Best Attacking Midfielders in the Serie A (Jun 2026)

Ranked by Analytical Strength Score

Market Overview: Serie A Attacking Midfielders 2022-23

Our database tracked 32 Serie A Attacking Midfielders in the 2022-23 season, representing 17 clubs with a combined market value of €336.7M. The average market value for Serie A Attacking Midfielders was €10.5M, with the average age at 24.8 years old.

The most valuable attacking midfielder in the Serie A was Nico Paz, worth €65.0M and played for Como 1907 at 21 years old. The top 5 Attacking Midfielders averaged €31.6M in market value, including Charles De Ketelaere and Teun Koopmeiners.

Age distribution showed the youngest tracked attacking midfielder was Darryl Bakola (18 years, US Sassuolo, €4.0M), while the oldest was Kevin De Bruyne (34 years, SSC Napoli, €15.0M). Research shows Attacking Midfielders typically peak at age 26.

Historical analysis showed 22 Attacking Midfielders (69%) increased in market value over the following 12 months based on age-curve trajectories, then-current performance trends, and playing time analysis. The Serie A market for Attacking Midfielders remained actively developing with emerging talent in the 2022-23 season.

💡 Use the search bar below to find specific players, or apply filters to narrow results by club, age range, or market value. Click the chart icon next to any player to view their historical value trajectory and forecast.

Market Intelligence

Explore Market Size by Position in Serie A

Interactive bubble chart showing predicted 2-year growth vs current age for all Serie A Attacking Midfielders. Identify undervalued assets and track market momentum across 17 clubs with €336.7M combined value.

Players Tracked

By League

Premier League La Liga Bundesliga Serie A Ligue 1

By Position

GK CB LB RB CDM

More Positions

CM CAM LW RW ST

By Season

2025-26 2024-25 2023-24 2022-23

Age Distribution: Serie A Attacking Midfielders

The Serie A CAM market shows 5 distinct age segments, with the largest cohort in the 24-26 bracket (11 players, 34% of market). The 24-26 age group holds the most value at €114.0M, averaging €10.4M per player.

U21 years4 players (13%)

€26.5MAvg: €6.6M

Top player: Vasilije Adžić (€8.0M)

21-23 years8 players (25%)

€108.8MAvg: €13.6M

Top player: Nico Paz (€65.0M)

24-26 years11 players (34%)

€114.0MAvg: €10.4M

Top player: Charles De Ketelaere (€35.0M)

27-29 years7 players (22%)

€69.9MAvg: €10.0M

Top player: Teun Koopmeiners (€28.0M)

30+ years2 players (6%)

€17.5MAvg: €8.8M

Top player: Kevin De Bruyne (€15.0M)

Top Attacking Midfielders by Age Bracket

U21 Years (4 players)

1. Vasilije Adžić(20yo)

€8.0M

2. Lorran(19yo)

€7.5M

3. Adrian Przyborek(19yo)

€7.0M

4. Darryl Bakola(18yo)

€4.0M

21-23 Years (8 players)

1. Nico Paz(21yo)

€65.0M

2. Tommaso Baldanzi(23yo)

€10.0M

3. Giovanni Fabbian(23yo)

€10.0M

4. Cristian Volpato(22yo)

€10.0M

5. Gaetano Oristanio(23yo)

€6.0M

24-26 Years (11 players)

1. Charles De Ketelaere(25yo)

€35.0M

2. Lazar Samardžić(24yo)

€15.0M

3. Eljif Elmas(26yo)

€14.0M

4. Nicolò Zaniolo(26yo)

€13.0M

5. Daniel Maldini(24yo)

€8.0M

27-29 Years (7 players)

1. Teun Koopmeiners(28yo)

€28.0M

2. Jens Odgaard(27yo)

€15.0M

3. Lorenzo Pellegrini(29yo)

€9.0M

4. Nikola Vlašić(28yo)

€9.0M

5. Calvin Stengs(27yo)

€6.0M

Market Value Distribution

Elite Tier Concentration

42%of market value

The top 4 Attacking Midfielders (13% of players) control €143.0M

1. Nico Paz€65.0M

2. Charles De Ketelaere€35.0M

3. Teun Koopmeiners€28.0M

4. Lazar Samardžić€15.0M

Market Tiers

Elite (€50M+)1 players (3%)

€65.0M

Premium (€30-50M)1 players (3%)

€35.0M

High (€15-30M)4 players (13%)

€73.0M

Mid (€5-15M)18 players (56%)

€145.0M

Emerging (<€5M)8 players (25%)

€18.7M

Market structure shows distributed value with elite (€50m+) tier representing 3% of the Serie A CAM pool.

