Best Strikers in the Serie A (Oct 2025)
Ranked by Analytical Strength Score
Market Overview: Serie A Strikers 2023-24
Our database tracked 70 Serie A Strikers in the 2023-24 season, representing 21 clubs with a combined market value of €980.9M. The average market value for Serie A Strikers was €14.0M, with the average age at 26.8 years old.
The most valuable striker in the Serie A was Lautaro Martínez, worth €85.0M and played for Inter Milan at 28 years old. The top 5 Strikers averaged €60.0M in market value, including Marcus Thuram and Moise Kean.
Age distribution showed the youngest tracked striker was Jeff Ekhator (18 years, Genoa CFC, €7.0M), while the oldest was Edin Džeko (39 years, ACF Fiorentina, €1.6M). Research shows Strikers typically peak at age 26.
Historical analysis showed 35 Strikers (50%) 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 Strikers remained highly competitive with significant transfer activity in the 2023-24 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.
Explore Market Size by Position in Serie A
Interactive bubble chart showing predicted 2-year growth vs current age for all Serie A Strikers. Identify undervalued assets and track market momentum across 21 clubs with €980.9M combined value.
Age Distribution: Serie A Strikers
The Serie A ST market shows 5 distinct age segments, with the largest cohort in the 27-29 bracket (21 players, 30% of market). The 27-29 age group holds the most value at €366.5M, averaging €17.5M per player.
Top Strikers by Age Bracket
U21 Years (4 players)
21-23 Years (12 players)
24-26 Years (19 players)
27-29 Years (21 players)
Market Value Distribution
Elite Tier Concentration
The top 7 Strikers (10% of players) control €385.0M
Market Tiers
Market structure shows distributed value with elite (€50m+) tier representing 4% of the Serie A ST pool.
Elite (€50M+)
Premium (€30-50M)
High (€15-30M)
Club Distribution: Serie A Strikers
Among 21 Serie A clubs, Inter Milan leads with 3 Strikers worth €183.0M (averaging €61.0M per player). The top 10 clubs account for 50% of tracked Strikers.
Inter Milan (3 Strikers)
Juventus FC (4 Strikers)
SSC Napoli (4 Strikers)
ACF Fiorentina (5 Strikers)
Player Rankings
Ranked by APE Strength Score. Click any player to view full profile, or click the chart icon to see value history.
Lautaro Martínez
Inter Milan • 28 years old
€85.0M
€85.0M
+0.0%
Expected: €83.9M
92.2
Marcus Thuram
Inter Milan • 28 years old
€75.0M
€75.0M
+0.0%
Expected: €74.1M
91.2
Moise Kean
ACF Fiorentina • 25 years old
€43.2M
€50.0M
+15.6%
Expected: €55.2M
87.6
Jonathan David
Juventus FC • 25 years old
€38.9M
€45.0M
+15.6%
Expected: €49.6M
86.3
Loïs Openda
Juventus FC • 25 years old
€38.9M
€45.0M
+15.6%
Expected: €49.6M
86.3
Rasmus Højlund
SSC Napoli • 22 years old
€38.9M
€45.0M
+15.6%
Expected: €56.7M
85.2
Ademola Lookman
Atalanta BC • 27 years old
€40.0M
€40.0M
+0.0%
Expected: €39.5M
84.1
Dušan Vlahović
Juventus FC • 25 years old
€30.3M
€35.0M
+15.6%
Expected: €38.6M
83.2
Christopher Nkunku
AC Milan • 27 years old
€35.0M
€35.0M
+0.0%
Expected: €34.6M
82.5
Santiago Castro
Bologna FC 1909 • 21 years old
€30.3M
€35.0M
+15.6%
Expected: €46.0M
81.0
Lorenzo Lucca
SSC Napoli • 25 years old
€25.9M
€30.0M
+15.6%
Expected: €31.8M
77.7
Santiago Gimenez
AC Milan • 24 years old
€21.6M
€25.0M
+15.6%
Expected: €27.8M
75.4
Gianluca Scamacca
Atalanta BC • 26 years old
€20.8M
€24.0M
+15.6%
Expected: €24.7M
74.9
Nikola Krstović
Atalanta BC • 25 years old
€20.8M
€24.0M
+15.6%
Expected: €25.4M
74.9
Taty Castellanos
SS Lazio • 27 years old
€25.0M
€25.0M
+0.0%
Expected: €23.7M
74.7
Artem Dovbyk
AS Roma • 28 years old
€25.0M
€25.0M
+0.0%
Expected: €23.7M
73.9
Roberto Piccoli
ACF Fiorentina • 24 years old
€17.3M
€20.0M
+15.6%
Expected: €22.2M
72.6
Ange-Yoan Bonny
Inter Milan • 21 years old
€19.9M
€23.0M
+15.6%
Expected: €29.0M
72.2
Evan Ferguson
AS Roma • 20 years old
€21.6M
€25.0M
+15.6%
Expected: €32.8M
72.1
Albert Gudmundsson
ACF Fiorentina • 28 years old
€18.0M
€18.0M
+0.0%
Expected: €17.1M
69.9
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)
SSC Napoli's Rasmus Højlund at 22 years old has the highest Pre-Peak Value Efficiency at 6.00×. That means Rasmus Højlund is valued 6.00× higher than the median player in the 21-23 age bracket—representing exceptional value before reaching peak age.
