an **Official Supplier**, we’re proud to stand alongside Bologna FC, providing our technology and solutions in support of athletic performance.

Congratulations to the entire Rossoblù family on this historic achievement.

We’re proud to be part of your journey.

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Kama.Sport proudly celebrates the success of Bologna FC, winners of the 2024/25 Coppa Italia, at the end of a journey built on vision, identity, and determination.

Congratulations to Bologna FC for winning the 2024/25 Coppa Italia Frecciarossa.

In modern football, data analysis has revolutionized how coaches and match analysts prepare their teams and plan matches. Kama.Sport, with its combination of **advanced software** and expertise in **data science** and **artificial intelligence**, stands as a leader in this revolution, offering analytical tools that go beyond simple visual observation. Within the **all-in-one platform of Kama**, the match report is one of the flagship tools, allowing for an unprecedented level of detail and depth in examining every aspect of a match. Its innovative approach, concrete results, and outstanding analytical capabilities have enabled Kama to become the **[Innovation Partner of Lega Serie A](https://www.legaseriea.it/it/media/serie-a/inizia-l-era-data-driven-6k3090l)** and **[Technical Provider of FIGC](https://blog.kama.sport/kama-sport-and-figc-together-for-a-data-driven-future)**, achieving remarkable successes such as SSC Napoli's Serie A championship victory in 2022/23 as the Official Technical Provider and [Bologna FC](https://blog.kama.sport/bologna-fc-1909-and-kama-sport)'s qualification for the Champions League in the 2023/24 season.

## The Kama Match Report
The Kama.Sport match report is a detailed and intuitive document that provides a comprehensive view of the match, divided into sections covering various key aspects of the game. This advanced tool is designed to give coaches and match analysts the crucial information they need to make informed decisions and improve team performance.
The true strength of the match report lies in its ability to delve into every detail of the game thanks to the vast amount of data that the **system integrator of Kama.Sport** processes through sophisticated algorithms. This tool is **unique** in the world of football, allowing for an unparalleled level of analysis and precision, transforming raw data into easily understandable and usable strategic insights.

### Timeline of Events
The timeline provides an overview of the key events of the match, such as goals, yellow cards, substitutions, and other relevant moments, allowing for a clear and immediate understanding of how the match unfolded minute by minute.
Notable are the **Momentum** and **Cumulative** graphs:
- **Match momentum**: Displays the momentum of the match minute by minute, highlighting the periods of dominance and the critical phases.
- **Cumulative xT**: Compares the overall volume of play generated by the two teams throughout the whole game.

### Possession Phase
This section analyzes the ball possession of the teams, including details on goal kicks, offensive build-up, and types of attack. Data on total ball possession, percentage of possession in the offensive half and the offensive third, as well as Field Tilt, which measures pressure exerted on the field, are provided.
- **Goal Kicks**: Total number of goal kicks, with percentages of offensive development.
- **Offensive Build-up**: Analysis of offensive build-up, including the percentage of offensive developments and finishes.
- **Ball Possession**: Percentages of total ball possession and in the offensive areas of the field.
- **Attacks**: Number of attacks by both teams based on the field area and type.
- **Entries into the Opponent's Area**: Number and type of entries into the opponent's area, such as from dribbling, short pass, cross, etc.
- **Expected Threats (xT)**: Value that quantifies the goal opportunities generated by different actions of the game.
<hr>

##### Euro 2024 Final Spain 2 - 1 England: Build up Analysis
![Spagna_Inghilterra_EN.webp](https://blog-staging.s3.eu-central-1.wasabisys.com/Spagna_Inghilterra_EN_b3724d09b9.webp)
_A notable image representing an extract from the **Spain - England final** of the 2024 European Football Championships.
Regarding the build up theme, it is evident how Spain's **full-field pressing** is clear from the high percentage of build up involving the England goalkeeper and the **high number of low build up**. This underscores England's difficulty in moving out of their defensive zone with the ball at their feet.
Analyzing **ball possession** and **Field Tilt**, it is clear that **Spain dominated the match**. The Spanish team maintained control of the game in all areas of the field, demonstrating **superiority in both possession and territorial control**._
<hr>

### Contested Phase
This section examines the contested phases of possession, providing data on recovered balls, lost balls, duels won, and successful tackles. Offensive and defensive recoveries, the percentage of recoveries over balls played conceded, and positive transitions are analyzed.
- **Recovered Balls**: Number of recovered balls in offensive and defensive phases.
- **Lost Balls**: Number of lost balls in offensive and defensive phases.
- **Duels**: Percentage of duels won, including aerial duels and tackles attempted and succeeded.
- **Recoveries from Lost Balls**: Total number of lost balls by both teams and percentage of total and offensive lost balls, as well as PPDA, acronym for Passes (allowed) Per Defensive Action, a metric measuring the effectiveness of pressure exerted on the offensive half.
<hr>

