Alexa Grasso vs Manon FiorotNoche UFC: Silva vs Delgado

Alexa Grasso vs Manon Fiorot — Peso mosca femenino — estaba programada para el sábado, 12 de septiembre de 2026 en Noche UFC: Silva vs Delgado en Desert Diamond Arena, Glendale. Resultado oficial aún no registrado. Picks Terminal cubre el enfrentamiento con una estimación de probabilidad de victoria, un desglose del enfrentamiento e inteligencia extraída de fuentes públicas.

Cartelera principal · Women's FlyweightID · 0CAFE6E6-4BFB-4E25-912A-C2A0F477A7DC
Alexa Grasso

Rango #3 · Women's Flyweight

Alexa Grasso

17-5-1 · MMA

Manon Fiorot

Rango #2 · Women's Flyweight

Manon Fiorot

"The Beast"

13-2-0 · Karate

Modelo de probabilidad de victoria · v4.2

Grasso

47%

Ventaja6%

Fiorot

53%

Comparación de habilidades

71
71
Golpeo
58
59
Lucha
69
69
Cardio
55
62
Defensa de derribos
71
72
Resistencia de mentón

Atributos físicos

GrassoMétricaFiorot
5' 5"Estatura5' 7"
66"Alcance65"
33Edad36
—Postura—
41%Tasa de finalización—

Récord de carrera

GrassoMétricaFiorot
5Victorias por KO/TKO8
2Victorias por sumisión—
6Finalizaciones en 1.º asalto2
4.11Golpes significativos / min4.61
3.71Golpes significativos recibidos / min3.26
59%Defensa de golpeo50%
0.40Promedio de knockdowns / 15 min1.29
55%Defensa de derribo62%
0.67Sumisiones / 15 min0.55
14:56Tiempo promedio de pelea12:29

Distribución de golpes

Grasso

Golpes significativos por objetivo

Objetivo principal Cabeza

Cabeza

62%

Cuerpo

19%

Pierna

19%
Golpes significativos por objetivo — Grasso

Golpes significativos por posición

De pie — 81%De pie81%
Clinch — 15%Clinch15%
Suelo — 3%Suelo3%

Posición principal De pie

Fiorot

Golpes significativos por objetivo

Objetivo principal Equilibrado

Cabeza

38%

Cuerpo

32%

Pierna

30%
Golpes significativos por objetivo — Fiorot

Golpes significativos por posición

De pie — 85%De pie85%
Clinch — 7%Clinch7%
Suelo — 8%Suelo8%

Posición principal De pie

Inteligencia de la pelea

Consenso público

— Datos de consenso no disponibles —

Últimas noticias

— Sin noticias recientes —

Grasso

Fortalezas

  • Ventaja en Sub/15 (0.67 vs 0.55)

Debilidades

  • Muestra de UFC potencialmente incompleta
  • Puede ser castigada cuando su fase preferida se desmorona

Oportunidades

  • Establecer la fase preferida
  • Construir una ofensiva repetible a lo largo del tiempo

Amenazas

  • Manon Fiorot cambiando la fase de la pelea
  • Giro de impulso por alto impacto
Fiorot

Fortalezas

  • Ventaja en SLpM (4.61 vs 4.11)
  • Ventaja en SApM (3.26 vs 3.71)
  • Ventaja en TDD (62 vs 55)

Debilidades

  • Muestra de UFC potencialmente incompleta
  • Puede ser castigada cuando su fase preferida se desmorona

Oportunidades

  • Establecer la fase preferida
  • Construir una ofensiva repetible a lo largo del tiempo

Amenazas

  • Alexa Grasso cambiando la fase de la pelea
  • Giro de impulso por alto impacto

Análisis detallado

El modelo favorece a Fiorot
Ventajas clave
  • Ventaja en SLpM (4.61 vs 4.11)
  • Ventaja en SApM (3.26 vs 3.71)
  • Ventaja en TDD (62 vs 55)
Posibles riesgos
  • Las muestras limitadas reducen la certeza donde los índices oficiales de UFC no están disponibles.
  • Alexa Grasso puede superar al modelo forzando una fase de pelea diferente.
  • Un intercambio de alto impacto puede anular la base estadística.
Análisis del modelo

Manon Fiorot tiene la ruta general más repetible, mientras que Alexa Grasso mantiene un camino creíble si la pelea se asienta en su fase preferida.

