Karen Khachanov: the fading power hitter who loses to everyone below him
Karen Khachanov has played 198 ATP matches from 2022 to 2025 at a 59.6% overall win rate. He is one of the most paradoxical profiles in the Batch 3 dataset: a Grand Slam win rate of 70.2% over 47 matches (easily his highest surface-specific figure), combined with a declining overall trajectory that reached 46.2% in 2025 — below 50% for the first time in the dataset. Two structural patterns define his profile most clearly: an extraordinary 0–7 deficit against Cerundolo, and a 0–15 combined record against five specific elite opponents.
Key metrics at a glance
| Metric | Value |
|---|---|
| Overall win rate | 59.6% |
| Dataset rank (end of period) | 13 |
| Matches analysed | 198 (2022–2025) |
| Best performance | Grand Slams — 70.2% |
| Worst surface | Hard — 57.1% |
| As market favourite | 74.6% |
| As underdog | 30.8% |
Khachanov's year-by-year record
| Year | Matches | Wins | Win rate |
|---|---|---|---|
| 2022 | 32 | 20 | 62.5% |
| 2023 | 19 | 10 | 52.6% |
| 2024 | 31 | 16 | 51.6% |
| 2025 | 26 | 12 | 46.2% |
Win rate by season, Karen Khachanov, 2022–2025. Source: ATP match data via tennispredictor.net
Four consecutive years of declining win rate — from 62.5% to 46.2% — is the clearest sustained decline in the Batch 3 dataset and one of the most consistent in the full top-20 study. The 2025 figure of 46.2% over 26 matches is the most recent and largest annual sample, making it the primary baseline for current predictions.
The trajectory matters more than the career average: Khachanov's model prediction should be anchored at approximately 48–52%, not the 59.6% career figure. The market continues to price him partly based on ranking (13) rather than his 2024–2025 form windows.
Surface breakdown: Grand Slams is the outlier
| Surface | Matches | Win rate |
|---|---|---|
| Grand Slam | 47 | 70.2% |
| Indoors | 19 | 63.2% |
| Clay | 59 | 62.7% |
| Grass | 21 | 61.9% |
| Hard | 98 | 57.1% |
Win rate by surface, Karen Khachanov, 2022–2025. Source: ATP match data via tennispredictor.net
Khachanov's Grand Slam win rate (70.2%, 47 matches) is the most striking figure in his profile: 10.6 points above his overall average and the largest GS-vs-overall gap in Batch 3. This reflects a player whose game works well in best-of-five format — his high-kicking serve, powerful first-strike forehand, and ability to raise intensity in long matches have produced strong results at Slams specifically.
The outdoor hard rate (57.1%, 98 matches — the largest surface sample) is 2.5 points below overall, reflecting a hard-court 250 and 500 event profile where he frequently loses in rounds 2–3 against opponents who target his lateral movement.
Clay (62.7%, 59 matches) is 3.1 points above overall — consistent with a power game that transfers better to clay than to indoor or fast outdoor hard.
Round-by-round: QF the soft ceiling
Win rate by round, Karen Khachanov, 2022–2025. Source: ATP match data via tennispredictor.net
| Round | Matches | Win rate |
|---|---|---|
| R1 | 23 | 69.6% |
| R2 | 19 | 57.9% |
| R3 | 14 | 57.1% |
| R16 | 30 | 50.0% |
| QF | 15 | 33.3% |
| SF | 5 | 40.0% |
| Final | 2 | 50.0% |
The QF figure (33.3%, 15 matches) is the most actionable number in Khachanov's round data. He reaches QFs at a reasonable rate, then converts only 33.3% of them — consistent with the H2H data showing that QF opponents at major events are drawn from the elite tier that dominates his record.
The R16 figure (50.0%, 30 matches — the largest round sample) confirms that from the second week onward, Khachanov is functionally a coin-flip regardless of ranking, which means any odds lower than parity at R16 stage represents overvaluation.