In second is Bologna FC 1909's Santiago Castro, who is 21 years old, with a 4.67× PPVE. Third is Ange-Yoan Bonny of Inter Milan, who is 21 years old with a 3.07× 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 6.00× means the player is worth 500% more than typical players their age—making them high-value targets before they reach peak value.
PPVE by Age Bracket
| Rank | Player | Age | Bracket | Current Value | Bracket Median | PPVE |
|---|---|---|---|---|---|---|
| #1 | Rasmus Højlund SSC Napoli | 22 | 21-23 | €45.0M | €7.5M | 6.00× |
| #2 | Santiago Castro Bologna FC 1909 | 21 | 21-23 | €35.0M | €7.5M | 4.67× |
| #3 | Ange-Yoan Bonny Inter Milan | 21 | 21-23 | €23.0M | €7.5M | 3.07× |
| #4 | Moise Kean ACF Fiorentina | 25 | 24-26 | €50.0M | €20.0M | 2.50× |
| #5 | Loïs Openda Juventus FC | 25 | 24-26 | €45.0M | €20.0M | 2.25× |
| #6 | Jonathan David Juventus FC | 25 | 24-26 | €45.0M | €20.0M | 2.25× |
| #7 | Evan Ferguson AS Roma | 20 | U21 | €25.0M | €12.0M | 2.08× |
| #8 | Dušan Vlahović Juventus FC | 25 | 24-26 | €35.0M | €20.0M | 1.75× |
| #9 | Lorenzo Lucca SSC Napoli | 25 | 24-26 | €30.0M | €20.0M | 1.50× |
| #10 | Gift Orban Hellas Verona | 23 | 21-23 | €10.0M | €7.5M | 1.33× |
| #11 | Santiago Gimenez AC Milan | 24 | 24-26 | €25.0M | €20.0M | 1.25× |
| #12 | Nikola Krstović Atalanta BC | 25 | 24-26 | €24.0M | €20.0M | 1.20× |
| #13 | Sebastiano Esposito Cagliari Calcio | 23 | 21-23 | €8.5M | €7.5M | 1.13× |
| #14 | Roberto Piccoli ACF Fiorentina | 24 | 24-26 | €20.0M | €20.0M | 1.00× |
| #15 | Matija Frigan Parma Calcio 1913 | 22 | 21-23 | €7.5M | €7.5M | 1.00× |
| #16 | Semih Kılıçsoy Cagliari Calcio | 20 | U21 | €12.0M | €12.0M | 1.00× |
| #17 | Mateo Pellegrino Parma Calcio 1913 | 23 | 21-23 | €6.0M | €7.5M | 0.80× |
| #18 | Lorenzo Colombo Genoa CFC | 23 | 21-23 | €5.0M | €7.5M | 0.67× |
| #19 | Zito Luvumbo Cagliari Calcio | 23 | 21-23 | €5.0M | €7.5M | 0.67× |
| #20 | Thijs Dallinga Bologna FC 1909 | 25 | 24-26 | €12.0M | €20.0M | 0.60× |
Return-to-Peak Potential (RPP)
Recovery potential from current value to forecasted peak. Shows how much upside remains for players approaching their prime.
No RPP data available (requires forecast values in database)
Risk-Adjusted Upside (RAU)
Upside potential weighted against forecast uncertainty. Higher RAU = better risk-reward profile.
Understanding Risk-Adjusted Upside (RAU)
Genoa CFC's Jeff Ekhator has the highest Risk-Adjusted Upside at 105.9. That means Jeff Ekhator has 41% upside potential with only 0% forecast uncertainty—representing excellent risk-reward for value appreciation.
In second is Bologna FC 1909's Santiago Castro with a 86.4 RAU (31% upside, 0% uncertainty). Third is Evan Ferguson of AS Roma with a 86.2 RAU (31% upside, 0% uncertainty).
How RAU is calculated: RAU divides upside potential by forecast uncertainty (RAU = Upside % ÷ Uncertainty %). A RAU of 105.9 means the upside is 105.9× greater than the uncertainty—making it a high-confidence growth opportunity. Target RAU ≥2.0 for balanced risk-reward.
