Swiss U17 & U19 Elite 25/26: A Data-Driven Scouting, Talent & Team Analysis

In this blog, we present a large and detailed analysis of the current Swiss U17 and U19 Elite competitions using football data and performance analytics. The analysis covers both player performance and team performance.

At player level, we use data scouting, player radars, key performance indicators and position-specific profiles to identify standout talents and compare players in a fair, data-driven way. This helps highlight forwards, midfielders and defenders who perform strongly in their specific roles.

At team level, we analyse playing styles through team radars and tactical data. This includes possession behaviour, chance creation, pressing intensity, defensive stability, expected goals (xG), expected goals against (xGA) and expected points. These metrics help us understand not only match results, but also the underlying performance quality of each team.

The goal is to provide a data-based overview of the Swiss U17 and U19 Elite competitions and make player development, team strengths and tactical trends easier to understand.

footballytics

Since 2021, we have combined deep tactical football expertise with advanced data analysis to help clubs, agencies and players make smarter, more sustainable decisions in scouting, match analysis and on the pitch. Work with an analytics partner, not just a data platform.

What is Data Scouting

Data scouting is a form of player scouting pre-selection. This is because it is neither possible nor sensible to use data to identify the absolute best player. Data helps to identify the 50 most suitable players from among thousands (pre-scouting), a group which is highly likely to include the top 10.

Depending on the market, data serves different purposes, but is always part of the scouting process.

In the primary market, the players are well known. Data is used here to validate scouting assessments. In the secondary market, where there are many unknown players, data is used to select the best and most suitable players from a large pool of profiles. Identifying the very best candidates remains the task of the scouts, drawing on their expertise and experience.

Data may or may not confirm your perception. In either case, this is beneficial. Either it reinforces your view, or it forces you to look at things more closely.

In response to a request, we will today analyse the Swiss U19 and U17 Elite teams from the 2025–26 season from a data perspective. For our complementary data scouting, we use the following smart approaches and methods.

1) Value Adjustment

To ensure that players are compared as fairly as possible, we adjust offensive and defensive performance metrics to account for context.

Depending on the metric, the adjustment is made per possession, per pass, per touch, or even per specific action. The aim is to establish a meaningful relationship between input and output. This highlights not only players from dominant possession-based teams, but also players from teams with less possession, whose performances are otherwise often underestimated.

Adjusting for the possession context is particularly important. Many models only take into account the team’s overall possession. We, however, have developed a method that accounts for a player’s individual possession context during their time on the pitch.

This Player Possession Adjustment (ppAdj) enables a more precise and fairer normalisation of performance and significantly improves the comparability of players from different playing systems and teams.

2) Data Scouting with Position Profiles

We have developed over 20 detailed position profiles that enable a precise analysis of players and their tactical roles. A defensive midfielder, for example, requires different key metrics to an attacking one, whilst a technically gifted centre-back with strong ball-playing ability has very different requirements to a traditional ball-winning defender.

Thanks to this precise fine-tuning, we identify the best and most suitable players – individually tailored to the clubs’ playing styles. In addition to traditional positions and roles, we also take modern interpretations into account, such as the inverted full-back or the deep-lying striker (False 9) . For midfielders alone, we have defined seven position profiles. In this blog, however, we use only the main position profiles.

3) Data Scouting with Similarity Algorithms

Imagine being able to spot up-and-coming talent at an early stage. Not by chance, but based on precise data analysis. That is exactly what intelligent similarity algorithms make possible.

They compare player profiles, analyse performance data and playing styles, and identify talents who bear a particularly strong resemblance to the profiles of established stars. This allows us to discover promising young players where others hardly look – in smaller leagues, youth leagues or emerging markets.

This approach became famous in sport through Bill James and later through Moneyball. It does not claim that a player is as good as the benchmark, but rather that their profile is similarly characterised.

Using Kevin de Bruyne in his prime as an example, our algorithm identifies players with a similar profile of strengths, such as Iliass Bel Hassani or the then-young Matt O’Riley, who later moved to Brighton. Similar profiles also emerged for Florian Wirtz, including Jens Petter Hauge. Such comparisons can be applied to any league.

This is how we identified Lennart Karl back in the U17s: our similarity algorithm showed an 89.45 % match with Ousmane Dembélé.