Pronóstico

Se espera que Manon Fiorot y Alexa Grasso pongan a prueba la fase principal del enfrentamiento desde el principio. Se proyecta que Manon Fiorot genere la ofensiva más sostenible, pero la ruta opuesta sigue vigente donde el tamaño de la muestra en UFC es reducido.

Las valoraciones de habilidades, la probabilidad de victoria, las ventajas, los riesgos y el pronóstico son estimaciones generadas por el modelo a partir de perfiles públicos de peleadores — no son estadísticas oficiales de UFC ni garantías de resultado.

Desglose del enfrentamiento

Este enfrentamiento de peso mosca femenino depende del control de las fases y del volumen de golpeo sostenible. Los índices oficiales disponibles de la UFC producen una inclinación del modelo analítico del 51% hacia Manon Fiorot. La confianza se reduce para debutantes y peleadores con muestras pequeñas en UFC, y los valores faltantes se dejan nulos deliberadamente. La inclinación final también incorpora el ranking actual, la experiencia en peleas de cinco asaltos o de nivel de campeonato, y la calidad de la muestra donde las estadísticas brutas de la UFC por sí solas están incompletas.

Análisis completo de la pelea

5 min de lectura · Actualizado 7 de septiembre de 2026

Este análisis extendido aún no está traducido; se muestra la versión en inglés.

The Women's Flyweight division takes center stage at Noche UFC: Silva vs Delgado on September 12, 2026. This matchup features Alexa Grasso, holding a record of 17-5-1, against Manon Fiorot, who enters with a record of 13-2-0. Hosted at the Desert Diamond Arena in Glendale, this contest pits two elite competitors against one another in a quest for divisional supremacy. With both fighters ranked in the top three, the tactical implications for the weight class are significant.

Striking Dynamics and Shot Selection

The striking exchange features two distinct approaches to volume and target selection. Manon Fiorot maintains a higher output with 4.61 strikes landed per minute, compared to 4.11 for Alexa Grasso. Fiorot utilizes a Karate style that distributes damage across the body, with 38 percent of significant strikes targeting the head, 32 percent to the body, and 30 percent to the legs. In contrast, Grasso is heavily head-oriented, directing 62 percent of her significant strikes to that region, with 19 percent going to the body and 19 percent to the legs. While Grasso shows a higher striking defense at 59 percent compared to 50 percent for Fiorot, Fiorot absorbs fewer strikes overall, maintaining a rate of 3.26 strikes absorbed per minute against Grasso's 3.71. This suggests Fiorot may find more success in prolonged exchanges through varied targeting.

Grappling and Defensive Transitions

In the grappling department, both fighters possess defensive capabilities that could force the action to remain standing. Manon Fiorot holds a statistical edge in takedown defense at 62 percent, while Alexa Grasso stands at 55 percent. The submission threat is present on both sides, though Grasso maintains a slightly higher submission average of 0.67 per fight compared to 0.55 for Fiorot. Grasso has secured 2 wins by submission throughout her career, whereas Fiorot relies more heavily on her striking base, having earned 8 wins by knockout. The model notes that Grasso can outperform expectations by forcing a different fight phase, potentially utilizing her MMA style to initiate grappling exchanges if the striking volume from Fiorot becomes difficult to manage. The wrestling ratings are nearly identical, with Grasso at 58 and Fiorot at 59, indicating a competitive stalemate on the mats.