H2H against the elite
H2H win rate vs rivals with 2+ meetings, Karen Khachanov, 2022–2025. Source: ATP match data via tennispredictor.net
| Opponent | Record | H2H win rate |
|---|---|---|
| Cerundolo | 0–7 | 0.0% |
| Dimitrov | 0–3 | 0.0% |
| Paul | 0–3 | 0.0% |
| Alcaraz | 0–5 | 0.0% |
| Djokovic | 0–5 | 0.0% |
| Rublev | 1–1 | 50.0% |
| Ruud | 1–1 | 50.0% |
| Zverev | 1–3 | 25.0% |
| Tsitsipas | 1–4 | 20.0% |
| Medvedev | 1–4 | 20.0% |
| Korda | 1–3 | 25.0% |
| Shelton | 0–2 | 0.0% |
| Auger-Aliassime | 1–1 | 50.0% |
Khachanov has zero wins against Cerundolo (0–7), Alcaraz (0–5), Djokovic (0–5), Dimitrov (0–3), Paul (0–3), and Shelton (0–2) in this dataset — a combined 0–25 record across 6 opponents and 25 matches. This is the most extreme concentration of losing H2H records in the full top-20 study. The Cerundolo 0–7 is most relevant for daily betting since both are ranked near each other (13 vs 21); the market prices them at approximate parity, and the H2H says Cerundolo should be the strong favourite every time.
The Tsitsipas (1–4) and Medvedev (1–4) records add to the pattern: Khachanov's power game is consistently solved by players who read his patterns early and return deep.
As market favourite vs underdog
Win rate as market favourite vs underdog, Karen Khachanov, 2022–2025. Raw tournament cache. Source: tennispredictor.net
As favourite (138 matches): 74.6% — adequate conversion, above overall average. As underdog (78 matches): 30.8% — the lowest underdog rate in the full top-20 dataset. When the market identifies Khachanov as inferior to his opponent, he wins fewer than 1 in 3 of those matches. This extreme underdog inefficiency combined with the H2H dominance patterns confirms a player whose game is highly matchup-dependent: dominant against the right opponents, near-helpless against those with strong returns and deep patterns.
What the betting market misses about Khachanov
The Cerundolo edge is massive. 0–7 is the most one-sided H2H record in the dataset, yet the market prices Cerundolo vs Khachanov near parity due to ranking proximity. Back Cerundolo against Khachanov every time the matchup occurs, regardless of event size or surface.
The declining trend is significant and unpriced. 46.2% in 2025 over 26 matches — below 50% — while his snapshot rank remains 13. The gap between his current form and his ranking creates a consistent mispricing where the market overvalues him at ranking-based odds.
The Grand Slam premium is genuinely real. 70.2% at Grand Slams over 47 matches is his one consistently above-average venue. If Khachanov participates in a Slam with a favourable draw (no Cerundolo, Alcaraz, or Djokovic early), his Slam performance has historically outperformed his regular-event results.
How our model treats Khachanov
- 2025 form as primary baseline — 46.2% in 2025 is the most recent large sample; model weights this heavily over the career average
- Grand Slam uplift — 70.2% GS figure triggers an upward adjustment at all four Slams
- Cerundolo, Alcaraz, Djokovic, Paul, Dimitrov — 0 wins across all five in combined 23 matches applied as near-zero probability signals
- Underdog discount — 30.8% underdog rate confirms market accuracy when it already discounts him; model does not attempt to find value there
Frequently asked questions
What is Khachanov's overall win rate?
59.6% across 198 matches from 2022 to 2025. The most relevant current figure is the 2025 rate of 46.2% over 26 matches.
What is his record against Cerundolo?
0–7 — the most extreme positive H2H for Cerundolo in the full dataset, and the single most actionable H2H fade in Batch 3.
Why does Khachanov perform better at Grand Slams?
70.2% over 47 GS matches — 10.6 points above overall. Best-of-five format allows his power game to compound over longer matches, and Slam draws provide more first-week low-ranked opponents than regular ATP events.
When is Khachanov worth backing?
At Grand Slams in rounds 1–3 against opponents outside the top 30, and specifically at Roland Garros (clay 62.7%) and Australian Open (hard, where his GS premium is largest). Fade him against Cerundolo, Alcaraz, Djokovic, Paul, and Dimitrov at any stage, and in R16 or later at any regular ATP event.
What is his underdog win rate?
30.8% — the lowest in the full top-20 dataset. The market is accurate when it identifies Khachanov as inferior; he almost never overcomes that assessment.
Conclusion
Karen Khachanov's profile represents the clearest case in the dataset of a player whose market valuation (ranking 13, former top-10) diverges from his current form reality (46.2% in 2025). The Grand Slam premium and the specific matchup advantages (positive records against Rublev and Auger-Aliassime) provide limited backing opportunities. The betting strategy is structural and clear: fade Khachanov against Cerundolo universally, fade him from R16 stage onward at any event, and note that when the market prices him at ranking-based odds, the 2024–2025 form data strongly argues against it.
For the most extreme H2H advantage over Khachanov, see the Cerundolo analysis where the 7–0 record is analysed from the opposite perspective.
All statistics sourced from ATP match data 2022–2025. ATP Tour events only. Data extracted October 2025.
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