That doesn’t mean Karl is on the same level as Dembélé. Rather, the similarity shows that Karl performs with similar attributes and strengths within his own league. His strengths and weaknesses compared to his league rivals are similar to Dembélé’s profile when compared to his Ligue 1 peers.

With years of experience in building and calibrating football metrics and weighting models, we have developed a player evaluation framework that delivers highly relevant results. Our clients confirm that the players identified by our models match their recruitment profiles and performance requirements exceptionally well.

Data Scouting Swiss U17-U19 Elite

The following analyses are based solely on player and team data. (Source: Wyscout)

The scores are based on our position profiles and are calculated as the average of the relevant roles. For example, a defensive midfielder’s score is made up of the average of the Defensive Midfielder, Number 6 and Possession Enabler profiles. All values are normalised on a scale of 0 to 100, with 100 corresponding to the best player within the comparison group.

Players have been assigned to their main Wyscout position based on the position in which they have played the most minutes.

You find the Player Radar Interpretation Helper here: https://www.footballytics.ch/playerradar

Central Defender

Centre-backs are difficult to evaluate with data because key qualities such as anticipation, positioning and space control often prevent actions from happening in the first place. Since most data focuses on on-ball events, much of their defensive impact remains in the dark.

LGE	Player	Team	Position	Age	Min	Score
U17	G. Mihajlovski	Servette U17	RCB, CB	17	1137	100.00
U17	E. Guire	Servette U17	LCB	17	2154	91.49
U17	S. Tanner	St. Gallen U17	LCB, RCB	16	1199	90.27
U17	M. Dos Santos	Sion U17	LCB, CB	16	1096	78.63

G. Mihajlovski (Servette U17, 17, RCB) profiles as a modern ball-playing centre-back with an exceptional ability to progress possession. He ranks among the league leaders for progressive passes, progressive carries, assists and expected assists, while also posting elite numbers in interceptions and shot blocks. His combination of defensive anticipation and outstanding distribution makes him one of the most complete U17 centre-backs in Switzerland.

LGE	Player	Team	Position	Age	Min	Score
U19	J. Kurmann	Luzern U19	LCB, RCB	19	1440	100.00
U19	Y. Ramdane	Servette U19	LCB, RCB	18	1299	98.33
U19	I. Onwuzulike	Winterthur U19	LCB	16	1240	98.12
U19	C. Graf	Luzern U19	RCB, LCB	19	1679	94.02
U19	V. Loboda	Young Boys U19	RCB, CB, LCB	19	1378	93.49
U19	J. Eglin	Basel U19	LCB, LB	17	1029	92.58
U19	A. Sekulic	Zürich U19	CB, RCB, LCB	18	1211	90.44

Our data profiles enable a quick and qualitative initial assessment of players. They provide a data-driven evaluation of performance at a glance and are ideal for initial player screening in the decision-making process. The profiles offer a concise overview of strengths, weaknesses and potential for development. All performance data is compared against players in the same position and in the same league (sample size). This saves time in player evaluation and ensures that the focus remains on the truly relevant profiles. Our data covers 600+ leagues worldwide, including women’s and youth competitions. Player radars for all players in a league can be ordered at a reasonable price.

Fullback

The fullback is like the pawn in chess. He can cover, protect the chain, defend forwards, steal meters and then transform into the mighty queen in attack.

LGE	Player	Team	Position	Age	Min	Score
U17	L. Zimmermann	Luzern U17	RB	16	2407	100.00
U17	E. Bajraktar	Young Boys U17	RB, RCB	17	839	89.27
U17	G. Roskovic	Zürich U17	LB, LWB	17	1911	86.80
U17	A. Kubli	Grasshopper U17	RB, RCB, LCB	16	1363	81.75
U17	N. Kobel	Thun U17	RB, LB	16	1240	78.45

L. Zimmermann (Luzern U17, 16, RB) profiles as an elite attacking full-back with exceptional creativity and ball progression. He ranks among the league leaders for progressive passes, assists, xA and shot assists, while also posting strong numbers in box presence and chance creation. Combined with solid defensive output and high passing quality, he offers a rare blend of offensive impact and all-around contribution from the right-back position.

