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Calibrated predictions slate

UFC 328: Chimaev vs. Strickland

May 9, 2026Newark, New Jersey, USA14 of 14 calibrated matchup cards liveFull slate live

This surface shows the governed calibrated stack honestly: probability splits, model reasons, and the caveats that matter when volatility or weak regimes are present.

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What this page is actually doing
  • Shows calibrated probabilities from the governed production alias rather than raw heuristic certainty.
  • Carries volatility and regime caveats forward instead of hiding them behind premium copy.
  • Keeps event rendering tied to real API outputs and real fighter identity data.
UFC Middleweight Title
guarded
Sean Strickland
lean
vs
Khamzat Chimaev
calibrated lean
Sean Strickland
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Sean Strickland
66%
Khamzat Chimaev
34%
why the model leans this way

Sean Strickland projects ahead on current measurable form and matchup profile. Khamzat Chimaev holds the clearer form edge Sean Strickland holds the clearer activity edge Khamzat Chimaev holds the clearer grappling edge Sean Strickland has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Khamzat Chimaev shows the clearer form edge
  • Sean Strickland shows the clearer activity edge
  • Khamzat Chimaev shows the clearer grappling edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Heavyweight
guarded
Alexander Volkov
vs
Waldo Cortes Acosta
lean
calibrated lean
Waldo Cortes Acosta
51% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Alexander Volkov
49%
Waldo Cortes Acosta
51%
why the model leans this way

Waldo Cortes Acosta projects ahead on current measurable form and matchup profile. Alexander Volkov has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Light Heavyweight
low
Jan Blachowicz
lean
vs
Bogdan Guskov
calibrated lean
Jan Blachowicz
66% calibrated win probability for the current lean
Jan Blachowicz
66%
Bogdan Guskov
34%
why the model leans this way

Jan Blachowicz projects ahead on current measurable form and matchup profile. Bogdan Guskov holds the clearer form edge Jan Blachowicz holds the clearer grappling edge Jan Blachowicz has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Bogdan Guskov shows the clearer form edge
  • Jan Blachowicz shows the clearer grappling edge
Uncertainty / caveats
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Middleweight
guarded
Ateba Gautier
lean
vs
Ozzy Diaz
calibrated lean
Ateba Gautier
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Ateba Gautier
66%
Ozzy Diaz
34%
why the model leans this way

Ateba Gautier projects ahead on current measurable form and matchup profile. Ateba Gautier holds the clearer form edge Ateba Gautier holds the clearer activity edge Ateba Gautier has the stronger proven sample in this division Ateba Gautier has shown more recent division stability Division-transition caution: At least one fighter has thin recent sample coverage behind the proxy stats; The matchup has uneven recent sample coverage between the fighters. Empirical calibration applied from historical outcome bins.

  • Ateba Gautier shows the clearer form edge
  • Ateba Gautier shows the clearer activity edge
Risk flags
  • Ozzy Diaz long layoff
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • At least one fighter has thin recent sample coverage behind the proxy stats
  • The matchup has uneven recent sample coverage between the fighters
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Middleweight
guarded
Marco Tulio
lean
vs
Roman Kopylov
calibrated lean
Marco Tulio
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Marco Tulio
66%
Roman Kopylov
34%
why the model leans this way

Marco Tulio projects ahead on current measurable form and matchup profile. Marco Tulio holds the clearer form edge Roman Kopylov has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Marco Tulio shows the clearer form edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Middleweight
guarded
Djorden Santos
lean
vs
Baisangur Susurkaev
calibrated lean
Djorden Santos
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Djorden Santos
66%
Baisangur Susurkaev
34%
why the model leans this way

Djorden Santos projects ahead on current measurable form and matchup profile. Baisangur Susurkaev holds the clearer form edge Baisangur Susurkaev holds the clearer grappling edge Empirical calibration applied from historical outcome bins.

