Rasmus Lauritsen

30 yrs · Centre-back · Denmark
Bröndby IF · Superliga · Foot: right · Height: 188 cm
Risk: Very HighConfidence: LowSample: LowDevelopment: LowContract: until 30 Jun 2027
Market value
€1.0M
Updated 6 days ago
Estimated acquisition
€236k – €884k
Estimated · 20–80% range
Model value
€315k – €731k
Performance-implied · estimated
Projected (24m)
€384k – €818k
Resale range · estimated
Potential value gap
-€569k – €495k
Model value − acquisition

Value picture

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

Estimated acquisition€236k – €884k
Model value (performance-implied)€315k – €731k
Projected value (24 months)€384k – €818k
Dashed line: current market value (€1.0M). Bars are 20–80% model ranges; tick = median.

The model rates Rasmus Lauritsen's performance-implied value at EUR 0.3M-0.7M, above the estimated acquisition range of EUR 0.2M-0.9M. Its 24-month market value projection is EUR 0.4M-0.8M. 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 average10.1th pct among DEF peers (age-neutral)
AgeUnfavorable30.3 years
Acquisition costVery favorableest. €314k vs market €1.0M
Expected appreciationVery low-42% over ~2 years (model)
Value gapSmallweak predictor on its own
DevelopmentLow
League translationUncertainleague coefficient 0.47
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: €6.5M

Profile vs positional peers

Percentiles among 1269 evaluated DEF players with 900+ minutes.

Performance (last season, league)

Minutes
720 (36% of available)
Goals + assists / 90
0.13
Context-adjusted G+A / 90
0.08
xG, xA, progression
Data unavailable
Defensive actions
Data unavailable
Performance percentile
10 (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
0.47 (rank 12)
Team strength (Elo)
1336
Opponent strength
1236
Possession, role
Data unavailable

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

Potential

Development
Low
Trajectory
improving
Breakout probability
Age > 23
Resale range (24m)
€384k – €818k

Trajectory drivers: league level up (+45 Elo); relative output up 213% vs positional peers.

Historical comparables (8): median 2-year value change -43% (IQR -59% to -30%).

Risk profile

Overall: Very High

  • ▲Small sample: 720 league minutes last season.
  • ⚠League level coefficient 0.47 (1.00 = big-five average): output may not translate.
  • ⚠Contract ends in 12 months: cheaper, but competition and wage demands likely.
  • ⚠Age 30: 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
24 (DEF)
Relative output kept
60%–139%
Held a regular role (900+ min)
71%
Confidence
Medium

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.
2025/26Bröndby IFSuperligaCB872036%010.130.08123613360.47
2024/25Bröndby IFSuperligaCB1064533%000.000.02121713420.38
2023/24Bröndby IFSuperligaCB1282842%000.000.03127714170.48
2018/19Vejle BoldklubSuperligaCB18151765%200.120.10132411690.44
2015/16FC MidtjyllandSuperligaCB150%000.000.04127114470.53

Cups & continental competitions

SeasonCompetitionClubAppsMinGAAvg opp. Elo
2025/26Uefa Conference League QualifyingBröndby IF4360001451
2024/25Uefa Conference League QualifyingBröndby IF4295001368
2024/25Oddset PokalenBröndby IF322500—
2023/24Oddset PokalenBröndby IF29400—
2022/23Uefa Champions League QualifyingGNK Dinamo Zagreb3270011425
2022/23Uefa Champions LeagueGNK Dinamo Zagreb114001706
2018/19Oddset PokalenVejle Boldklub221000—
2015/16Oddset PokalenSkive IK19000—

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
Oumar Sako
Premier Liga · 2024
28€1.2M€2.5Mrose
Paulinho
Super League 1 · 2021
30€500k€200kfell
Vladimir Volkov
Jupiler Pro League · 2016
30€700k€400kfell
Simon Deli
Super Lig · 2022
31€1.8M€200kfell
Ivo Pinto
Liga Portugal · 2020
30€1.2M€500kfell
Mihály Korhut
Super League 1 · 2019
31€600k€400kfell
Mark Wilson
Scottish Premiership · 2014
30€400k€325kflat
Vegar Hedenstad
Super Lig · 2021
30€800k€450kfell

Transfer history

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

DateFromToFeeMV at time
30 Jan 2023Dinamo ZagrebBröndby IF€2.5M€4.0M
2 Oct 2020NorrköpingDinamo Zagreb€1.9M€1.2M
11 Feb 2019Vejle BKNorrköping€200k€400k
1 Jul 2017Skive IKVejle BKUnknown€200k
6 Jan 2016MidtjyllandSkive IKUnknown€50k
1 Jul 2015Midtjylland U19MidtjyllandUnknownData unavailable
1 Jul 2013FCM YouthMidtjylland U19UnknownData 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.

Rasmus Lauritsen · MoneyballAI