LGE	Player	Team	Position	Age	Min	Score
U19	V. Beck	Zürich U19	LB, LWB	19	1265	100.00
U19	T. Goll	Grasshopper U19	RB, RCMF, RWB	18	858	84.39
U19	M. Correia	Basel U19	RB	18	1271	78.95
U19	E. Rrudhani	Winterthur U19	LB, RWB, LWB	18	1215	78.52
U19	L. Mota Campos	Zürich U19	RWB, RB, LB	18	1901	71.11
U19	B. Dema	Young Boys U19	LB, RCB, RB	18	930	69.67

V. Beck (Zürich U19, 19, LB) profiles as an elite attacking full-back with exceptional ball progression and chance creation. He ranks among the league's best for progressive carries, carries into advanced areas, assists, xA and shot assists, while also contributing significant goal threat through shots and box presence. Combined with strong defensive activity, Beck offers a rare blend of creativity, dynamism and end-product from the left-back position.

Defensive Midfielder

LGE	Player	Team	Position	Age	Min	Score
U17	A. Smajic	Luzern U17	RCMF, DMF, RDMF	17	1227	100.00
U17	J. Bakambo	Neuchâtel Xamax U17	DMF, RCMF, LDMF	16	839	99.07
U17	E. Derguti	Lausanne Sport U17	DMF, RCMF, RDMF	17	1987	87.57
U17	J. Baur	Grasshopper U17	RDMF, RCMF, DMF	16	917	84.55
U17	S. Ghirlanda	Team Ticino U17	DMF, RCB, LCMF	17	2261	78.98
U17	L. Shala	Grasshopper U17	LDMF, LCMF, DMF	16	1301	78.94
U17	A. Huber	Winterthur U17	RCMF, DMF	16	1804	78.48

A. Smajic (Luzern U17, 17, RCMF) profiles as an elite playmaking midfielder with outstanding creativity, progression and ball retention. He ranks among the league leaders for progressive passes, assists, second assists, xA and passing quality, while also contributing significant goal threat through shots and goals. His combination of chance creation, technical security and forward-thinking distribution makes him one of the most complete midfielders in the Swiss U17 Elite.

LGE	Player	Team	Position	Age	Min	Score
U19	Y. Odin	Winterthur U19	LCMF, RCMF	17	1672	100.00
U19	K. Pinto Da Silva	Winterthur U19	RCMF, LCMF	19	1072	95.21
U19	I. Muccia	Luzern U19	DMF, LDMF, AMF	19	1558	87.73
U19	S. Furundzic	Grasshopper U19	RCMF, LCMF	16	762	78.17
U19	S. Isljami	Sion U19	LCMF, LW	19	1956	73.13
U19	N. Häusler	Zürich U19	DMF, RCMF	19	1594	72.42

Y. Odin (Winterthur U19, 17, LCMF) profiles as a defensively dominant box-to-box midfielder with excellent ball-winning ability and strong technical security. He ranks among the league leaders for defensive actions, tackles, interceptions and aerial duels, while also posting elite short- and medium-passing numbers. His profile is built around defensive impact, ball retention and midfield control, providing a strong foundation for both possession and transition phases.

Central Midfielder

LGE	Player	Team	Position	Age	Min	Score
U17	A. Smajic	Luzern U17	RCMF, DMF, RDMF	17	1227	100.00
U17	L. Shala	Grasshopper U17	LDMF, LCMF, DMF	16	1301	73.72
U17	E. Maksutaj	Winterthur U17	DMF, RCMF	17	2066	70.51
U17	L. Istrefi	Grasshopper U17	RCMF, LDMF, RDMF	17	1598	68.44
U17	E. Derguti	Lausanne Sport U17	DMF, RCMF, RDMF	17	1987	62.69
U17	J. Henauer	Winterthur U17	LCMF	16	1866	62.24

A. Smajic (Luzern U17, 17, RCMF) profiles as an elite playmaking midfielder with outstanding creativity, progression and ball retention. He ranks among the league leaders for progressive passes, assists, second assists, xA and passing quality, while also contributing significant goal threat through shots and goals. His combination of chance creation, technical security and forward-thinking distribution makes him one of the most complete midfielders in the Swiss U17 Elite.