##### Euro 2024 Round of 16 Switzerland 2 - 0 Italy: Pressure Analysis
![Svizzera_Italia_EN.webp](https://blog-staging.s3.eu-central-1.wasabisys.com/Svizzera_Italia_EN_aa427c8396.webp)
_The image represents an extract from the **Switzerland - Italy** match of the 2024 European Football Championships. The **heatmap** clearly shows the **pressure exerted by Switzerland on Italy**, indicating a **higher recovery center of gravity** for Switzerland compared to Italy._
_The **data on recoveries from lost balls**, both in absolute and percentage terms, further **emphasize** the **importance of aggression**, particularly the counter-pressing after losing the ball, as a **key element** for Switzerland's victory._
<hr>

### Player Analysis
This section analyzes in-depth the possession phase, the offensive phase, and the duels of individual players, presenting the data in tabular format. Each table includes detailed information on minutes played, number of passes, crosses, goals, and assists. Additionally, recovered balls in offensive and defensive phases, aerial duels won, and fouls committed or suffered are highlighted.

## Conclusion
The **Kama.Sport match report** is an indispensable tool for anyone who wants to bring their team to the highest level of performance. Thanks to its **detailed structure** and the **depth of the analyses provided**, **coaches** and **match analysts** can gain a **comprehensive understanding of the game**, transforming data into concrete actions to continuously improve team performance. With **Kama**, innovation and expertise are at the service of football.

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Discover how the Kama Match Report is becoming increasingly indispensable for technical staff who want to delve deep into football match analysis.

Kama Match Report: the match analysis with a fine-tooth comb.

As football continues to grow and evolve technologically, Kama stays one step ahead to support football professionals in elevating their game to new heights. To highlight our innovative efforts, we recently unveiled one of our newest solutions, Kama Team Labels. Powered by advanced statistical models and machine learning, Kama Team Labels summarize the most impactful aspects of each team's game, allowing for the instantaneous and intuitive analysis of a team's statistics.

The outputs are segmented into 3 unique sections (Strengths, Weaknesses, Style of Play) that reflect the overall performance of a team while highlighting their strong points, shortcomings and overall game style. The use of Kama Team Labels allows users to quickly navigate the complex football ecosystem and facilitate a comprehensive, rapid, and intuitive analysis of a team. Despite all of its perks, the feature was limited to teams and served more as a general overview rather than an extensive report. 

To ensure that users receive the most accurate and detailed information about a football team’s capabilities, we are now excited to present the newest addition to the Kama platform - Kama Player Labels. An extension of the Team Labels, Kama player labels zoom in on a player’s strengths and weaknesses, making it more intuitive for users to analyze the true value a player brings on the pitch.  

Kama Player Labels are categorized into 3 unique sections: Game Features, Strengths and Weaknesses. 

![Kama Player Labels: Strengths and Weknesses Scale.](https://blog-production.s3.eu-central-1.wasabisys.com/Whats_App_Image_2024_03_07_at_15_28_01_28a0596afb.jpeg)

**1. Game Features**

Through Machine Learning algorithms, players are categorized based on specific playing characteristics for their respective roles. The goal is to provide a precise and objective description of the player's on-field abilities, based on their contribution to the team, evaluated across a substantial group of game statistics. Each group is displayed with a relative percentage, indicating how well the player's characteristics align with the specified archetype.

For the specific role, the algorithm identifies the following archetypes:

- _Offensive phase enhancer:_ Striker who makes 1vs1 skills his specialty, able to dribble past defenders and turn the action from defensive to offensive through effective carries.
- _Target offensive player:_ Offensive reference who is not necessarily a striker, physically strong and who plays for the team.
- _Central scorer:_ Striker who prefers patrolling the central area of the attack, seeking to finish the play.
- _Breakthrough offensive player:_ Player who positions himself in the offensive zone but makes breakingthrough plays his specialty.
- _Between the lines target:_ Positional offensive player, dominant on the high ball, with great physical presence. Tends to position himself as a reference in the central zone.
- _Reliable offensive player:_ Offensive player who does not excel or flaw in any precise characteristic of the game, a balanced player.
- _Versatile offensive player:_ Multipurpose offensive player, able to cover multiple roles reliably, physically strong and dangerous when carrying. Not always effective in scoring.
- _Offensive chance creator:_ Clever offensive player whose priority is to create through dangerous passes and crosses, rather than finishing.
- _Dynamic scorer:_ Forward who likes to roam across the entire offensive front, dangerous with the ball at his feet, and a threat in the goal area.

