B. Krejcikova vs V. Tomova — prediction
›Ranking: #37 vs #155 (better ranked)
›Recent form: 6/10 in recent matches
›Model 72% vs market 90% → the model sees it as less likely than the odds
The gap between the two players is substantial on paper. Krejcikova's 1780 Elo rating sits 285 points above Tomova's 1495, and the ranking difference (#37 versus #155) reinforces that this is a mismatch in overall level. Her 63% baseline win rate, more than double Tomova's 28%, confirms that across a broad sample of comparable situations Krejcikova simply wins more points and matches.
This is the foundation of the model's lean toward Krejcikova: not a single metric, but a consistent pattern across ranking, Elo, and baseline performance that all point the same direction.
Recent form adds a layer of nuance. Krejcikova is 6-4 in her last 10 matches, including a notable win over Andreeva (Elo 1906), though she is on a two-match losing streak. Tomova's form is considerably worse at 2-8 with a three-match losing streak and no quality wins to point to, suggesting she has not been finding rhythm against comparable opposition.
The one factor working against Krejcikova is scheduling: she has played 5 matches in the last 14 days versus Tomova's zero, having gone 19 days without competing. Heavier recent workload can matter over a long match, so while the level gap favors Krejcikova, she is not entering this with fresh legs the way her opponent is.
Krejcikova's 62% serve-points-won rate is a solid number that plays into her broader baseline advantage. No serve or return data is available for Tomova, so a direct comparison isn't possible, but the absence of any offsetting metric on her side means there's nothing in the data to suggest she can consistently trouble Krejcikova's service games.
The model rates Krejcikova's win probability at 72%, notably below the market's implied 90% (odds of 1.11). That gap produces a striking -20.3% expected value on the favorite, meaning the price is not compensating for the model's assessed risk even though Krejcikova is clearly favored on merit.
Being the stronger player is not the same as being a good bet at this price. The honest read here is that Krejcikova is likely to win more often than not, but the odds already assume an even more lopsided outcome than the model supports — this is not a spot where favorite and value line up.
Impact and analysis from real match data (Elo, form, head-to-head, rest, surface vs baseline, weather, altitude). The model ≈ the market on average; the odds already capture almost all the edge. 18+ · gamble responsibly.