LGE	Player	Team	Position	Age	Min	Score
U19	E. Ndjoko	Servette U19	LCMF, LDMF	18	2215	100.00
U19	M. Hodza	Zürich U19	LCMF, RCMF, LWF	19	2234	87.93
U19	A. Smajic	Luzern U19	RCMF, RAMF	17	739	86.40
U19	M. Maia Valente	Neuchâtel Xamax U19	RCMF, CF	18	1588	82.86
U19	K. Pinto Da Silva	Winterthur U19	RCMF, LCMF	19	1072	74.74
U19	Simao Vieira	Grasshopper U19	LCMF, LWF, RCMF	19	1124	73.67

E. Ndjoko (Servette U19, 18, LCMF) profiles as a dynamic two-way midfielder with exceptional ball progression and strong all-around contribution. He ranks among the league leaders for progressive passes, progressive carries, second assists and long passing, while also providing solid defensive output through aerial ability and ball-winning actions. His combination of progression, physical presence and creative support makes him a highly effective box-to-box midfield profile.

Attacking Midfielder

LGE	Player	Team	Position	Age	Min	Score
U17	L. Gigon	Grasshopper U17	AMF, LCMF	17	1090	100.00
U17	J. Henauer	Winterthur U17	LCMF	16	1866	94.67
U17	L. Jäger	FC Aarau U17	AMF, RW, RWF	15	1037	73.59
U17	A. Smajic	Luzern U17	RCMF, DMF, RDMF	17	1227	66.08
U17	V. Costantino	Servette U17	AMF, CF, DMF	15	1349	62.21

L. Gigon (Grasshopper U17, 17, AMF) profiles as an elite attacking playmaker with outstanding creativity, ball progression and goal threat. He ranks among the league leaders for shot assists, assists, second assists, progressive carries, dribbling and touches in the box, while also posting exceptional scoring numbers. His combination of chance creation, ball-carrying ability and attacking output makes him one of the most complete and impactful offensive players in the Swiss U17 Elite.

LGE	Player	Team	Position	Age	Min	Score
U19	D. Sahin	Grasshopper U19	AMF, CF	17	1337	100.00
U19	A. Smajic	Luzern U19	RCMF, RAMF	17	739	97.21
U19	M. Hodza	Zürich U19	LCMF, RCMF, LWF	19	2234	94.29
U19	M. Maia Valente	Neuchâtel Xamax U19	RCMF, CF	18	1588	82.98
U19	P. Muff	Luzern U19	AMF, CF, LCMF	19	1456	78.86
U19	Simao Vieira	Grasshopper U19	LCMF, LWF, RCMF	19	1124	77.00

D. Sahin (Grasshopper U19, 17, AMF) profiles as an elite attacking midfielder with a rare blend of creativity and goal threat. He ranks among the league leaders for npxG, shots, touches in the box, shot assists and smart passes, while also contributing strongly through dribbling and ball progression. His combination of chance creation, attacking presence and end product makes him one of the most complete attacking midfielders in the Swiss U19 Elite.

Winger

LGE	Player	Team	Position	Age	Min	Score
U17	S. Furundzic	Grasshopper U17	LWF, LAMF	16	873	100.00
U17	E. Karrer	Winterthur U17	RWF, RW	17	1374	96.92
U17	H. Samouiller	Lausanne Sport U17	RWF, CF, RW	17	1609	95.34
U17	E. Kurti	Grasshopper U17	RAMF, RWF	17	948	92.36
U17	L. Krasniqi	Grasshopper U17	LAMF, RB, LWF	17	1010	90.46

S. Furundzic (Grasshopper U17, 16, LWF) profiles as a creative winger with outstanding chance creation and ball progression. He ranks among the league leaders for shot assists, second assists, progressive passing and dribbling, while also providing a solid scoring threat through his box presence and npxG. His profile is built around creating opportunities for teammates, progressing attacks and adding dynamism in the final third.