  • Baisangur Susurkaev shows the clearer form edge
  • Baisangur Susurkaev shows the clearer grappling edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Welterweight
guarded
Sean Brady
lean
vs
Joaquin Buckley
calibrated lean
Sean Brady
55% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Sean Brady
55%
Joaquin Buckley
45%
why the model leans this way

Sean Brady projects ahead on current measurable form and matchup profile. Sean Brady holds the clearer activity edge Sean Brady holds the clearer grappling edge Sean Brady has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Sean Brady shows the clearer activity edge
  • Sean Brady shows the clearer grappling edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Welterweight
guarded
Joel Alvarez
lean
vs
Yaroslav Amosov
calibrated lean
Joel Alvarez
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Joel Alvarez
66%
Yaroslav Amosov
34%
why the model leans this way

Joel Alvarez projects ahead on current measurable form and matchup profile. Yaroslav Amosov holds the clearer grappling edge Yaroslav Amosov has shown more recent division stability Division-transition caution: Joel Alvarez is only in a second fight in this division; Yaroslav Amosov is only in a second fight in this division. Empirical calibration applied from historical outcome bins.

  • Yaroslav Amosov shows the clearer grappling edge
Risk flags
  • Yaroslav Amosov low recent sample
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Joel Alvarez is only in a second fight in this division
  • Yaroslav Amosov is only in a second fight in this division
  • At least one fighter has thin recent sample coverage behind the proxy stats
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Lightweight
guarded
Jeremy Stephens
vs
King Green
lean
calibrated lean
King Green
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Jeremy Stephens
34%
King Green
66%
why the model leans this way

King Green projects ahead on current measurable form and matchup profile. King Green holds the clearer form edge King Green holds the clearer activity edge King Green has the stronger proven sample in this division Division-transition caution: At least one fighter has thin recent sample coverage behind the proxy stats; The matchup has uneven recent sample coverage between the fighters. Empirical calibration applied from historical outcome bins.

  • King Green shows the clearer form edge
  • King Green shows the clearer activity edge
Risk flags
  • Jeremy Stephens long layoff
  • Jeremy Stephens low recent sample
Uncertainty / caveats
  • At least one fighter has thin recent sample coverage behind the proxy stats
  • The matchup has uneven recent sample coverage between the fighters
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Lightweight
guarded
Mateusz Rebecki
vs
Grant Dawson
lean
calibrated lean
Grant Dawson
51% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Mateusz Rebecki
49%
Grant Dawson
51%
why the model leans this way

Grant Dawson projects ahead on current measurable form and matchup profile. Grant Dawson holds the clearer form edge Grant Dawson has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Grant Dawson shows the clearer form edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Lightweight
guarded
Jared Gordon
vs
Jim Miller
lean
calibrated lean
Jim Miller
51% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Jared Gordon
49%
Jim Miller
51%
why the model leans this way

Jim Miller projects ahead on current measurable form and matchup profile. Jared Gordon holds the clearer activity edge Jim Miller holds the clearer grappling edge Jim Miller has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Jared Gordon shows the clearer activity edge
  • Jim Miller shows the clearer grappling edge
Risk flags
  • Jim Miller long layoff
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Featherweight
guarded
Pat Sabatini
vs
William Gomis
lean
calibrated lean
William Gomis
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Pat Sabatini
34%
William Gomis
66%
why the model leans this way

William Gomis projects ahead on current measurable form and matchup profile. Pat Sabatini holds the clearer grappling edge Pat Sabatini has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Pat Sabatini shows the clearer grappling edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
Flyweight
guarded
Jose Ochoa
vs
Clayton Carpenter
lean
calibrated lean
Clayton Carpenter
51% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Jose Ochoa
49%
Clayton Carpenter
51%
why the model leans this way

Clayton Carpenter projects ahead on current measurable form and matchup profile. Clayton Carpenter has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.
UFC Flyweight Title
guarded
Joshua Van
lean
vs
Tatsuro Taira
calibrated lean
Joshua Van
66% calibrated win probability for the current lean, but guarded by volatility or weak-regime caveats
Joshua Van
66%
Tatsuro Taira
34%
why the model leans this way

Joshua Van projects ahead on current measurable form and matchup profile. Tatsuro Taira holds the clearer grappling edge Joshua Van has the stronger proven sample in this division Empirical calibration applied from historical outcome bins.

  • Tatsuro Taira shows the clearer grappling edge
Risk flags
  • Both fighters carry high finish volatility
Uncertainty / caveats
  • High-volatility matchup: finish variance is elevated and certainty should be discounted.
  • Probability is shown through the calibrated presentation layer built from baseline-v4-clean.