UFC Fight Night: Blaydes vs. Daukaus: Predictions & Analysis

Saturday, March 26, 2022·Columbus, Ohio, USA

UFC Fight Night: Blaydes vs. Daukaus lands on Saturday, March 26, 2022 in Columbus, Ohio, USA with 12 bouts on the card. Below is our fight-by-fight breakdown, combining Elo ratings, rolling statistical trends, style matchup data, and betting market context into a pick for every bout.

Quick Picks

MatchupPickConfidenceProb
Curtis Blaydes vs Chris DaukausHeavyweightCurtis BlaydesStrong92%
Alexa Grasso vs Joanne WoodWomen's FlyweightAlexa GrassoStrong76%
Bryan Barberena vs Matt BrownWelterweightMatt BrownToss-up52%
Kai Kara-France vs Askar AskarovFlyweightAskar AskarovConfident71%
Neil Magny vs Max GriffinWelterweightNeil MagnyConfident69%
Marc Diakiese vs Viacheslav BorshchevLightweightViacheslav BorshchevLean61%
Sara McMann vs Karol RosaWomen's BantamweightKarol RosaStrong84%
Chris Gutierrez vs Batgerel DanaaBantamweightChris GutierrezLean64%
Aliaskhab Khizriev vs Denis TiuliulinMiddleweightAliaskhab KhizrievStrong88%
Manon Fiorot vs Jennifer MaiaWomen's FlyweightManon FiorotStrong91%
Matheus Nicolau vs David DvorakFlyweightMatheus NicolauToss-up50%
Luis Saldana vs Bruno SouzaFeatherweightBruno SouzaLean56%

Fight-by-Fight Breakdown

92%
Curtis Blaydes
Blaydes
13-5
Elo 1634
Striker
VS
Daukaus
4-3
Elo 1108
Striker

The Heavyweight matchup features Curtis Blaydes (13-5) taking on Chris Daukaus (4-3). Blaydes will look to use a 4-inch reach edge to control distance.

Blaydes is rated at 1634 — 527 points above Daukaus's 1108. Gaps this large usually mean one fighter has been consistently beating better opponents.

The style clash matters here: Blaydes brings a versatile approach, while Daukaus is patient on the feet, timing counters and loading up when he sees openings. In our database, knockout artists own a 54% win rate against strikers, giving Daukaus the stylistic edge.

A few statistical edges stand out. Daukaus throws significantly more leather — a 4.7 sig. strike per minute gap. Blaydes is far more active with takedowns, averaging 5.5 more per 15 minutes. Blaydes has tighter striking defense, making opponents miss more often.

**The Pick: Curtis Blaydes over Chris Daukaus.** The model is firm on this one: Blaydes at 92%. Notably, the betting market has Blaydes at 82% implied while our model sees 92% — a 10-point disagreement that could signal value.

Alexa Grasso vs Joanne Wood

Women's Flyweight
76%
Alexa Grasso
Grasso
8-4-1
Elo 1376
All-Rounder
VS
Wood
8-8
Elo 1101
All-Rounder

The Women's Flyweight matchup features Alexa Grasso (8-4-1) taking on Joanne Wood (8-8).

Grasso is rated at 1376 — 275 points above Wood's 1101. Gaps this large usually mean one fighter has been consistently beating better opponents.

Both fighters land in our "All-Rounder" archetype — fighters comfortable everywhere, able to strike or grapple depending on what the opponent gives them. When mirror matchups like this happen, the edge usually goes to whoever can impose their preferred pace and range.

A few statistical edges stand out. Wood throws significantly more leather — a 2.6 sig. strike per minute gap. Wood is far more active with takedowns, averaging 0.9 more per 15 minutes. Grasso has tighter striking defense, making opponents miss more often.

**The Pick: Alexa Grasso over Joanne Wood.** The model is firm on this one: Grasso at 76%. Notably, the betting market has Grasso at 71% implied while our model sees 76% — a 4-point disagreement that could signal value.

52%
Matt Brown
Barberena
9-9
Elo 960
All-Rounder
VS
Brown
16-13
Elo 1201
All-Rounder

The Welterweight matchup features Bryan Barberena (9-9) taking on Matt Brown (16-13). Brown will look to use a 3-inch reach edge to control distance.

Brown is rated at 1201 — 241 points above Barberena's 960. Gaps this large usually mean one fighter has been consistently beating better opponents.

Both fighters land in our "All-Rounder" archetype — fighters comfortable everywhere, able to strike or grapple depending on what the opponent gives them. When mirror matchups like this happen, the edge usually goes to whoever can impose their preferred pace and range.

A few statistical edges stand out. Barberena throws significantly more leather — a 2.8 sig. strike per minute gap. Brown is far more active with takedowns, averaging 1.1 more per 15 minutes. Brown has tighter striking defense, making opponents miss more often.

**The Pick: Matt Brown over Bryan Barberena.** This is essentially a pick'em. The model nudges toward Brown at 52%, but there's almost nothing separating these two. The market and our model are aligned — the line looks fair.