Elite (€50M+)

1. Nico Paz

Como 1907€65.0M

Premium (€30-50M)

1. Charles De Ketelaere

Atalanta BC€35.0M

High (€15-30M)

1. Teun Koopmeiners

Juventus FC€28.0M

2. Lazar Samardžić

Atalanta BC€15.0M

3. Kevin De Bruyne

SSC Napoli€15.0M

4. Jens Odgaard

Bologna FC 1909€15.0M

Club Distribution: Serie A Attacking Midfielders

Among 17 Serie A clubs, Como 1907 leads with 1 Attacking Midfielders worth €65.0M (averaging €65.0M per player). The top 10 clubs account for 63% of tracked Attacking Midfielders.

Como 1907

1 players • €65.0M

Atalanta BC

2 players • €50.0M

Juventus FC

2 players • €36.0M

SSC Napoli

3 players • €31.5M

SS Lazio

3 players • €21.5M

Pisa Sporting Club

3 players • €19.5M

Bologna FC 1909

1 players • €15.0M

US Sassuolo

2 players • €14.0M

Torino FC

2 players • €14.0M

#10

Udinese Calcio

1 players • €13.0M

Como 1907 (1 Attacking Midfielders)

Nico Paz(21yo)

€65.0M

Atalanta BC (2 Attacking Midfielders)

Charles De Ketelaere(25yo)

€35.0M

Lazar Samardžić(24yo)

€15.0M

Juventus FC (2 Attacking Midfielders)

Teun Koopmeiners(28yo)

€28.0M

Vasilije Adžić(20yo)

€8.0M

SSC Napoli (3 Attacking Midfielders)

Kevin De Bruyne(34yo)

€15.0M

Eljif Elmas(26yo)

€14.0M

Antonio Vergara(23yo)

€2.5M

Player Rankings

Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.