**2. Strengths**

Strength points are divided into offensive and defensive, then evaluated on three distinct levels, identified as follows:

- Top in the best 5 European competitions: indicates that the player is in the top 5th percentile among all players in teams belonging to the top 5 European leagues.
- Top in the league: indicates that the player is in the top 5th percentile among players in their respective league.
- Strong in the league: indicates that the player is between the 85th and 95th percentile among players in their respective league.
If the player is both Top in the best 5 competitions and Top in their own league, only the European level will be shown, implying the one related to their own league.

We consider the Premier League, Serie A, Bundesliga, Ligue 1 and LaLiga to be the Top 5 European leagues. It is also important to mention that all labels are calculated by analyzing data from the last 1000 minutes played.

**3. Weaknesses**

Weakness points are divided into offensive and defensive, then evaluated on three distinct levels, identified as follows:

- Worse in the best 5 European competitions: indicates that the player is in the worst 5th percentile among all players in teams belonging to the top 5 European leagues.
- Worse in the league: indicates that the player is in the worst 5th percentile among players in their respective league.
- Weak in the league: indicates that the player is between the 5th and 15th percentile among players in their respective league.

Same as the strength labels, If the player is both Top in the best 5 competitions and Top in their own league, only the European level will be shown, implying the one related to their own league.

![Lewis Ferguson Player Labels.](https://blog-production.s3.eu-central-1.wasabisys.com/Whats_App_Image_2024_03_07_at_15_28_01_1_e2acab27b6.jpeg)




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Find out how Kama’s newest feature enhances the analytical process and provides you with a comprehensive depiction of a player’s qualities at the click of a button. 

What are Kama Player Labels and Why Are They The Future of Player Analysis 

The Italian Football Federation (FIGC) has signed a historic innovation-oriented technical supply partnership with Kama.Sport, a leading start-up in the Italian sport-tech landscape. This strategic collaboration will enable the FIGC to explore sports data in a more advanced way and digitise management processes. 

The use of Kama.Sport's cutting-edge technology will allow the FIGC to integrate all the numerous data sources at its disposal, within a single platform. This will lead to a significant improvement in the efficiency of data analysis and management, allowing for in-depth exploration at both quantitative and qualitative levels. 

As Technical Supplier, Kama.Sport will provide the FIGC with all the skills and resources necessary to develop ad-hoc solutions, specifically designed for the Federation's needs. This will result in FIGC monitoring and scouting tools that will support the daily work of the Italian Federation, from the first team to the youth teams, from the under-21 to the under-15. 

Furthermore, FIGC will be able to count on the assistance of Kama.Sport in the creation of proprietary applications dedicated to the technical sector. These applications will involve a wide federal audience through detailed statistics on players and teams of the main European Leagues, the integration and uploading of original content and videos, as well as an internal information system and a series of useful tools for the evolution of a harmonious internal organisation. 

"The work that Kama.Sport has carried out with many important customers in recent years, identifying and developing concrete solutions to the specific needs of professional football, complements the digital and technological evolution of the sector by expanding the opportunities for technical development in football. We are pleased to be able to rely on Kama.Sport's expertise to optimise current processes and jointly develop the best technologies for the near future'. 

**Marco Brunelli, Secretary General of the Federazione Italiana Giuoco Calcio**

"Supporting and working alongside the FIGC, ranging from the technical to the organisational areas, represents a valuable opportunity for Kama that highlights the high standards required by football at the highest level. Analysis and data processing are central elements in the decision-making process. One of the main objectives that Kama has set itself is to speed up these processes and make them more accurate and effective. To achieve this, we have specialised in developing the best solutions, combining the skills and experience gained by our technical staff in the field with quantitative and qualitative analyses, extracting the most from the enormous amount of data available". 

**Davide Ragazzi, CEO of Kama.Sport**


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The Italian start-up, a leader in the sport-tech landscape of data integration, will support the FIGC in its sport-performance technology transition. 

Kama.Sport and FIGC Together For a Data-Driven Future 

Among avid football enthusiasts, it is a common phenomenon for every supporter to showcase and assert their coaching prowess, especially in the aftermath of a disappointing match. Fans spend countless hours engaging in passionate discussions, dissecting player performances, critiquing tactical decisions, and delving into controversial game incidents. Although most opinions are constructed purely based on a team’s weekend performance, this passion and controversy contribute to football’s immense popularity while at the same time making it so difficult to analyze objectively.

