The Round of 16 at Wimbledon continues on Monday, and one of the most interesting matches of the day pits Grigor Dimitrov against local talent Arthur Fery.
This matchup offers the best projected edges, and I will go over the picks for moneyline, spread and total.
Find my Wimbledon preview and Dimitrov vs Fery prediction for Monday below.
Grigor Dimitrov vs Arthur Fery Player Prediction
- Dimitrov vs Fery Pick: Dimitrov -4.5 (-115)
My Dimitrov vs Fery best bet is on Dimitrov to cover the spread. Make sure to find the best odds by checking our live Wimbledon odds page.
Dimitrov vs Fery Odds
| Grigor Dimitrov Odds | -234 |
| Arthur Fery Odds | +188 |
| Spread | Dimitrov -4.5 (-115), Fery +4.5 (-125) |
| Over/Under | 39.5 (-110o / -130u) |
| Dimitrov-Fery H2H | 0-0 |
| Time | How to Watch | Monday, Approx. 9:40 a.m. ET | ESPN Unlmtd |
| Odds via DraftKings | |
Dimitrov vs Fery Preview, Prediction
Fery has been a nice story for the London crowd, winning three straight matches here after not being able to get past the qualifying stage at Roland Garros, but his ride seems to end now against a much tougher rival than previous ones.
These two players have never met, but Dimitrov not only has the arsenal of shots and the experience, but the model gives him a clear edge on the market.
Thus, I'm taking Dimitrov -4.5, which has the top grade in my tennis model (A+) and an 8.0% overall edge.
He also gets a B+ grade on the moneyline, with a 5.7% edge, and his dominance should keep the total under 39.5 games, which has a C+ grade in my model with a 4.7% edge.
Basically, for my model, this is what I'm trying to accomplish: For every match, three independent signals get blended into a final probability. First, a walk-forward Elo rating for each player (separate for overall and by surface, regressed hard toward a below-average baseline for anyone with a thin sample or a history of playing qualifiers, so a hot streak against weak competition can’t fake elite form).
Second, a point-by-point Monte Carlo simulation built from each player’s real serve/return stats, which gets pulled toward what Elo says whenever the two disagree — Elo acts as a strong check on the simulation, not the other way around.
Third, the devigged market consensus price itself, blended in at the end as a sanity anchor. The result is a single win probability per match that reflects skill history, current form, and what the market already believes, not any one of those alone.
From there, the same win probability gets used to grade three markets — Moneyline, Spread, and Total Games — by comparing what the model thinks against what the market is actually offering.
The size of that gap, scaled consistently across all three markets on one shared scale, is the “edge” you see, and the letter grade is just that edge bucketed for a quick read.
In the case of this matchup, here's where the edges lie statistically:
Picks: Dimitrov -4.5 (-115, DraftKings)