Nico Paz

Como 1907 • 21 years old

€56.2M

€65.0M

+15.6%

€61.7M€87.5M

Expected: €74.6M

90.0

Charles De Ketelaere

Atalanta BC • 25 years old

€30.3M

€35.0M

+15.6%

€30.3M€41.0M

Expected: €35.6M

82.8

Teun Koopmeiners

Juventus FC • 28 years old

€36.2M

€28.0M

-22.6%

€21.6M€29.2M

Expected: €25.4M

76.6

Lazar Samardžić

Atalanta BC • 24 years old

€13.0M

€15.0M

+15.6%

€13.6M€18.4M

Expected: €16.0M

69.9

Kevin De Bruyne

SSC Napoli • 34 years old

€19.4M

€15.0M

-22.6%

€11.2M€15.9M

Expected: €13.6M

69.2

Jens Odgaard

Bologna FC 1909 • 27 years old

€15.9M

€15.0M

-5.4%

€11.6M€15.6M

Expected: €13.6M

69.0

Eljif Elmas

SSC Napoli • 26 years old

€12.1M

€14.0M

+15.6%

€12.8M€17.3M

Expected: €15.0M

68.1

Nicolò Zaniolo

Udinese Calcio • 26 years old

€11.2M

€13.0M

+15.6%

€11.8M€16.0M

Expected: €13.9M

67.2

#10

Tommaso Baldanzi

Genoa CFC • 23 years old

€8.6M

€10.0M

+15.6%

€9.1M€12.3M

Expected: €10.7M

61.6

Giovanni Fabbian

ACF Fiorentina • 23 years old

€8.6M

€10.0M

+15.6%

€9.1M€12.3M

Expected: €10.7M

61.6

#11

Cristian Volpato

US Sassuolo • 22 years old

€8.6M

€10.0M

+15.6%

€9.0M€12.2M

Expected: €10.6M

61.0

#12

Lorenzo Pellegrini

AS Roma • 29 years old

€11.6M

€9.0M

-22.6%

€6.3M€8.5M

Expected: €7.4M

59.0

#13

Nikola Vlašić

Torino FC • 28 years old

€11.6M

€9.0M

-22.6%

€6.7M€9.0M

Expected: €7.8M

59.0

#14

Daniel Maldini

SS Lazio • 24 years old

€6.9M

€8.0M

+15.6%

€7.0M€9.4M

Expected: €8.2M

58.4

#15

Vasilije Adžić

Juventus FC • 20 years old

€6.9M

€8.0M

+15.6%

€7.6M€10.8M

Expected: €9.2M

57.0

#16

Lorran

Pisa Sporting Club • 19 years old

€6.5M

€7.5M

+15.6%

€7.4M€10.5M

Expected: €8.9M

55.6

#17

Fisayo Dele-Bashiru

SS Lazio • 25 years old

€5.6M

€6.5M

+15.6%

€5.4M€7.3M

Expected: €6.4M

55.4

#18

Gaetano Oristanio

Parma Calcio 1913 • 23 years old

€5.2M

€6.0M

+15.6%

€5.5M€7.4M

Expected: €6.4M

55.4

#19

Adrian Przyborek

SS Lazio • 19 years old

€6.1M

€7.0M

+15.6%

€6.9M€9.8M

Expected: €8.3M

54.8

#20

Calvin Stengs

Pisa Sporting Club • 27 years old

€6.3M

€6.0M

-5.4%

€4.4M€6.0M

Expected: €5.2M

54.0

Showing 1-20 of 32

Scout Tools

Advanced analytics for scouting and recruitment decisions. Each tool provides unique insights into player value, potential, and market dynamics.

Pre-Peak Value Efficiency (PPVE)

Identifies pre-peak players offering exceptional value relative to their age bracket. Higher PPVE = better value.

Understanding Pre-Peak Value Efficiency (PPVE)

Como 1907's Nico Paz at 21 years old has the highest Pre-Peak Value Efficiency at 6.50×. That means Nico Paz is valued 6.50× higher than the median player in the 21-23 age bracket—representing exceptional value before reaching peak age.

In second is Atalanta BC's Charles De Ketelaere, who is 25 years old, with a 4.38× PPVE. Third is Lazar Samardžić of Atalanta BC, who is 24 years old with a 1.88× PPVE.

How PPVE is calculated: PPVE compares a player's current market value to the median value of all players in their age bracket. A PPVE of 6.50× means the player is worth 550% more than typical players their age—making them high-value targets before they reach peak value.