Pace, Cardio, and Durability

Durability and stamina will be tested as these athletes navigate their respective average fight times. Alexa Grasso has an average fight time of 14:56, reflecting her experience in longer contests and her 10 wins by decision. Manon Fiorot averages 12:29 in the cage, which aligns with her higher knockdown average of 1.29 compared to 0.4 for Grasso. Both fighters share a cardio rating of 69, suggesting that neither should see a significant drop in performance as the rounds progress. Chin durability is also closely matched, with Fiorot rated at 72 and Grasso at 71. Given that Grasso has 5 wins by knockout and Fiorot has 8, the ability to withstand high-impact exchanges is paramount. The model highlights that one high-impact exchange can override the statistical baseline, making the early rounds critical for establishing dominance.

Physical Attributes and Reach Factors

Physical dimensions may play a role in how each fighter manages distance. Manon Fiorot stands at 170 cm, providing a height advantage over the 165 cm Alexa Grasso. However, Grasso possesses a slight reach advantage at 66 inches compared to the 65 inches of Fiorot. This reach discrepancy, though small, could assist Grasso in her head-heavy striking approach, allowing her to land her 4.11 strikes per minute from the outside. Fiorot’s height may aid her in maintaining the 62 percent takedown defense, as she can use her frame to leverage against Grasso’s attempts. With Grasso aged 33 and Fiorot aged 36, both are in their athletic prime for the division. The interaction between Fiorot's height and Grasso's reach will likely dictate the range at which the majority of the 4.61 to 4.11 striking volume exchange occurs.

The Model's Statistical Perspective

The analyst model produces a 51 percent lean toward Manon Fiorot, while Alexa Grasso holds a win probability of 47 percent. This narrow margin is driven by Fiorot's advantages in strikes landed per minute and takedown defense. The model identifies that Fiorot has the more repeatable overall route, primarily through her sustainable offense and lower rate of strikes absorbed. However, the confidence in these figures is tempered by limited samples where official UFC rates are unavailable. Grasso remains a credible threat, particularly if she can leverage her 41 percent finish rate or utilize her superior striking defense of 59 percent to frustrate Fiorot. The matchup breakdown suggests that while Fiorot is projected to create more sustainable offense, the opposing route for Grasso remains live, especially if the fight settles into a phase where Grasso can exploit her submission average.

Veredicto del modelo

The model indicates a marginal 51 percent lean toward Manon Fiorot, primarily supported by her higher volume of 4.61 strikes landed per minute and a 62 percent takedown defense. Alexa Grasso, with a 47 percent win probability, remains competitive through her 59 percent striking defense and higher submission average of 0.67. While Fiorot is projected to sustain more offense, Grasso's ability to force different phases and her 10 decision wins suggest she can win rounds through tactical adjustments. The narrow statistical gap reflects a high-level encounter where small advantages in output and defensive efficiency define the projected outcome.

Preguntas frecuentes

What are the primary statistical advantages for Manon Fiorot?
Manon Fiorot holds key advantages in strikes landed per minute at 4.61 versus 4.11 for Grasso. She also maintains a superior takedown defense of 62 percent and a lower rate of strikes absorbed per minute at 3.26, which contributes to her 51 percent win probability.
How does Alexa Grasso's striking style differ from her opponent?
Alexa Grasso is highly focused on head strikes, which account for 62 percent of her significant strikes. While her volume is lower at 4.11 landed per minute, she possesses a higher striking defense rate of 59 percent, compared to 50 percent for Fiorot.
What role does experience play in this matchup?
Alexa Grasso brings a record of 17-5-1 and an average fight time of 14:56, including 10 wins by decision. Manon Fiorot, with a 13-2-0 record, shows a higher knockdown average of 1.29 and 8 wins by knockout, suggesting a more power-oriented approach.

Análisis informativo generado a partir de estadísticas públicas y revisado con controles de calidad automáticos. No es asesoramiento de apuestas.

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