Given the great number of playing styles and game tactics, we are constantly seeing new, creative ways of approaching the game. Beyond the spirited "pub debates", football experts are now interested in objective facts about their players and opponents to make informed, tailored and timely decisions and elevate their chances of success. This is where data analysis comes into play.

The main objective of football analytics is to comprehensively and objectively evaluate player performance through a meticulous examination of match event data. This process not only highlights the perceptible highs and lows of outstanding and lackluster performances but also offers nuanced insights into players who may not garner a lot of attention due to their specific roles or assignments on the field.

![Expected Threat Statistics for the Serie A. ](https://blog-production.s3.eu-central-1.wasabisys.com/221_a70f415dd3.jpg)

However, navigating the football analytics landscape presents challenges that cannot easily be overlooked. Some of the main challenges are:

**1)Offensive Bias:** As the primary objective of football is to score more goals than your opponents, event data is predominantly skewed towards offensive actions. This results in a noticeable imbalance between offensive and defensive statistics.

**2)Player Roles and Statistics:** Offensive players are often considered "volume" players, accumulating statistics through frequent involvement in the play. In contrast, defenders are deemed "situational" players, requiring readiness for infrequent but crucial tackles and duels. This discrepancy not only limits the availability of statistics for defenders but also challenges the notion that "more" necessarily equates to "better."

**3)Opponent Quality Bias:** Evaluations based on a single game are susceptible to bias stemming from the caliber of the opposing team. Statistics that appear commendable against top-tier teams may lose significance against lower-ranked opponents.

**4)Normalization Challenges:** While normalizing statistics "per 90 minutes" aids in achieving a more comprehensive representation of data, it introduces potential outliers for players with brief playing durations. Robust checks become imperative to mitigate distortions arising from such anomalies.

In light of these considerations, we have chosen to sidestep the intricate evaluations of individual matches, and instead concentrate on comprehensive assessments spanning entire tournaments. The rationale is that aggregating data across multiple matches helps mitigate the impact of various issues inherent in single-game analyses, providing a more holistic perspective on player performance.

## Kama Score

In the preliminary stages of formulating our comprehensive performance index (Kama Index), it is important to delve into the detailed nature of the data, which is ranked based on various magnitudes:

- Low-ranged data, exemplified by metrics such as aerial duels won.
- Medium-ranged data, represented by factors like lost balls.
- High-ranged data, such as successful passes.
- Fixed interval data, encompassing every percentage statistic.

Given our intent to construct the index through a synthesis of key statistical evaluations, a crucial prerequisite is to normalize these diverse statistics to a uniform scale, ideally ranging between 0 and 10. This normalization facilitates a seamless integration of scores, making it easier to compute the final index score. In essence, this approach can be conceptualized as a translation: scores change more rapidly where observations are densely concentrated, and the rate of change diminishes in regions where observations are less dense.

## Kama Index

In the context of our statistical analysis, each type of data now corresponds to objective scores. Negative occurrences, such as fouls, possessions lost, and missed chances, have been inverted to align with a standardized scale. The subsequent task involves the judicious selection of scores most fitting for various player profiles.

To recognize the distinct roles and characteristics of each footballer, we categorize players into seven distinct roles:

1. Goalkeeper
2. Full back
3. Center back
4. Midfielder (including defensive midfielders)
5. Wide midfielder (including those in a mid-5 formation)
6. Winger and attacking midfielder (players operating around the opponent's area)
7. Forward

While we collect an extensive pool of over 300 statistics, we also ensure to curate a meaningful subset. Initial attempts with a mere 10 statistics revealed an undesirable flattening of results and a loss of valuable information. Consequently, for each outfield role, we judiciously select between 6 and 8 statistics, with goalkeepers requiring only 4 key statistics due to their comparatively limited dataset.

![Kama Index explanation](https://blog-production.s3.eu-central-1.wasabisys.com/Index_Info_3781b876b9.png)

To derive the KamaIndex, we use a very straightforward approach: a scalar product between scores and a vector of weights, where each element represents the importance weight of the corresponding statistic. Normalization is achieved by dividing the result by the sum of weights. This process, being a convex combination of values within the [0-10] range, ensures that the KamaIndex also falls within this specified range [0-10].

In the future, we are contemplating an extension that focuses on evaluating performances based only on the last 1500 minutes played. This feature would allow for the interpretation of recent form throughout an entire season for players who surpass this threshold. Conversely, players falling below this minimum threshold (due to hierarchy or injury reasons) have their data sourced from the previous season, albeit at the cost of reduced result reliability.

## Kama Index for Players

To showcase what the Kama Index looks like, we have selected and ranked a few Serie A players based on their performance so far this season. 