PPVE by Age Bracket

Nico PazComo 1907

21-23 • 21yo6.50×

€65.0M • 550% above median

Charles De KetelaereAtalanta BC

24-26 • 25yo4.38×

€35.0M • 338% above median

Lazar SamardžićAtalanta BC

24-26 • 24yo1.88×

€15.0M • 88% above median

Vasilije AdžićJuventus FC

U21 • 20yo1.07×

€8.0M • 7% above median

LorranPisa Sporting Club

U21 • 19yo1.00×

€7.5M • 0% above median

Daniel MaldiniSS Lazio

24-26 • 24yo1.00×

€8.0M • 0% above median

Giovanni FabbianACF Fiorentina

21-23 • 23yo1.00×

€10.0M • 0% above median

Tommaso BaldanziGenoa CFC

21-23 • 23yo1.00×

€10.0M • 0% above median

Cristian VolpatoUS Sassuolo

21-23 • 22yo1.00×

€10.0M • 0% above median

Adrian PrzyborekSS Lazio

U21 • 19yo0.93×

€7.0M • -7% above median

Fisayo Dele-BashiruSS Lazio

24-26 • 25yo0.81×

€6.5M • -19% above median

Tino AnjorinTorino FC

24-26 • 24yo0.63×

€5.0M • -38% above median

Gaetano OristanioParma Calcio 1913

21-23 • 23yo0.60×

€6.0M • -40% above median

Darryl BakolaUS Sassuolo

U21 • 18yo0.53×

€4.0M • -47% above median

Tomas SuslovHellas Verona

21-23 • 23yo0.50×

€5.0M • -50% above median

Rank	Player	Age	Bracket	Current Value	Bracket Median	PPVE
#1	Nico Paz Como 1907	21	21-23	€65.0M	€10.0M	6.50×
#2	Charles De Ketelaere Atalanta BC	25	24-26	€35.0M	€8.0M	4.38×
#3	Lazar Samardžić Atalanta BC	24	24-26	€15.0M	€8.0M	1.88×
#4	Vasilije Adžić Juventus FC	20	U21	€8.0M	€7.5M	1.07×
#5	Lorran Pisa Sporting Club	19	U21	€7.5M	€7.5M	1.00×
#6	Daniel Maldini SS Lazio	24	24-26	€8.0M	€8.0M	1.00×
#7	Giovanni Fabbian ACF Fiorentina	23	21-23	€10.0M	€10.0M	1.00×
#8	Tommaso Baldanzi Genoa CFC	23	21-23	€10.0M	€10.0M	1.00×
#9	Cristian Volpato US Sassuolo	22	21-23	€10.0M	€10.0M	1.00×
#10	Adrian Przyborek SS Lazio	19	U21	€7.0M	€7.5M	0.93×
#11	Fisayo Dele-Bashiru SS Lazio	25	24-26	€6.5M	€8.0M	0.81×
#12	Tino Anjorin Torino FC	24	24-26	€5.0M	€8.0M	0.63×
#13	Gaetano Oristanio Parma Calcio 1913	23	21-23	€6.0M	€10.0M	0.60×
#14	Darryl Bakola US Sassuolo	18	U21	€4.0M	€7.5M	0.53×
#15	Tomas Suslov Hellas Verona	23	21-23	€5.0M	€10.0M	0.50×
#16	Filip Marchwinski US Lecce	24	24-26	€2.5M	€8.0M	0.31×
#17	Antonio Vergara SSC Napoli	23	21-23	€2.5M	€10.0M	0.25×
#18	Hugo Cuenca Genoa CFC	21	21-23	€300K	€10.0M	0.03×

Return-to-Peak Potential (RPP)

Recovery potential from current value to forecasted peak. Shows how much upside remains for players approaching their prime.

Understanding Return-to-Peak Potential (RPP)

US Sassuolo's Darryl Bakola at 18 years old has the highest Return-to-Peak Potential at +44%. That means Darryl Bakola is projected to appreciate 44% as they reach their peak age in 8 years—representing significant upside before entering their prime.

In second is Pisa Sporting Club's Lorran, who is 19 years old, with a +40% RPP (7 years to peak). Third is Adrian Przyborek of SS Lazio, who is 19 years old with a +40% RPP (7 years to peak).

How RPP is calculated: RPP compares a player's current market value to their forecasted peak value, calculating the percentage appreciation potential. A 44% RPP means the player is expected to gain 44% value as they enter their prime—making them excellent growth investments.

