UFC Fight Night: Brady vs. Buckley: Predictions & Analysis
UFC Fight Night: Brady vs. Buckley lands on Saturday, April 25, 2026 in Las Vegas, Nevada, USA with 1 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
| Matchup | Pick | Confidence | Prob |
|---|---|---|---|
| Sean Brady vs Joaquin BuckleyWelterweight | Joaquin Buckley | Toss-up | 51% |
Fight-by-Fight Breakdown
Sean Brady vs Joaquin Buckley
The Welterweight matchup features Sean Brady (8-1) taking on Joaquin Buckley (11-4). Buckley will look to use a 4-inch reach edge to control distance.
Buckley carries a modest Elo edge (1728 to 1658), the kind of gap that reflects a slightly better run of form rather than a talent chasm. Both fighters bring momentum: Brady rides a 3-fight win streak into this one, while Buckley has won 6 straight.
The style clash matters here: Brady looks to close distance and put the fight on the mat, while Buckley is comfortable adjusting on the fly, mixing strikes and grappling as openings appear. In our database, wrestlers own a 59% win rate against all-rounders, giving Brady the stylistic edge.
The submission threat is elevated here at 42%, with the model also seeing 28% KO/TKO and 29% decision probability.
The Pick: Joaquin Buckley over Sean Brady. This is essentially a pick'em. The model nudges toward Buckley at 51%, but there's almost nothing separating these two.
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.