Andrey Mendel

31 yrs · Defensive midfielder · Russia
FK Baltika · Premier Liga · Foot: right · Height: 186 cm
Risk: Very HighConfidence: LowSample: LowDevelopment: LowContract: until 30 Jun 2027
Market value
€900k
Updated 7 days ago
Estimated acquisition
€203k – €724k
Estimated · 20–80% range
Model value
€406k – €1.1M
Performance-implied · estimated
Projected (24m)
€309k – €732k
Resale range · estimated
Potential value gap
-€318k – €870k
Model value − acquisition

Value picture

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

Estimated acquisition€203k – €724k
Model value (performance-implied)€406k – €1.1M
Projected value (24 months)€309k – €732k
Dashed line: current market value (€900k). Bars are 20–80% model ranges; tick = median.

The model rates Andrey Mendel's performance-implied value at EUR 0.4M-1.1M, above the estimated acquisition range of EUR 0.2M-0.7M. Its 24-month market value projection is EUR 0.3M-0.7M. Context-adjusted goal contributions are 0.54x the positional average in the league (787 minutes, league coefficient 0.56). Confidence is low: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.

Acquisition note: Final year of contract: selling club's leverage is reduced.

Bargain Index: not assigned

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

Insufficient sample (< 900 league minutes)

PerformanceBelow average14.4th pct among MID peers (age-neutral)
AgeUnfavorable31.2 years
Acquisition costVery favorableest. €271k vs market €900k
Expected appreciationVery low-48% over ~2 years (model)
Value gapLargeweak predictor on its own
DevelopmentLow
League translationModerateleague coefficient 0.56
Tactical fitNot evaluatedRequires event/role data not available from the current free source.
RiskVery High
Data confidenceLow

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: €1.0M

Profile vs positional peers

Percentiles among 1164 evaluated MID players with 900+ minutes.

Performance (last season, league)

Minutes
787 (29% of available)
Goals + assists / 90
0.00
Context-adjusted G+A / 90
0.07
xG, xA, progression
Data unavailable
Defensive actions
Data unavailable
Performance percentile
14 (Below 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
0.56 (rank 10)
Team strength (Elo)
1326
Opponent strength
1386
Possession, role
Data unavailable

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

Potential

Development
Low
Trajectory
insufficient
Breakout probability
Age > 23
Resale range (24m)
€309k – €732k

Historical comparables (8): median 2-year value change -35% (IQR -45% to -15%).

Risk profile

Overall: Very High

  • ▲Small sample: 787 league minutes last season.
  • ⚠League level coefficient 0.56 (1.00 = big-five average): output may not translate.
  • ⚠No continental-competition minutes last season.
  • ⚠League level estimated mainly from squad values (few matches vs other leagues).
  • ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
  • ⚠Age 31: resale value typically declines.
  • ⚠Played under 40% of available league minutes (injury data unavailable, cause unknown).
  • ⓘ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).

Historical movers
18 (MID)
Relative output kept
54%–153%
Held a regular role (900+ min)
56%
Confidence
Low

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.
2025/26FK BaltikaPremier LigaDM1578729%000.000.07138613260.56
2023/24Fakel VoronezhPremier LigaDM15117143%010.080.10131012440.49
2022/23Fakel VoronezhPremier LigaDM26139352%100.060.10132012390.53

Cups & continental competitions

SeasonCompetitionClubAppsMinGAAvg opp. Elo
2025/26Russian CupFK Baltika215010—
2023/24Russian CupFakel Voronezh315800—
2022/23Russian CupFakel Voronezh19000—

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
Semedo
Liga Portugal · 2017
29€800k€50kfell
Steven Defour
Jupiler Pro League · 2021
33€900k€900kflat
Aleksey Pomerko
Premier Liga · 2020
30€550k€275kfell
Gertjan De Mets
Jupiler Pro League · 2018
31€500k€300kfell
Steven De Petter
Jupiler Pro League · 2015
30€700k€500kfell
Matthieu Debisschop
Jupiler Pro League · 2013
29€400k€400kflat
Pierrick Valdivia
Jupiler Pro League · 2017
29€750k€600kfell
Tayfur Bingöl
Super Lig · 2024
31€700k€400kfell

Transfer history

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

DateFromToFeeMV at time
8 Sept 2024Fakel VoronezhBaltikaFree / loan€500k
1 Jul 2021VolgarFakel VoronezhFree / loan€300k
1 Jul 2020KhimkiVolgarFree / loan€350k
30 Jun 2020VolgarKhimkiFree / loan€350k
21 Feb 2020KhimkiVolgarFree / loan€450k
1 Jul 2019Chernomorets N.KhimkiFree / loan€200k
13 Jul 2018Afips AfipskiyChernomorets N.Free / loan€100k
1 Jul 2016Chernomorets N.Afips AfipskiyFree / loanData unavailable
25 Feb 2016Druzhba MaikopChernomorets N.Free / loanData unavailable
27 Jul 2015Torpedo ArmavirDruzhba MaikopUnknownData unavailable
12 Aug 2014BiologTorpedo ArmavirUnknownData unavailable
1 Aug 2013Kuban U19BiologUnknownData 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.

Andrey Mendel · MoneyballAI