FairValue

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  • EnvironmentOverviewWhat FairValue measures, what it found, where to go next.
  • EnvironmentTerminalExplore, compare and track players; market, league and model views.
  • EnvironmentStoriesValuations, head-to-heads and research findings, told as stories.
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Valuation story

Inside a valuation: Jean-Clair Todibo

From the model's €2.2M starting point to €16.5M, one input at a time, and where that lands against an observed €22M.

Built from Published SHAP output for the served Model A (reports/explainability); the player was in its training data.10 chapters

Observed €22MModel A €16.5M (served, in-sample)Premier League · Centre-Back

Portrait of Jean-Clair Todibo

Jean-Clair

Todibo

CB

№ 605184Elite €15.7M +0.34

Image: FootyLogos · image credits

The valuation

Jean-Clair Todibo: 26, centre-back in Premier League. Transfermarkt's valuation is €22M, in the Elite tier. This story follows how Model A arrives at its own figure, one input at a time.

Where every estimate starts

Before it looks at this player, Model A sits at €2.2M: its average output across the players it was trained on. Every player's journey starts here. Each input then multiplies the estimate up or down.

League

League (Premier League, England) raises the estimate ×6.33: from €2.2M to €13.8M.

Across all modelled players this input moves Model A's estimate by ×1.96 on average, in one direction or the other. Here it moves it more than usual.

Club points per game

Club points per game (1.03) lowers the estimate ×0.75: from €13.8M to €10.3M.

Across all modelled players this input moves Model A's estimate by ×1.38 on average, in one direction or the other. Here it moves it less than usual.

Age

Age (26.4 yrs) raises the estimate ×1.32: from €10.3M to €13.6M.

Across all modelled players this input moves Model A's estimate by ×1.60 on average, in one direction or the other. Here it moves it less than usual.

Minutes (2 years)

Minutes (2 years) (3,903) raises the estimate ×1.11: from €13.6M to €15.1M.

Across all modelled players this input moves Model A's estimate by ×1.07 on average, in one direction or the other. Here it moves it more than usual.

European-cup minute share

European-cup minute share (0%) lowers the estimate ×0.90: from €15.1M to €13.6M.

Across all modelled players this input moves Model A's estimate by ×1.20 on average, in one direction or the other. Here it moves it less than usual.

Everything else

The remaining 15 inputs are individually small. Together they raise the estimate ×1.21, to €16.5M.

The estimate

After all 20 inputs, Model A says €16.5M. Transfermarkt says €22M. The residual, log(observed) − log(estimate), is +0.289: the observed value is above the estimate, so the model under-predicts by ×1.33.

The served model was trained on this player, so this is an in-sample figure; on unseen players a typical miss is ×1.50.

What this is not

SHAP describes the model's arithmetic for these inputs. It is not a price, a scouting judgement or a statement about what causes value, and the order of the steps is by size, not sequence.

The same record, with Model B and the player's traits, is in the dossier.

Starting point€2.2Mobserved €22M

Every Model A valuation starts at €2.2M, the model's average output over the players it was trained on (log 14.592).

raises the estimate lowers it Model A estimate observed value (dashed line)Log scale: equal lengths are equal multiplications. Inputs are ordered by size of effect, not in any causal sequence. Published SHAP run for the served Model A; this player was in its training data.