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ITF Men - Doubles: M15 Dublin (Ireland), hard
ITF Men - Doubles: M15 Dublin (Ireland), hard
29.07.2026 13:00 UTC Match prediction

Farzam M./Finkelstein A. - Fradkin J./Lorusso L.

Tennis ITF Men - Doubles: M15 Dublin (Ireland), hard
ITF Men - Doubles: M15 Dublin (Ireland), hard hard 29.07.2026 13:00 UTC Finished
29.07.2026 13:00 UTC Finished
Farzam M./Finkelstein A.
Farzam M./Finkelstein A.
F
Fradkin J./Lorusso L.
1:2
Odds
P1 2.75 33.7% BetBoom
P2 1.40 66.3% BetBoom
Coverage: hard
Preview Statistics Broadcast Comments

About the athletes

- Country -
- Rating -
- Age -
- Height (cm) -
- Weight (kg) -
- Hand -
- Seed -
hard Coverage hard
0 H2H 0
🎯 PropickAI prediction
Medium confidence

Our model prediction (Glicko-2)

PropickAI model · comparison with the market line (no margin)

2 Fradkin J./Lorusso L. — 64%

Pure model vs market (2 · Fradkin J./Lorusso L.): model 48% · market 66% Δ −18 pp model estimates below the market

1 · Farzam M./Finkelstein A.35.7%
market34%
2 · Fradkin J./Lorusso L. ✓ Pick64.3%
market66%

Model estimate: win Farzam M./Finkelstein A. 35.7%, win Fradkin J./Lorusso L. 64.3%. Model favourite — Fradkin J./Lorusso L..

Informational estimate, not a betting recommendation.

AI agent prediction

Independent AI-agent assessment from our data (model, market line, form, H2H)

2Fradkin J./Lorusso L. (odds1.40) Score 1:2 confidence 64% ✓ outcome correct · exact score
  • • Farzam M./Finkelstein A
  • • — Fradkin J./Lorusso L
  • • (tennis)
  • • Model backs Fradkin J./Lorusso L.: probability 64% vs 71% on the line (odds 1.40)
  • • no edge over the line (-7 pp) — informational only.

Analytical AI-agent assessment, not a betting recommendation.

Math-model prediction

AI match prediction Farzam M./Finkelstein A. - Fradkin J./Lorusso L. July 29, 2026

Tennis math model

Based on the collected prematch data, the favourite looks like Fradkin J./Lorusso L..

Line favourite market consensus: Fradkin J./Lorusso L.. We cross-check with Glicko and the math model below.
  • Win odds (market consensus): 1 2.75 / 2 1.40
  • Glicko: Farzam M./Finkelstein A. 35.7% / Fradkin J./Lorusso L. 64.3%

For reference

Fair probability (no margin)

Probability excluding the bookmaker margin — for reference, not a betting recommendation.
Winner bookmaker margin 7.8%
1 33.7%
2 ✓ Pick 66.3%

Odds source: market consensus. This is the fair probability after removing the bookmaker margin from the odds — reference information, not a prediction or a betting recommendation.

Match center
Start 29.07.2026 13:00 UTC
Coverage hard
Match center

Farzam M./Finkelstein A. - Fradkin J./Lorusso L.

H2H 0 head-to-head matches
Market 2 model / bookmakers
Flashscore match data source checked
Odds match data source checked
Line depth match data source checked
Present in data
Market Match Participants Line
More needed
Form Championat, Flashscore
H2H Championat, Flashscore
Tournament Championat, Flashscore
Movement Line history
Overview Championat
Post-match / PropickAI database
Score 1:2
Events 0
Statistics 0
PropickAI check: math model and Glicko-2

We mark in green only strong signals where the model passed our publication filter. The other rows are for audit and training.

Option Signal Prediction / actual Rating
Glicko-2: base favourite Audit tennis is audit-only for now: surface, serve/return and market are needed Data: line, coverage away - 64.3% fact: away hit / ROI 40.0% / Brier 0.255 / LogLoss 0.441
Glicko-2: calibrated favourite Audit tennis is audit-only for now: surface, serve/return and market are needed Data: line, coverage away - 51.7% fact: away hit / ROI 40.0% / Brier 0.466 / LogLoss 0.659
Market and Glicko

Tennis math model. Tennis without draws: the base signal comes from player rating, surface, form, serve/return and tournament fatigue. For live logic the set state and who is serving matter more than the overall points score.

Outcome Line Glicko Signal
Farzam M./Finkelstein A. 33.8% 35.7%
Fradkin J./Lorusso L. 66.2% 64.3% market and model agree
1X2: 2 Bookies

Glicko-2 is a team-strength rating: it weighs the line, history and consistency, but is not a guarantee.

Tennis math model
P1 / P2 35.7% / 64.3% probabilities
Rating 1,500 / 1,500 Farzam M./Finkelstein A. / Fradkin J./Lorusso L.
RD 350 / 350 rating uncertainty
r +/- 2RD 800-2,200 / 800-2,200 strength interval
HFA: 0 HFA mu: 0.000 MoV: on N: N=1 P: two_way_glicko2_expected_score

Best value: no value found

Tennis without draws: the base signal comes from player rating, surface, form, serve/return and tournament fatigue. For live logic the set state and who is serving matter more than the overall points score.

Betting snapshot
1X2
2 1.40 market consensus · no value · model 64.3%
1 2.74 market consensus · no value · model 35.7%

Betting notes are built from the line, market and our math model: take a signal only when the model and market agree.

Bookmaker line

Match markets

bookmaker line and markets

Outcome (1X2)

Outcome Baltbet Betcity
2.73 36.6% 2.75 36.4%
1.40 71.4% 1.40 71.4%