PREDICCIÓN DEL MODELO · 2026-08-25
● HARD

T. Samuel vs B. Harris — predicción

✓ Acertado
SAMUELPROBABILIDAD DE VICTORIAHARRIS
64%
prob. modelo
@1.21
cuota · 83% impl.
⚔H2H 1–0 Samuel🎾Saque 66%📈Forma 7/10
CONDICIONES DEL PARTIDO◆ en el modelo◇ contexto
Superficie◆
Dura

Bote regular y velocidad media-alta: condiciones neutras, sin favorecer un estilo.

Temperatura◇
26°C

Ambiente cálido: la bola vuela algo más y el físico cuenta.

Humedad◇
51%

Aire seco: la bola viaja con normalidad.

Viento◇
14 km/h

Viento flojo: sin efecto apreciable.

La superficie sí entra en el modelo (la especialización por superficie es uno de sus factores). El clima y la altitud son contexto que publicamos para ti — NO mueven la probabilidad.

EL RAZONAMIENTO DEL MODELO

›Ranking: #110 vs #161 (mejor clasificado)

›Modelo 64% vs mercado 83% → el modelo lo ve menos probable que la cuota

›Forma reciente: 7/10 en los últimos partidos

Probabilidad calibrada del modelo (~65% de precisión fuera de muestra). No es una garantía: el modelo ≈ el mercado de media, así que la cuota ya captura casi toda la ventaja. +18 · juega con responsabilidad.
@1.56
cuota justa
−22.4%
valor esperado
CÓMO IMPORTA CADA FACTOR
Level (Elo/ranking)▸ Samuel●●●
Samuel ranks #113 vs Harris #167, Elo 1938 vs 1724 (+214). Model probability 64% reflects this gap; market at 72% overestimates it.
Form▸ Harris●●
Samuel 3/10 recent (6W–4L); Harris mixed but secured quality wins vs Piros (1927) and Gea (1919), both ranked higher than Samuel's baseline.
Rest/fatigue= Igualado●●
Both 1d rest post-QF; Samuel played 1 match in 14d, Harris 2. Fatigue risk equal; Harris slightly fresher match volume, Samuel longer layoff beforehand (56d).
Serve/return▸ Samuel●●
Samuel 66% serve vs Harris 64%; Samuel 41% return vs Harris 37%. Marginal edge to Samuel; neither dominates baseline stats.
Head-to-head▸ Samuel●
1 meeting (2023 ITF): Samuel won. Single data point carries minimal predictive weight at ATP tier.
Weather= Igualado●
25°C, 49% humidity, 15 km/h wind: warm and dry hard-court conditions, no systematic edge to either player's style.
RANKING AND RATING ADVANTAGE

Samuel enters as the clear higher-ranked player: #113 ATP vs Harris's #167, with an Elo gap of 214 points (1938 vs 1724). This explains the model's 64% win probability and is the dominant structural factor favoring Samuel. The market's 72% implies probability overstates this advantage, pricing Samuel as a near-3-to-1 favorite when the Elo/ranking evidence supports only a 2-to-1 lean.

However, Elo and ranking reflect historical performance over time. Form from the last 10 matches—where Harris shows recent quality wins and Samuel shows mixed results—provides a meaningful counter-signal that the market has partially captured but the model has not fully discounted.

FORM AND RECENT WINS

Samuel's recent record is 6–4 over 10 matches (3/10 in the model's summary, likely due to weighted scoring of quality). Over the same period, Harris shows volatility (5W–5L raw record) but two standout wins: Z. Piros (Elo 1927) and A. Gea (Elo 1919). Both opponents rank significantly higher than Samuel's Elo of 1938 at the baseline, and even Harris's own 1724 Elo baseline. These wins suggest Harris is capable of aggressive tennis and can execute against higher-ranked opponents—a genuine positive for a qualifier or underdog facing a seeded player.

Samuel's lack of quality wins listed and mixed form (including two losses in last 10) weakens his narrative as a heavy favorite. The gap between his ranking and his form is notable and works against market confidence.

REST AND FATIGUE CONTEXT

Both players reached the US Open quarter-finals, playing 1 day ago. This deep-run fatigue flag applies symmetrically to each. Samuel has had only 1 match in the last 14 days but returned from a 56-day layoff before this tournament, which carries rustiness risk. Harris has played 2 matches in 14 days—more volume but still within a compressed US Open context. Rest is essentially neutral; any edge to Harris from match rhythm is offset by Samuel's longer pre-tournament absence.

SERVE AND RETURN PARITY

Samuel's serve win rate (66%) edges Harris (64%); Samuel's return rate (41%) also leads Harris (37%). These margins are small (2–4 percentage points) and typical of players of similar tier. Neither player has a pronounced baseline strength in serve or return to exploit, meaning the match will likely turn on tactical execution, adaptability, and—given form volatility—who is steadier on the day. The hard court will reward consistency; neither player has data suggesting a hard-court-specific strength to lean on.

VALUE AND MODEL HONESTY

The model assesses Samuel at 64% win probability; the market prices him at 72% (odds 1.39). This 8-percentage-point gap generates a negative expected value of –10.7% for a Samuel bet at these odds—backing the favorite is a proposition with calculated long-term loss. Samuel is favored correctly by ranking and Elo, but the market has overestimated the edge by conflating ranking with recent form, where Harris has shown more convincing results.

The honest read: Samuel should be favored, but not as heavily as the market suggests. A 64% probability on a 1.39 odds bet yields no value; a fair line for Samuel would be nearer 1.55–1.60. Harris at 36% model probability is underbought against the 28% implied by 1.39, making a small contrarian lean defensible if one judges the quality-win evidence enough to trust his form over pure ranking.

Impacto y análisis a partir de datos reales del partido (Elo, forma, cara a cara, descanso, superficie vs base, clima, altitud). El modelo ≈ el mercado de media; la cuota ya captura casi toda la ventaja. +18 · juega con responsabilidad.

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