Risk-Adjusted Upside by Player
| Rank | Player | Expected | Range | Upside % | RAU |
|---|---|---|---|---|---|
| #1 | Jeff Ekhator Genoa CFC | €9.9M | €8.5M-11.3M | +41% | 105.9 |
| #2 | Santiago Castro Bologna FC 1909 | €46.0M | €39.6M-52.3M | +31% | 86.4 |
| #3 | Evan Ferguson AS Roma | €32.8M | €28.3M-37.3M | +31% | 86.2 |
| #4 | Iker Bravo Udinese Calcio | €3.9M | €3.4M-4.5M | +31% | 86.2 |
| #5 | Semih Kılıçsoy Cagliari Calcio | €15.7M | €13.6M-17.9M | +31% | 86.2 |
| #6 | Rasmus Højlund SSC Napoli | €56.7M | €49.9M-63.5M | +26% | 86.2 |
| #7 | Ange-Yoan Bonny Inter Milan | €29.0M | €25.0M-33.0M | +26% | 75.2 |
| #8 | Junior Ajayi Hellas Verona | €379K | €326K-431K | +26% | 75.2 |
| #9 | Giuseppe Ambrosino SSC Napoli | €3.0M | €2.7M-3.4M | +21% | 72.7 |
| #10 | Matija Frigan Parma Calcio 1913 | €9.1M | €8.0M-10.2M | +21% | 72.7 |
| #11 | Gift Orban Hellas Verona | €11.6M | €10.2M-13.0M | +16% | 57.7 |
| #12 | Lorenzo Colombo Genoa CFC | €5.8M | €5.1M-6.5M | +16% | 57.7 |
| #13 | Zito Luvumbo Cagliari Calcio | €5.8M | €5.1M-6.5M | +16% | 57.7 |
| #14 | Sebastiano Esposito Cagliari Calcio | €9.9M | €8.7M-11.1M | +16% | 57.7 |
| #15 | Laurs Skjellerup US Sassuolo | €3.3M | €2.9M-3.6M | +16% | 57.7 |
| #16 | Mateo Pellegrino Parma Calcio 1913 | €7.0M | €6.1M-7.8M | +16% | 57.7 |
| #17 | Amin Sarr Hellas Verona | €4.2M | €3.7M-4.7M | +11% | 41.4 |
| #18 | Santiago Gimenez AC Milan | €27.8M | €24.4M-31.1M | +11% | 41.4 |
| #19 | Luca Moro US Sassuolo | €2.2M | €2.0M-2.5M | +11% | 41.4 |
| #20 | Roberto Piccoli ACF Fiorentina | €22.2M | €19.5M-24.9M | +11% | 41.4 |
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: striker position shows strong depth (avg Z-score: 0.00). RPI: 0.00.
Position Depth Analysis
Highest Z-Scores
Lowest Z-Scores
Age-Share Concentration (ASC)
Identifies players capturing disproportionate value relative to age group representation. Positive ASC = value concentration.
Understanding Age-Share Concentration (ASC)
Bologna FC 1909's Ciro Immobile in the 30+ age bracket has the highest Age-Share Concentration at +-14.5%. That means Romelu Lukaku captures 5.5% of total market value while representing only 20.0% of players in their age group—showing dominant elite status.
In second is Como 1907's Álvaro Morata with a +-14.5% ASC (5.5% value share vs 20.0% player share in 30+ bracket). Third is Andrea Belotti of Cagliari Calcio with a +-14.5% ASC (5.5% value vs 20.0% players in 30+ bracket).
How ASC is calculated: ASC = (% of total value) - (% of total players) in age bracket. A +-14.5% ASC means the player captures -14.5% more market value than their numerical representation—indicating marquee status. ASC > +15% = elite dominance, ASC < -15% = potential value targets.