LGE	Player	Team	Position	Age	Min	Score
U19	J. Seyfu	Young Boys U19	RW, RWB, RAMF	18	1294	100.00
U19	M. Kurtishi	Basel U19	LAMF, LW	17	1587	71.51
U19	D. Recica	Winterthur U19	LW, LWF, LAMF	18	1079	71.12
U19	G. Caputo	Luzern U19	LW, LAMF, LWF	18	2079	70.43
U19	N. Gezahegn	Servette U19	LW, RW, LAMF	18	813	65.80

J. Seyfu (Young Boys U19, 18, RW) profiles as an elite goalscoring winger with exceptional attacking output and penalty-box presence. He ranks among the league leaders for npxG, non-penalty goals, shots, touches in the box and finishing efficiency, while also contributing strongly through ball progression, dribbling and chance creation. His combination of directness, goal threat and creative support makes him one of the most dangerous attacking wingers in the Swiss U19 Elite.

Forward

LGE	Player	Team	Position	Age	Min	Score
U17	T. Nunez	Servette U17	CF, LAMF, LWF	16	1151	100.00
U17	N. Gutovic	Luzern U17	CF	16	2036	94.14
U17	N. Cavka	Winterthur U17	CF	16	938	78.66
U17	R. Ukshini	Lausanne Sport U17	CF, LWF	17	1050	71.70
U17	J. Ramos Vogt	Zürich U17	CF	16	1523	68.52
U17	A. Mehmeti	Grasshopper U17	CF, RAMF	17	1087	67.78

T. Nunez (Servette U17, 16, CF) profiles as an elite attacking and chance-creation forward. He combines outstanding goal threat with exceptional ball-carrying ability, ranking among the league leaders for npxG, non-penalty goals, shots, touches in the box, progressive carries, xA and shot assists. His rare blend of scoring output, creativity and dynamism makes him one of the most complete striker profiles in the Swiss U17 Elite.

LGE	Player	Team	Position	Age	Min	Score
U19	H. Zaier	Zürich U19	CF	18	847	100.00
U19	K. Landu	Servette U19	CF	18	1683	94.85
U19	D. Ahmeti	Young Boys U19	CF	18	866	90.56
U19	C. Ilis	Basel U19	CF, AMF	19	1024	88.78
U19	Y. Hansal	Basel U19	CF, RAMF, RW	19	2144	87.88
U19	J. Kramer	Grasshopper U19	CF	18	1016	85.13

H. Zaier (Zürich U19, 18, CF) profiles as an elite penalty-box striker with outstanding scoring efficiency and aerial presence. He ranks among the league leaders for npxG, non-penalty goals, shots, touches in the box and finishing efficiency, consistently generating high-quality scoring opportunities. While his creative and progression metrics are more limited, his profile is built around attacking the box, winning aerial duels and converting chances at an elite level.

Here is our interpretation guide for the player radars

U17 Best Performer per Position Profile

Position Profile	Player	Team	Age
Goalkeeper	H. Fehr	Winterthur U17	16
Defensive CB	A. Kubli	Grasshopper U17	16
Progressive CB	G. Mihajlovski	Servette U17	17
Inverted CB	G. Mihajlovski	Servette U17	17
Defensive FB	A. Kubli	Grasshopper U17	16
Progressive FB	E. Bajraktar	Young Boys U17	17
Inverted FB	L. Zimmermann	Luzern U17	16
Defensive MF	D. Heiniger	Basel U17	17
Number 6	J. Bakambo	Neuchâtel Xamax U17	16
Possession Enabler	A. Smajic	Luzern U17	17
Deepp Playmaker	A. Smajic	Luzern U17	17
Progressive MF	A. Smajic	Luzern U17	17
Box2Box MF	A. Smajic	Luzern U17	17
Adv. Playmaker	J. Henauer	Winterthur U17	16
Classic CAM	J. Henauer	Winterthur U17	16
Wide CAM	J. Henauer	Winterthur U17	16
2nd Striker CAM	L. Gigon	Grasshopper U17	17
Inverted Winger	E. Kurti	Grasshopper U17	17
Playmaking Winger	L. Krasniqi	Grasshopper U17	17
Inside Forward Winger	E. Karrer	Winterthur U17	17
Traditional Winger	P. Babaja	Zürich U17	16
Advanced Striker	T. Nunez	Servette U17	16
Targetman CF	N. Gutovic	Luzern U17	16
Deeplying Striker	T. Nunez	Servette U17	16
Playmaking Striker	L. Bajraj	Luzern U17	16
Linkup Striker	L. Bajraj	Luzern U17	16

