Hans Nicolussi Caviglia

26 yrs · Defensive midfielder (also CM) · Italy
ACF Fiorentina · Serie A · Foot: right · Height: 184 cm
Risk: ModerateConfidence: MediumSample: MediumDevelopment: LowContract: until 30 Jun 2030
Market value
€6.0M
Updated 7 days ago
Estimated acquisition
€2.8M – €6.8M
Estimated · 20–80% range
Model value
€2.5M – €5.2M
Performance-implied · estimated
Projected (24m)
€2.8M – €6.7M
Resale range · estimated
Potential value gap
-€4.2M – €2.3M
Model value − acquisition

Value picture

Where the market, the likely price and the model estimates sit.

Estimated acquisition€2.8M – €6.8M
Model value (performance-implied)€2.5M – €5.2M
Projected value (24 months)€2.8M – €6.7M
Dashed line: current market value (€6.0M). Bars are 20–80% model ranges; tick = median.

The model rates Hans Nicolussi Caviglia's performance-implied value at EUR 2.5M-5.2M, below the estimated acquisition range of EUR 2.8M-6.8M. Its 24-month market value projection is EUR 2.8M-6.7M. Context-adjusted goal contributions are 2.08x the positional average in the league (1458 minutes, league coefficient 0.93). Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.

Bargain Index: 26

What drives the score. Not a black box: each component and its level.

PerformanceAbove average58.4th pct among MID peers (age-neutral)
AgeNeutral26 years
Acquisition costNeutralest. €5.2M vs market €6.0M
Expected appreciationVery low-29% over ~2 years (model)
Value gapNegativeweak predictor on its own
DevelopmentLow
League translationBig-five leagueleague coefficient 0.93
Tactical fitNot evaluatedRequires event/role data not available from the current free source.
RiskModerate
Data confidenceMedium

Bargain Index = percentile (among all evaluated players) of expected 2-year value relative to estimated cost. See methodology and backtests.

Market value history

Market value ≠ transfer fee ≠ acquisition cost.

Highest recorded: €8.5M

Profile vs positional peers

Percentiles among 1163 evaluated MID players with 900+ minutes.

Performance (last season, league)

Minutes
1458 (43% of available)
Goals + assists / 90
0.25
Context-adjusted G+A / 90
0.34
xG, xA, progression
Data unavailable
Defensive actions
Data unavailable
Performance percentile
58 (Above average)

Adjusted = shrunk toward positional baseline for small samples, corrected for team dominance over opponents, expressed relative to positional peers in the same league.

Context

League strength
0.93 (rank 4)
Team strength (Elo)
1427
Opponent strength
1539
Possession, role
Data unavailable

League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.

Potential

Development
Low
Trajectory
declining
Breakout probability
Age > 23
Resale range (24m)
€2.8M – €6.7M

Trajectory drivers: minutes share down 41 pts; changed club; team strength up (+134 Elo).

Historical comparables (8): median 2-year value change -36% (IQR -55% to -26%).

Risk profile

Overall: Moderate

  • ⚠Limited sample: 1458 league minutes last season.
  • ⚠Declining trajectory versus previous season.
  • ⓘInjury history unavailable from current data source.

League translation

What happened to players who moved from this league to the big-five leagues (observed, not a forecast).

Already playing in a big-five league.

Output is relative to positional peers in each league. Movers are a selected group (clubs buy players who fit), so treat this as context, not a guarantee.

Season-by-season (domestic league)

Context-adjusted values are model outputs.

SeasonClubLeaguePosAppsMinMin shareGAG+A/90Adj. G+A/90Opp. EloTeam EloLeague str.
2025/26Parma Calcio 1913Serie ADM1587326%030.310.34153913740.93
2025/26ACF FiorentinaSerie ADM1158517%010.150.14150915060.93
2024/25Venezia FCSerie ADM35287084%430.220.30150312930.99
2023/24Juventus FCSerie ACM82668%010.340.18148816210.98
2022/23US Salernitana 1919Serie ACM1258517%100.150.28151113790.94

Cups & continental competitions

SeasonCompetitionClubAppsMinGAAvg opp. Elo
2023/24Italy CupJuventus FC29000—
2022/23Italy CupFC Südtirol13700—
2020/21Italy CupParma Calcio 1913217002—

Small continental samples are shown for context only and are not over-weighted.

Historical comparables

Most similar profiles 2+ years ago (same position group) and what happened next. Chosen by similarity only — failures included.

Player (then)AgeValue then~2y laterOutcome
Nikola Moro
Serie A · 2023
25€6.5M€4.5Mfell
Romain Faivre
Ligue 1 · 2023
25€10.0M€6.0Mfell
Lewis Holtby
Bundesliga · 2018
28€2.5M€800kfell
Abdoulaye Touré
Ligue 1 · 2021
27€4.0M€1.3Mfell
Mickaël Malsa
Laliga · 2022
27€3.0M€1.5Mfell
Steven Defour
Premier League · 2017
29€6.0M€5.0Mflat
Flavien Tait
Ligue 1 · 2020
27€4.8M€8.0Mrose
Radosav Petrovic
Super Lig · 2014
25€3.5M€2.5Mfell

Transfer history

Fees as reported by the source; undisclosed fees shown as unknown, never estimated.

DateFromToFeeMV at time
1 Jul 2026VeneziaParma€6.0M€6.0M
30 Jun 2026ParmaVeneziaFree / loan€6.0M
29 Jan 2026VeneziaParmaFree / loan€7.0M
28 Jan 2026FiorentinaVeneziaFree / loan€7.0M
30 Aug 2025VeneziaFiorentinaFree / loan€8.5M
1 Jul 2025JuventusVenezia€4.1M€8.5M
30 Jun 2025VeneziaJuventusFree / loan€8.5M
22 Aug 2024JuventusVeneziaFree / loan€3.0M
1 Jul 2023Juve Next GenJuventusUnknown€2.0M
30 Jun 2023SalernitanaJuve Next GenFree / loan€2.0M
5 Jan 2023Juve Next GenSalernitanaFree / loan€1.8M
4 Jan 2023SüdtirolJuve Next GenFree / loan€1.8M
12 Jul 2022Juve Next GenSüdtirolFree / loan€900k
30 Jun 2021ParmaJuventus U23Free / loan€1.5M
5 Oct 2020Juventus U23ParmaFree / loan€1.5M
31 Aug 2020PerugiaJuventus U23Free / loan€1.5M
2 Sept 2019Juventus U23PerugiaFree / loan€500k
21 Feb 2019Juventus U19Juventus U23UnknownData unavailable
1 Jul 2017Juventus U17Juventus U19UnknownData unavailable
1 Jul 2016Juventus YouthJuventus U17UnknownData unavailable

MoneyballAI identifies statistical opportunities from available data. A player flagged as a potential bargain is not guaranteed to succeed, to transfer, to rise in value, or to generate resale profit. Market values, fees and contracts come from third-party sources; ranges are model estimates with stated confidence.