Recovery Potential by Player

Darryl BakolaUS Sassuolo

8yr to peak+44%

€4.0M → €7.1M

LorranPisa Sporting Club

7yr to peak+40%

€7.5M → €12.5M

Adrian PrzyborekSS Lazio

7yr to peak+40%

€7.0M → €11.6M

Vasilije AdžićJuventus FC

6yr to peak+35%

€8.0M → €12.4M

Hugo CuencaGenoa CFC

5yr to peak+30%

€300K → €431K

Nico PazComo 1907

5yr to peak+30%

€65.0M → €93.4M

Cristian VolpatoUS Sassuolo

4yr to peak+25%

€10.0M → €13.4M

Gaetano OristanioParma Calcio 1913

3yr to peak+20%

€6.0M → €7.5M

Tomas SuslovHellas Verona

3yr to peak+20%

€5.0M → €6.2M

Giovanni FabbianACF Fiorentina

3yr to peak+20%

€10.0M → €12.4M

Tommaso BaldanziGenoa CFC

3yr to peak+20%

€10.0M → €12.4M

Antonio VergaraSSC Napoli

3yr to peak+20%

€2.5M → €3.1M

Tino AnjorinTorino FC

2yr to peak+14%

€5.0M → €5.8M

Daniel MaldiniSS Lazio

2yr to peak+14%

€8.0M → €9.2M

Filip MarchwinskiUS Lecce

2yr to peak+14%

€2.5M → €2.9M

Rank	Player	Age	Years to Peak	Current	Peak Forecast	RPP %
#1	Darryl Bakola US Sassuolo	18	8	€4.0M	€7.1M	+44%
#2	Lorran Pisa Sporting Club	19	7	€7.5M	€12.5M	+40%
#3	Adrian Przyborek SS Lazio	19	7	€7.0M	€11.6M	+40%
#4	Vasilije Adžić Juventus FC	20	6	€8.0M	€12.4M	+35%
#5	Hugo Cuenca Genoa CFC	21	5	€300K	€431K	+30%
#6	Nico Paz Como 1907	21	5	€65.0M	€93.4M	+30%
#7	Cristian Volpato US Sassuolo	22	4	€10.0M	€13.4M	+25%
#8	Gaetano Oristanio Parma Calcio 1913	23	3	€6.0M	€7.5M	+20%
#9	Tomas Suslov Hellas Verona	23	3	€5.0M	€6.2M	+20%
#10	Giovanni Fabbian ACF Fiorentina	23	3	€10.0M	€12.4M	+20%
#11	Tommaso Baldanzi Genoa CFC	23	3	€10.0M	€12.4M	+20%
#12	Antonio Vergara SSC Napoli	23	3	€2.5M	€3.1M	+20%
#13	Tino Anjorin Torino FC	24	2	€5.0M	€5.8M	+14%
#14	Daniel Maldini SS Lazio	24	2	€8.0M	€9.2M	+14%
#15	Filip Marchwinski US Lecce	24	2	€2.5M	€2.9M	+14%
#16	Lazar Samardžić Atalanta BC	24	2	€15.0M	€17.3M	+14%
#17	Fisayo Dele-Bashiru SS Lazio	25	1	€6.5M	€7.0M	+7%
#18	Charles De Ketelaere Atalanta BC	25	1	€35.0M	€37.6M	+7%

Risk-Adjusted Upside (RAU)

Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.

Understanding Risk-Adjusted Upside (RAU)

US Sassuolo's Darryl Bakola has the highest Risk-Adjusted Upside at 55.1. That means Darryl Bakola has 23% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.

In second is SS Lazio's Adrian Przyborek with a 46.4 RAU (19% upside, 0% uncertainty). Third is Lorran of Pisa Sporting Club with a 46.4 RAU (19% upside, 0% uncertainty).

How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 55.1 means the upside is 55.1× greater than the uncertainty—making it a high-confidence growth opportunity. Target RAU ≥2.0 for balanced risk-reward.

