Striker alternatives · Juventus recruitment workbench

This is a reconstructed summer comparison. The window has closed. Listed market moves do not establish that Juventus could have signed the player. Forecasts exclude partial 2026/27 results; costs and availability are separate dated evidence.

859indexed alternatives, including strategies

551shared striker rate baselines

516empirical minutes estimates

11partial numeric cost references

Define the comparison

Job labels describe scenarios, not fitted player types. The stress factor applies equally to selected rates; it is an assumption, not a league-conversion model.

Output and cost

Dark: Kolo Muani · Green: references · Brown: your cost scenario

Horizontal ranges are partial cost scenarios; vertical ranges are empirical stress envelopes. No automatic “good deal” quadrants or efficiency frontier.

Selected alternatives

Alternative	npxG / xA per90	Minutes	Selected output	Annualized partial cost	Full-term partial cost	Budget check

Annualized cost = fee allocation + one year fixed gross wage. Full-term cost = fee + fixed wage × stated years. These exclude unpriced extras and do not describe actual cash paid. Equal low/base/high values mean no published range, not certainty.

Inspect an alternative

Performance history

Test a cost assumption

For unknown Juventus terms, enter your own fee, gross wage and contract duration. This changes only the scenario, not the source evidence. For retention, use incremental future costs; do not recharge sunk acquisition fees.

Fee / signing costs (€m)

LowBaseHigh

Annual fixed gross wage (€m)

LowBaseHigh

Contract years

How much should we trust it?

Retrospective temporal rate checks: 2,396 striker-season pairs, with ≥450 minutes in both seasons. This survivor-based rate test does not validate total contribution or prove a recruitment edge.

Error (RMSE; lower is better)	Shared Marcel baseline	Last season	Prior positional mean
npxG/90	0.126	0.141	0.171
xA/90	0.077	0.088	0.098

Expected minutes are uncertain

The empirical baseline uses prior playing time. It does not know a manager’s selection, future injuries or the precise Juventus role. Validation retains covered zero-minute outcomes, with return events reported separately. Missing history and uncovered outcomes are excluded explicitly, not changed to zero.

Multiplying separately estimated rates and minutes is an output proxy. Their dependence is not modeled; the displayed endpoints are stress scenarios, not a calibrated joint interval.

What is—and is not—comparable

Every numerical forecast targets a full 38-match Serie A opportunity. Performance rates still come from the player’s prior league context. There is no validated adjustment that guarantees those rates at Juventus. npxG and xA are separate components, not an overall striker grade or additive team goals.

Feeder observations retain FotMob definitions and do not enter the Understat projection. Historical recorded positions are not within-match role-minute allocations. Unknown acquisition prices remain unknown; Transfermarkt market values never substitute for fees.

Source timing and closed-window alternatives

Historical files were reconstructed from available snapshots; their original publication vintages are incomplete. This is not a forecast proven to have existed before the transfer decision. Current transfers and contracts require dated evidence because the bulk transfer snapshot is incomplete around deadline day.

Vlahović is a hypothetical renewal comparator. David and Openda are hypothetical retention-before-loan alternatives. The known loan arrangements and unresolved salary-sharing make “keep for free” an unsupported claim.

Reproduce and inspect the evidence

Full comparison CSV · Versioned comparison data · Build report · Deal evidence · Minutes evaluation · Coverage audit · Independent review · Input hashes

Descriptive baselines only. No validated recruitment edge, final grade or monetary Deal Alpha is claimed.