
Bryan Reynolds
Value picture
Where the market, the likely price and the model estimates sit.
The model rates Bryan Reynolds's performance-implied value at EUR 1.2M-3.4M, below the estimated acquisition range of EUR 1.5M-4.2M. Its 24-month market value projection is EUR 1.8M-4.3M. Confidence is medium: no event-level data (xG, progressive actions) is available from the current free source, and injury history is unavailable.
Bargain Index: 33
What drives the score. Not a black box: each component and its level.
| Performance | Average | 50.7th pct among DEF peers (age-neutral) |
| Age | Neutral | 25 years |
| Acquisition cost | Favorable | est. €2.9M vs market €3.5M |
| Expected appreciation | Very low | -27% over ~2 years (model) |
| Value gap | Negative | weak predictor on its own |
| Development | Moderate | |
| League translation | Moderate | league coefficient 0.65 |
| Tactical fit | Not evaluated | Requires event/role data not available from the current free source. |
| Risk | Moderate | |
| Data confidence | Medium |
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.
Profile vs positional peers
Percentiles among 1268 evaluated DEF players with 900+ minutes.
Performance (last season, league)
- Minutes
- 2594 (96% of available)
- Goals + assists / 90
- 0.10
- Context-adjusted G+A / 90
- 0.10
- xG, xA, progression
- Data unavailable
- Defensive actions
- Data unavailable
- Performance percentile
- 51 (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
- 0.65 (rank 6)
- Team strength (Elo)
- 1348
- Opponent strength
- 1385
- Possession, role
- Data unavailable
League strength 1.00 = average club of the big-five leagues. Elo includes continental matches.
Potential
- Development
- Moderate
- Trajectory
- declining
- Breakout probability
- Age > 23
- Resale range (24m)
- €1.8M – €4.3M
Trajectory drivers: relative output down 51% vs positional peers.
Historical comparables (8): median 2-year value change -37% (IQR -52% to +11%).
Risk profile
Overall: Moderate
- ⚠No continental-competition 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).
- Historical movers
- 76 (DEF)
- Relative output kept
- 67%–160%
- Held a regular role (900+ min)
- 76%
- 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.
| Season | Club | League | Pos | Apps | Min | Min share | G | A | G+A/90 | Adj. G+A/90 | Opp. Elo | Team Elo | League str. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025/26 | KVC Westerlo | Jupiler Pro League | RB | 29 | 2594 | 96% | 2 | 1 | 0.10 | 0.10 | 1385 | 1348 | 0.65 |
| 2024/25 | KVC Westerlo | Jupiler Pro League | RB | 27 | 2369 | 88% | 1 | 4 | 0.19 | 0.20 | 1368 | 1322 | 0.63 |
| 2023/24 | KVC Westerlo | Jupiler Pro League | RB | 27 | 2358 | 87% | 0 | 4 | 0.15 | 0.15 | 1397 | 1293 | 0.63 |
| 2022/23 | KVC Westerlo | Jupiler Pro League | RB | 27 | 2080 | 68% | 1 | 5 | 0.26 | 0.19 | 1325 | 1333 | 0.58 |
| 2021/22 | KV Kortrijk | Jupiler Pro League | RB | 9 | 679 | 22% | 1 | 0 | 0.13 | 0.13 | 1357 | 1208 | 0.49 |
| 2021/22 | Associazione Sportiva Roma | Serie A | RB | 1 | 1 | 0% | 0 | 0 | 0.00 | 0.11 | 1506 | 1589 | 0.89 |
| 2020/21 | Associazione Sportiva Roma | Serie A | RM | 5 | 285 | 8% | 0 | 0 | 0.00 | 0.10 | 1338 | 1591 | 0.90 |
Cups & continental competitions
| Season | Competition | Club | Apps | Min | G | A | Avg opp. Elo |
|---|---|---|---|---|---|---|---|
| 2025/26 | Jupiler Pro League Europe Play Offs | KVC Westerlo | 10 | 900 | 0 | 3 | 1365 |
| 2021/22 | Uefa Conference League Qualifying | Associazione Sportiva Roma | 1 | 1 | 0 | 0 | 1388 |
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) | Age | Value then | ~2y later | Outcome |
|---|---|---|---|---|
| Jesper Daland Jupiler Pro League · 2024 | 24 | €4.5M | €2.5M | fell |
| Toni Borevković Liga Portugal · 2021 | 24 | €3.0M | €1.0M | fell |
| Jan-Arie van der Heijden Eredivisie · 2014 | 26 | €3.5M | €2.5M | fell |
| Sébastien Dewaest Jupiler Pro League · 2016 | 25 | €4.0M | €2.0M | fell |
| Ümit Kurt Super Lig · 2015 | 24 | €2.4M | €1.0M | fell |
| Bruno Onyemaechi Liga Portugal · 2023 | 24 | €2.5M | €2.7M | flat |
| Bruno Uvini Eredivisie · 2016 | 25 | €1.5M | €1.8M | rose |
| Maksim Belyaev Premier Liga · 2018 | 27 | €2.6M | €3.5M | rose |
Transfer history
Fees as reported by the source; undisclosed fees shown as unknown, never estimated.
| Date | From | To | Fee | MV at time |
|---|---|---|---|---|
| 30 Jul 2023 | Roma | KVC Westerlo | €3.3M | €4.0M |
| 30 Jun 2023 | KVC Westerlo | Roma | Free / loan | €4.0M |
| 1 Jul 2022 | Roma | KVC Westerlo | Free / loan | €3.5M |
| 30 Jun 2022 | KV Kortrijk | Roma | Free / loan | €3.5M |
| 23 Jan 2022 | Roma | KV Kortrijk | Free / loan | €4.0M |
| 1 Jul 2021 | Dallas | Roma | €6.8M | €6.0M |
| 30 Jun 2021 | Roma | Dallas | Free / loan | €6.0M |
| 1 Feb 2021 | Dallas | Roma | Free / loan | €6.0M |
| 30 Nov 2019 | North Texas SC | Dallas | Free / loan | €250k |
| 29 Mar 2019 | Dallas | North Texas SC | Free / loan | €50k |
| 22 Nov 2016 | Dallas Academy | Dallas | Unknown | Data 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.