Risk-Adjusted Upside by Player

Darryl BakolaUS Sassuolo

↑23% / ±0%55.1

Range: €4.1M - €5.8M

Adrian PrzyborekSS Lazio

↑19% / ±0%46.4

Range: €6.9M - €9.8M

LorranPisa Sporting Club

↑19% / ±0%46.4

Range: €7.4M - €10.5M

Nico PazComo 1907

↑15% / ±0%37.3

Range: €61.7M - €87.5M

Vasilije AdžićJuventus FC

↑15% / ±0%37.1

Range: €7.6M - €10.8M

Hugo CuencaGenoa CFC

↑10% / ±0%26.9

Range: €274K - €388K

Nicolò ZanioloUdinese Calcio

↑7% / ±0%22.3

Range: €11.8M - €16.0M

Eljif ElmasSSC Napoli

↑7% / ±0%22.3

Range: €12.8M - €17.3M

Tomas SuslovHellas Verona

↑7% / ±0%22.0

Range: €4.6M - €6.2M

Giovanni FabbianACF Fiorentina

↑7% / ±0%22.0

Range: €9.1M - €12.3M

Tommaso BaldanziGenoa CFC

↑7% / ±0%22.0

Range: €9.1M - €12.3M

Antonio VergaraSSC Napoli

↑7% / ±0%22.0

Range: €2.3M - €3.1M

Gaetano OristanioParma Calcio 1913

↑7% / ±0%22.0

Range: €5.5M - €7.4M

Lazar SamardžićAtalanta BC

↑7% / ±0%20.6

Range: €13.6M - €18.4M

Cristian VolpatoUS Sassuolo

↑6% / ±0%18.4

Range: €9.0M - €12.2M

Rank	Player	Expected	Range	Upside %	RAU
#1	Darryl Bakola US Sassuolo	€4.9M	€4.1M-5.8M	+23%	55.1
#2	Adrian Przyborek SS Lazio	€8.3M	€6.9M-9.8M	+19%	46.4
#3	Lorran Pisa Sporting Club	€8.9M	€7.4M-10.5M	+19%	46.4
#4	Nico Paz Como 1907	€74.6M	€61.7M-87.5M	+15%	37.3
#5	Vasilije Adžić Juventus FC	€9.2M	€7.6M-10.8M	+15%	37.1
#6	Hugo Cuenca Genoa CFC	€331K	€274K-388K	+10%	26.9
#7	Nicolò Zaniolo Udinese Calcio	€13.9M	€11.8M-16.0M	+7%	22.3
#8	Eljif Elmas SSC Napoli	€15.0M	€12.8M-17.3M	+7%	22.3
#9	Tomas Suslov Hellas Verona	€5.4M	€4.6M-6.2M	+7%	22.0
#10	Giovanni Fabbian ACF Fiorentina	€10.7M	€9.1M-12.3M	+7%	22.0
#11	Tommaso Baldanzi Genoa CFC	€10.7M	€9.1M-12.3M	+7%	22.0
#12	Antonio Vergara SSC Napoli	€2.7M	€2.3M-3.1M	+7%	22.0
#13	Gaetano Oristanio Parma Calcio 1913	€6.4M	€5.5M-7.4M	+7%	22.0
#14	Lazar Samardžić Atalanta BC	€16.0M	€13.6M-18.4M	+7%	20.6
#15	Cristian Volpato US Sassuolo	€10.6M	€9.0M-12.2M	+6%	18.4
#16	Omri Gandelman US Lecce	€5.1M	€4.4M-5.9M	+3%	9.6
#17	Gianluca Gaetano Cagliari Calcio	€4.1M	€3.5M-4.7M	+3%	9.6
#18	Matteo Tramoni Pisa Sporting Club	€6.2M	€5.3M-7.1M	+3%	9.6
#19	Daniel Maldini SS Lazio	€8.2M	€7.0M-9.4M	+2%	7.8
#20	Tino Anjorin Torino FC	€5.1M	€4.4M-5.9M	+2%	7.8

Roster Pressure Index (RPI)

Squad depth pressure based on Z-score distribution. Negative RPI = thin depth, positive = deep roster.

What This Shows

Z-Score explained: Measures how many standard deviations a player's strength is from the position average. Z-Score = 0 means average, +1.0 is one standard deviation above average, -1.0 is below average.

How to use: RPI < -1.0 indicates critical depth shortage. These positions need immediate reinforcement. RPI > +1.0 suggests strong depth, allowing selective, high-value additions only.

Current market: attacking midfielder position shows strong depth (avg Z-score: 0.00). RPI: 0.00.

Position Depth Analysis

Total Players

0.00

Avg Z-Score

0.00

RPI Score

Weak DepthStrong Depth

-3.00+3.0

Highest Z-Scores

Nico Paz+4.49

Charles De Ketelaere+2.02

Teun Koopmeiners+1.44

Lazar Samardžić+0.37

Kevin De Bruyne+0.37

Lowest Z-Scores

Hugo Cuenca-0.84

Grigoris Kastanos-0.75

Abdelhamid Sabiri-0.74

Ruslan Malinovskyi-0.66

Filip Marchwinski-0.66

Age-Share Concentration (ASC)

Identifies players capturing disproportionate value relative to age group representation. Positive ASC = value concentration.

Understanding Age-Share Concentration (ASC)

Hellas Verona's Tomas Suslov in the 21-23 age bracket has the highest Age-Share Concentration at +7.3%. That means Nico Paz captures 32.3% of total market value while representing only 25.0% of players in their age group—showing dominant elite status.

In second is Parma Calcio 1913's Gaetano Oristanio with a +7.3% ASC (32.3% value share vs 25.0% player share in 21-23 bracket). Third is Giovanni Fabbian of ACF Fiorentina with a +7.3% ASC (32.3% value vs 25.0% players in 21-23 bracket).

How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +7.3% ASC means the player captures 7.3% more market value than their numerical representation—indicating marquee status. ASC > +15% = elite dominance, ASC < -15% = potential value targets.