U19 Best Performer per Position Profile

Position Profile	Player	Team	Age
Goalkeeper	T. Pinthus-Duah	Zürich U19	17
Defensive CB	J. Kurmann	Luzern U19	19
Progressive CB	G. Ajdin	Basel U19	19
Inverted CB	Y. Ramdane	Servette U19	18
Defensive FB	V. Beck	Zürich U19	19
Progressive FB	V. Beck	Zürich U19	19
Inverted FB	T. Goll	Grasshopper U19	18
Defensive MF	K. Pinto Da Silva	Winterthur U19	19
Number 6	Y. Odin	Winterthur U19	17
Possession Enabler	Y. Odin	Winterthur U19	17
Deepp Playmaker	A. Smajic	Luzern U19	17
Progressive MF	E. Ndjoko	Servette U19	18
Box2Box MF	E. Ndjoko	Servette U19	18
Adv. Playmaker	D. Sahin	Grasshopper U19	17
Classic CAM	D. Sahin	Grasshopper U19	17
Wide CAM	A. Smajic	Luzern U19	17
2nd Striker CAM	D. Sahin	Grasshopper U19	17
Inverted Winger	J. Seyfu	Young Boys U19	18
Playmaking Winger	L. Mota Campos	Zürich U19	18
Inside Forward Winger	J. Seyfu	Young Boys U19	18
Traditional Winger	J. Seyfu	Young Boys U19	18
Advanced Striker	H. Zaier	Zürich U19	18
Targetman CF	J. Kramer	Grasshopper U19	18
Deeplying Striker	C. Ilis	Basel U19	19
Playmaking Striker	G. van der Sluis	Young Boys U19	17
Linkup Striker	Y. Hansal	Basel U19	19

Finally, we will examine various charts and analyses to demonstrate how different metrics can provide valuable insights into the performance and development of players and teams.

Position Profile Score

The major advantage of these role profiles is that they assess not only how good a player is, but also which role he is best suited to.

In the case of Josiah Seyfu, the analysis clearly shows that his greatest strengths lie as an inside forward/winger and an inverted winger. In these positions, he achieves the maximum score of 100, making him an ideal fit for roles that require dynamism, a drive towards goal and finishing ability. As a classic winger or playmaking winger, his rating is lower because his profile is less geared towards width, crossing or creative playmaking.

The benefit for clubs: players can be deployed, developed and recruited in a more targeted manner. Rather than simply searching for positions such as ‘right wing’, it becomes clear which specific role within that position is the best fit. This reduces the number of unsuccessful transfers, improves squad planning and helps to identify hidden potential at an early stage.

The benefit for agencies: players can be positioned more precisely according to their real strengths and the profiles clubs are actively looking for. Instead of presenting a player only by position, agencies can show which specific role suits them best, how they compare to similar players and where their market potential is highest. This strengthens player representation, improves club matching and supports more convincing negotiations.

Attacking Performer

This chart highlights the top attacking performers across several key offensive metrics. Each column represents a different attacking action, while every dot represents a player.

Pass Danger Index

The Passing Danger Index (PDI) is a creativity index that highlights which players create a particularly high level of attacking threat through their passing. The index combines smart passes (line-breaking), passes into the penalty area, key passes and shot assists. All figures are adjusted for player possession to ensure that players from different teams can be compared fairly. This highlights creative talents who are often underestimated in traditional scouting metrics.

Best U17 4-2-3-1 Eleven

This graphic shows a data-driven U17 Elite 2025/26 selection in a formation specific 4-2-3-1 . For each tactical role, the top four players are ranked based on footballytics' position-specific profiles. The score shows how strongly a player matches the requirements of that role, with 100 being the league benchmark.

Team Possession & Pressing

The chart shows the playing styles of the Swiss U19 elite teams in terms of possession and pressing intensity. A lower PPDA indicates higher pressing intensity.

FC Zurich is the clearest example of a possession and pressing team, with high ball possession and high pressing intensity. YB, Lucerne and Winterthur also adopt a very active style with above-average ball possession and strong pressing. Team Ticino represents a clear transition and counter-attacking approach with low ball possession and lower pressing intensity.

Team Expected Goals and Expected Goals Against

Goals are relatively rare events in football and can be heavily influenced by randomness, individual mistakes, refereeing decisions or exceptional finishing.