71%
Askar Askarov
Kara-France
8-4
Elo 1351
Striker
VS
Askarov
3-0-1
Elo 1285

The Flyweight matchup features Kai Kara-France (8-4) taking on Askar Askarov (3-0-1).

Kara-France carries a modest Elo edge (1351 to 1285), the kind of gap that reflects a slightly better run of form rather than a talent chasm. Askarov has won 3 straight.

A few statistical edges stand out. Kara-France throws significantly more leather — a 1.6 sig. strike per minute gap. Askarov is far more active with takedowns, averaging 2.8 more per 15 minutes. Kara-France has tighter striking defense, making opponents miss more often.

**The Pick: Askar Askarov over Kai Kara-France.** We're leaning Askarov here at 71%, a solid but not overwhelming edge. Notably, the betting market has Kara-France at 22% implied while our model sees 29% — a 7-point disagreement that could signal value.

Neil Magny vs Max Griffin

Welterweight
69%
Neil Magny
Magny
24-12
Elo 1270
Wrestler
VS
Griffin
8-9
Elo 1152
Striker

The Welterweight matchup features Neil Magny (24-12) taking on Max Griffin (8-9). Magny is the bigger frame at 6'3" with a 4-inch reach advantage.

There's a real Elo separation here: Magny at 1270 versus Griffin at 1152. That 119-point gap typically reflects a meaningful difference in recent quality of competition and results.

Stylistically this is Magny's all-rounder game against Griffin's striker approach. Magny is comfortable adjusting on the fly, mixing strikes and grappling as openings appear, while Griffin brings a versatile approach. Historically these archetypes are dead-even when they collide.

A few statistical edges stand out. Griffin throws significantly more leather — a 1.6 sig. strike per minute gap. Magny is far more active with takedowns, averaging 0.2 more per 15 minutes. Griffin has tighter striking defense, making opponents miss more often.

**The Pick: Neil Magny over Max Griffin.** We're leaning Magny here at 69%, a solid but not overwhelming edge. The market and our model are aligned — the line looks fair.

61%
Viacheslav Borshchev
Diakiese
7-7
Elo 1050
Striker
VS
Borshchev
3-5-1
Elo 812
All-Rounder

The Lightweight matchup features Marc Diakiese (7-7) taking on Viacheslav Borshchev (3-5-1). Diakiese will look to use a 4-inch reach edge to control distance.

Diakiese is rated at 1050 — 238 points above Borshchev's 812. Gaps this large usually mean one fighter has been consistently beating better opponents.

Stylistically this is Diakiese's striker game against Borshchev's all-rounder approach. Diakiese brings a versatile approach, while Borshchev is comfortable adjusting on the fly, mixing strikes and grappling as openings appear. Historically these archetypes are dead-even when they collide.

A few statistical edges stand out. Borshchev throws significantly more leather — a 0.6 sig. strike per minute gap. Diakiese is far more active with takedowns, averaging 1.7 more per 15 minutes. Borshchev has tighter striking defense, making opponents miss more often.

**The Pick: Viacheslav Borshchev over Marc Diakiese.** The model gives Borshchev a slight nod at 61% — this could easily go either way. The market implies 43% for Diakiese, but our model sees only 39%. That 3-point gap favoring Borshchev is worth watching.

Sara McMann vs Karol Rosa

Women's Bantamweight
84%
Karol Rosa
McMann
6-6
Elo 1158
Wrestler
VS
Rosa
7-4
Elo 1201
Striker

The Women's Bantamweight matchup features Sara McMann (6-6) taking on Karol Rosa (7-4).

Rosa carries a modest Elo edge (1201 to 1158), the kind of gap that reflects a slightly better run of form rather than a talent chasm.

Stylistically this is McMann's wrestler game against Rosa's striker approach. McMann looks to close distance and put the fight on the mat, while Rosa brings a versatile approach. Historically these archetypes are dead-even when they collide.

A few statistical edges stand out. Rosa throws significantly more leather — a 5.7 sig. strike per minute gap. McMann is far more active with takedowns, averaging 1.9 more per 15 minutes. Rosa has tighter striking defense, making opponents miss more often.

**The Pick: Karol Rosa over Sara McMann.** The model is firm on this one: Rosa at 84%. The market implies 31% for McMann, but our model sees only 16%. That 15-point gap favoring Rosa is worth watching.

64%
Chris Gutierrez
Gutierrez
10-3-1
Elo 1298
Striker
VS
Danaa
3-3
Elo 887
Striker

The Bantamweight matchup features Chris Gutierrez (10-3-1) taking on Batgerel Danaa (3-3). Danaa will look to use a 3-inch reach edge to control distance.

Gutierrez is rated at 1298 — 410 points above Danaa's 887. Gaps this large usually mean one fighter has been consistently beating better opponents.

Stylistically this is Gutierrez's all-rounder game against Danaa's striker approach. Gutierrez is comfortable adjusting on the fly, mixing strikes and grappling as openings appear, while Danaa brings a versatile approach. Historically these archetypes are dead-even when they collide.