![Wojciech Szczęsny Kama Index analysis. ](https://blog-production.s3.eu-central-1.wasabisys.com/Szczesny_2689a44657.png)

We first take a look at goalkeepers as they are the ones whose evaluation is most likely to be misleading and misread. Goalkeepers playing for teams with weaker defenses may showcase seemingly impressive statistics, while those in teams with robust defenses may appear relatively inactive. Notably, Juventus’ goalkeeper, Wojciech Szczęsny, has emerged as one of the standout performers of the season. Despite a lower-than-average saves per game metric, attributable to the team's solid defensive organization, Szczesny holds the league's best save percentage while also shining in the building-up phase of the game, where he shines with his impressive passing abilities. Szczesny has a Kama Index of 8.28 so far - one of the leading rankings among goalies in the Serie A. 

![Lucas Martinez Quarta Kama Index analysis.  ](https://blog-production.s3.eu-central-1.wasabisys.com/Quarta_74bb562811.png)

Transitioning to the center-back role, Fiorentina's defensive stalwart, Lucas Martinez Quarta, consistently garners recognition as a top-class performer in the league. Although he doesn’t shine with any superior physical attributes, he manages to excel as a consistent and versatile defender who displays stellar playmaking from deep positions and makes his presence known on the offensive end with three goals so far this season. He rakes in an impressive 7.97 Kama Index. 

![Hakan Çalhanoğlu Kama Index analysis. ](https://blog-production.s3.eu-central-1.wasabisys.com/Chala_59f6419110.png)

In the midfield, the zone characterized by the most diverse parameters, Hakan Çalhanoğlu emerges as the epitome of excellence, achieving the highest KamaIndex in Serie A with an impressive 9.7. Calhanoglu's multifaceted skillset encompasses defensive intensity, superb playmaking abilities, a potent long-range shooting ability, and an impeccable record as a penalty kicker.

![Matteo Politano Kama Index analysis. ](https://blog-production.s3.eu-central-1.wasabisys.com/Politano_64266740ec.png)

And finally, turning our attention to strikers, we spotlight Matteo Politano, who has played a pivotal role in maintaining Napoli's resilience amidst a challenging season following their last title-winning season. While Osimhen and Kvaratshkelia are struggling to reach the heights achieved during the 22/23 campaign, Politano has been outstanding during the first half of the 23/24 season. Leading the standings for expected threats, his proficiency lies in his dynamic dribbling abilities, strategic movement and his ability to create space for his cannon of a left foot. All of these qualities contribute to his impressive 8.69 Kama rating.  

## Kama Index for Teams

While our focus has primarily been on evaluating individual players, it's essential to highlight that Kama Index is equally suitable for assessing team performance, with some minor distinctions. In order to have a complete, holistic picture of team's capabilities, the Kama Team Index incorporates three different indexes instead of the one applied for players. 

1. Offensive Phase Index
2. Defensive Phase Index
3. Transition Phase Index

Similar to the player index, each of these three indices incorporates a unique set of parameters that embody the essence of the respective phases. In some instances, certain parameters that are unique to a given team are also considered in the evaluation. 

![Roma Kama Index breakdown](https://blog-production.s3.eu-central-1.wasabisys.com/241_33da30d7dd.png)

While elite teams are naturally expected to excell across all three indices, the division into offensive, defensive, and transition phases also reveals a team’s playing philosophy and approach to the game. The Kama Index showcases the strengths and weaknesses of teams while providing valuable insights into their distinctive strategies. 


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Introducing the revised and improved Kama Index, the best way of evaluating a player's performance and understanding their true value. 

Kama Index: Understanding a Player's True Value

Leading software and data analysis provider, Kama.Sport, becomes the Official Data Partner of U.S. Ancona for the 2023/2024 season. Kama joins forces with the professional football club to support their digital transition and enhance the outcomes of tactical and strategic decision making processes, both on and off the pitch.  

Specializing in data integration and digital innovation, Kama will utilize the most advanced technologies in the field of sports data to U.S. Ancona to manage its daily operations more efficiently and unlock their maximum technical and tactical potential.

"We are delighted to have been chosen by U.S. Ancona to contribute to their digital transition and technological innovation," says Davide Ragazzi, CEO of Kama.Sport. "We will provide our expertise and professionals to collaborate with Ancona in maintaining the highest technical-tactical standards, following a data-driven strategic vision."

Find out more about Kama.Sport at [https://kama.sport/en/home/](https://kama.sport/en/home/)


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Kama.Sport announces new partnership with professional football club U.S. Ancona for the 2023/2024 season. 

Kama.Sport is the New Official Data Partner of U.S. Ancona