Expected Goals (xG) and Expected Goals Against (xGA) provide a more reliable measure of team performance because they evaluate the quality of chances created and conceded rather than the final score alone.

Tracking xG and xGA over time helps identify underlying performance trends and provides a better indication of a team's development, consistency and long-term potential.

The graph shows Winterthur U19’s xG and xGA on a 4-match rolling average.

Winterthur had a difficult start, with xGA above xG. From the middle of the season, performance improved clearly. xG increased, xGA dropped and the team created better chances than it conceded.

The strongest phase was around matches 18-23, where Winterthur had a clear positive gap between xG and xGA.

Winterthur U19 showed strong development during the season. After a weak start, the team became more dominant and controlled games better. The final matches showed a small decline in attacking output, but overall the trend was positive.

Team Playing Style and Performance Radar

The graph introduces the TeamRadar, a data-driven framework that makes team playing styles and performance visible through intuitive visual profiles. Built on key metrics across five tactical clusters — General (possession, PPDA, passing rhythm, long balls), Attacking (goals, xG, shots, box presence), Passing (final-third passes, % of forward passes, accuracy, crosses), Defense (conceded goals, shots against, duels, aerial duels) and Efficiency (shot-ending attacks, counterattacks and set-piece effectiveness).

The model translates raw data into percentile scores, enabling fair comparisons across teams. By combining style and performance in a single visualisation, the TeamRadar helps coaches, analysts, scouts and decision-makers understand team identity, benchmark tactical approaches and uncover strengths, weaknesses and development opportunities. As examples Basel and Zürich U19

Basel U19 are one of the league's most dangerous attacking teams, ranking among the top sides for goals, xG and touches in the box. Their strength lies in turning possession into chances, as reflected by elite efficiency scores in positional attacks, set pieces and corners. While their defensive and pressing numbers are more average, Basel's success is driven primarily by their ability to create and convert scoring opportunities.

Zürich U19 combine the league's strongest possession game with aggressive pressing, ranking first for possession and among the best teams for high pressing. Their attacking profile is equally impressive, leading the league in xG while maintaining strong shot volume and penalty-box presence. Defensively, Zürich concede very few goals and allow few shots, making them one of the most complete and dominant teams in the Swiss U19 Elite.

League Expected Points

This chart compares each team's actual points with their expected points (xP). Expected points are calculated from match performance data and estimate how many points a team should have earned based on the quality of chances (xG) and overall performances.

Teams above their xP have been more efficient than expected, while teams below their xP may have been unlucky or less effective in key moments.

Basel U19 are the biggest overperformers. Basel collected 11.3 more points than expected, suggesting exceptional efficiency in converting performances into results.

Lausanne Sport U19 and Zürich U19 also exceeded expectations. Lausanne Sport (+10.8) and Zürich (+6.7) significantly outperformed their xP, indicating strong finishing, game management or decisive moments.

Young Boys U19, Sion U19 and Servette U19 underperformed the most. Young Boys (-7.4), Sion (-7.0) and Servette (-6.5) earned considerably fewer points than their performances suggested, indicating potential bad luck or inefficiency in key situations.

Team Squad Composition Analysis

The squad composition analysis shows how the squad is structured according to specific role profiles. This highlights which players perform particularly well in their optimal roles and where there are still gaps in the squad. Here is an example: FC Zurich U19

and Champions League winners PSG.

The benefit for clubs is that transfers, squad planning and player development become much more precise. Instead of simply searching by position, clubs can specifically scout for players who fit the desired role and playing style.

Data analysis transforms large amounts of data into actionable insights and provides a deeper understanding of player and team performance. It helps clubs and agencies evaluate players objectively, identify strengths and development areas and benchmark players against their peers. By positioning players relative to league and position, data creates transparency and supports better recruitment, player development, career planning and decision-making.

footballytics combines deep tactical expertise, data analytics and innovative thinking to turn complex football challenges into effective solutions. Through data scouting, match analysis and tactical player coaching, we help clubs, agencies and players make better decisions, identify opportunities and maximise performance.

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footballytics – we know how to make the data talk

We support clubs, coaches, agencies and players by providing analysis and consultancy services to help them utilise and interpret data. This enables them to make better decisions in scouting, match analysis and on the pitch.

Work with a partner, not just a platform.

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www.footballytics.ch 

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