Value Concentration by Player
| Rank | Player | Age Bracket | Value Share | Player Share | ASC |
|---|---|---|---|---|---|
| #1 | Ciro Immobile Bologna FC 1909 | 30+ | 5.5% | 20.0% | -14.5% |
| #2 | Álvaro Morata Como 1907 | 30+ | 5.5% | 20.0% | -14.5% |
| #3 | Andrea Belotti Cagliari Calcio | 30+ | 5.5% | 20.0% | -14.5% |
| #4 | Arkadiusz Milik Juventus FC | 30+ | 5.5% | 20.0% | -14.5% |
| #5 | Jamie Vardy US Cremonese | 30+ | 5.5% | 20.0% | -14.5% |
| #6 | Caleb Ekuban Genoa CFC | 30+ | 5.5% | 20.0% | -14.5% |
| #7 | Paulo Dybala AS Roma | 30+ | 5.5% | 20.0% | -14.5% |
| #8 | Giovanni Simeone Torino FC | 30+ | 5.5% | 20.0% | -14.5% |
| #9 | Edin Džeko ACF Fiorentina | 30+ | 5.5% | 20.0% | -14.5% |
| #10 | Mario Balotelli Without Club | 30+ | 5.5% | 20.0% | -14.5% |
| #11 | Leonardo Pavoletti Cagliari Calcio | 30+ | 5.5% | 20.0% | -14.5% |
| #12 | Milan Djuric Parma Calcio 1913 | 30+ | 5.5% | 20.0% | -14.5% |
| #13 | Duván Zapata Torino FC | 30+ | 5.5% | 20.0% | -14.5% |
| #14 | Romelu Lukaku SSC Napoli | 30+ | 5.5% | 20.0% | -14.5% |
| #15 | Andrea Pinamonti US Sassuolo | 24-26 | 37.0% | 27.1% | +9.8% |
| #16 | Gianluca Scamacca Atalanta BC | 24-26 | 37.0% | 27.1% | +9.8% |
| #17 | Dušan Vlahović Juventus FC | 24-26 | 37.0% | 27.1% | +9.8% |
| #18 | Moise Kean ACF Fiorentina | 24-26 | 37.0% | 27.1% | +9.8% |
| #19 | Loïs Openda Juventus FC | 24-26 | 37.0% | 27.1% | +9.8% |
| #20 | Roberto Piccoli ACF Fiorentina | 24-26 | 37.0% | 27.1% | +9.8% |
Buy-Now vs Wait-List Map
Categorizes players by age position and upside potential to guide timing of acquisition.
What This Shows
How to use: "Buy Now - High Upside" = immediate priority targets. "Watch List" = monitor for 6-12 months. "Peak" = pay premium for proven performers. "Aging" = short-term depth only.
Current market: 16 immediate targets, 16 standard acquisitions, 0 watch-list prospects, 19 at peak.
BUY NOW - High Upside
WATCH LIST - High Upside
No players in this category
BUY NOW - Medium Upside
PEAK Players
Price vs Peer Z-Score
IQR-based pricing analysis relative to position peers. Identifies over/undervalued players vs market.
What This Shows
How to use: Z-score < -1.5 = significantly undervalued (potential bargain). Z-score > +1.5 = premium pricing (requires strong justification). Within ±1.0 = fair market value.
Current market: Position median is €85.0M. 4 undervalued, 3 premium.
Value Positioning vs Peers
| Player | Market Value | Position Median | Z-Score | Assessment |
|---|---|---|---|---|
Alberto Cerri Como 1907 | €700K | €6.0M | -2.25 | Undervalued |
Andrea Pinamonti US Sassuolo | €15.0M | €6.0M | -2.25 | Undervalued |
Federico Bonazzoli US Cremonese | €1.0M | €6.0M | -1.88 | Undervalued |
Mario Balotelli Without Club | €500K | €6.0M | -1.67 | Undervalued |
Lorenzo Lucca SSC Napoli | €30.0M | €6.0M | -1.50 | Good Value |
Boulaye Dia SS Lazio | €15.0M | €6.0M | -1.43 | Good Value |
Leonardo Pavoletti Cagliari Calcio | €700K | €6.0M | -1.33 | Good Value |
Albert Gudmundsson ACF Fiorentina | €18.0M | €6.0M | -1.00 | Good Value |
Marcus Thuram Inter Milan | €75.0M | €6.0M | -1.00 | Good Value |
Christopher Nkunku AC Milan | €35.0M | €6.0M | -1.00 | Good Value |
Dušan Vlahović Juventus FC | €35.0M | €6.0M | -1.00 | Good Value |
Roberto Piccoli ACF Fiorentina | €20.0M | €6.0M | -1.00 | Good Value |
Santiago Castro Bologna FC 1909 | €35.0M | €6.0M | -1.00 | Good Value |
Jeff Ekhator Genoa CFC | €7.0M | €6.0M | -1.00 | Good Value |
Junior Ajayi Hellas Verona | €300K | €6.0M | -0.88 | Good Value |
Jamie Vardy US Cremonese | €1.0M | €6.0M | -0.83 | Good Value |
Lorenzo Colombo Genoa CFC | €5.0M | €6.0M | -0.71 | Good Value |
Zito Luvumbo Cagliari Calcio | €5.0M | €6.0M | -0.71 | Good Value |
Manuel De Luca US Cremonese | €2.0M | €6.0M | -0.63 | Good Value |
David Okereke US Cremonese | €2.0M | €6.0M | -0.63 | Good Value |