A few statistical edges stand out. Danaa throws significantly more leather — a 1.4 sig. strike per minute gap. Gutierrez is far more active with takedowns, averaging 0.7 more per 15 minutes. Gutierrez has tighter striking defense, making opponents miss more often.

**The Pick: Chris Gutierrez over Batgerel Danaa.** The model gives Gutierrez a slight nod at 64% — this could easily go either way.

88%
Aliaskhab Khizriev
Khizriev
1-0
Elo 1111
VS
Tiuliulin
1-4
Elo 756
Striker

The Middleweight matchup features Aliaskhab Khizriev (1-0) taking on Denis Tiuliulin (1-4). Tiuliulin is the bigger frame at 6'1" with a 3-inch reach advantage.

Khizriev is rated at 1111 — 355 points above Tiuliulin's 756. Gaps this large usually mean one fighter has been consistently beating better opponents.

A few statistical edges stand out. Tiuliulin throws significantly more leather — a 0.0 sig. strike per minute gap. Tiuliulin is far more active with takedowns, averaging 0.0 more per 15 minutes. Tiuliulin has tighter striking defense, making opponents miss more often.

**The Pick: Aliaskhab Khizriev over Denis Tiuliulin.** The model is firm on this one: Khizriev at 88%. The market and our model are aligned — the line looks fair.

Manon Fiorot vs Jennifer Maia

Women's Flyweight
91%
Manon Fiorot
Fiorot
7-1
Elo 1641
Striker
VS
Maia
6-5
Elo 1193
All-Rounder

The Women's Flyweight matchup features Manon Fiorot (7-1) taking on Jennifer Maia (6-5). There's a 3-inch height gap favoring Fiorot.

Fiorot is rated at 1641 — 449 points above Maia's 1193. Gaps this large usually mean one fighter has been consistently beating better opponents.

Stylistically this is Fiorot's striker game against Maia's all-rounder approach. Fiorot brings a versatile approach, while Maia is comfortable adjusting on the fly, mixing strikes and grappling as openings appear. Historically these archetypes are dead-even when they collide.

A few statistical edges stand out. Fiorot throws significantly more leather — a 3.6 sig. strike per minute gap. Fiorot is far more active with takedowns, averaging 1.5 more per 15 minutes. Fiorot has tighter striking defense, making opponents miss more often.

**The Pick: Manon Fiorot over Jennifer Maia.** The model is firm on this one: Fiorot at 91%. Notably, the betting market has Fiorot at 80% implied while our model sees 91% — a 11-point disagreement that could signal value.

50%
Matheus Nicolau
Nicolau
7-3
Elo 1033
Knockout Artist
VS
Dvorak
3-2
Elo 956
All-Rounder

The Flyweight matchup features Matheus Nicolau (7-3) taking on David Dvorak (3-2).

Nicolau carries a modest Elo edge (1033 to 956), the kind of gap that reflects a slightly better run of form rather than a talent chasm.

Both fighters land in our "All-Rounder" archetype — fighters comfortable everywhere, able to strike or grapple depending on what the opponent gives them. When mirror matchups like this happen, the edge usually goes to whoever can impose their preferred pace and range.

A few statistical edges stand out. Dvorak throws significantly more leather — a 0.5 sig. strike per minute gap. Nicolau is far more active with takedowns, averaging 1.4 more per 15 minutes. Nicolau has tighter striking defense, making opponents miss more often.

**The Pick: Matheus Nicolau over David Dvorak.** This is essentially a pick'em. The model nudges toward Nicolau at 50%, but there's almost nothing separating these two. Notably, the betting market has Nicolau at 46% implied while our model sees 50% — a 4-point disagreement that could signal value.

Luis Saldana vs Bruno Souza

Featherweight
56%
Bruno Souza
Saldana
2-1
Elo 1050
VS
Souza
0-1
Elo 866

The Featherweight matchup features Luis Saldana (2-1) taking on Bruno Souza (0-1). Saldana will look to use a 3-inch reach edge to control distance.

Saldana is rated at 1050 — 184 points above Souza's 866. Gaps this large usually mean one fighter has been consistently beating better opponents.

A few statistical edges stand out. Saldana throws significantly more leather — a 0.7 sig. strike per minute gap. Souza is far more active with takedowns, averaging 0.0 more per 15 minutes. Saldana has tighter striking defense, making opponents miss more often.

**The Pick: Bruno Souza over Luis Saldana.** The model gives Souza a slight nod at 56% — this could easily go either way. The market and our model are aligned — the line looks fair.

Methodology

Predictions are generated by our ensemble model combining LightGBM (65%) and CatBoost (35%), trained on every UFC fight since 1994. The model uses 23 features including Elo ratings, rolling 5-fight statistical averages, style matchup history, physical attributes, and market odds when available.

On our held-out test set (402 fights from January-September 2023), the model achieves 63.4% accuracy with a log-loss of 0.626. High-confidence picks (>75% probability) hit at 82.7%. For full model transparency, visit our Model page.