Stat Leaders
See who leads every division. Rank UFC fighters by CCR and TSR, striking, grappling, and control—with every metric measured against their weight class peers.
Michal Figlak
Lightweight
98.3
CCR
Li Jingliang
Welterweight
98.2
CCR
Sean Sharaf
Heavyweight
98.2
CCR
Ange Loosa
Welterweight
98.1
CCR
Makhmud Muradov
Middleweight
98.1
CCR
Billy Quarantillo
Featherweight
98.1
CCR
Khusein Askhabov
Featherweight
98.1
CCR
Chris Weidman
Catch Weight
98.0
CCR
Damon Jackson
Lightweight
98.0
CCR
Ramazan Emeev
Welterweight
98.0
CCR
Yanis Ghemmouri
Bantamweight
97.9
CCR
Bolaji Oki
Lightweight
97.9
CCR
Austin Hubbard
Lightweight
97.8
CCR
Josh Fremd
Middleweight
97.8
CCR
Ante Delija
Heavyweight
97.8
CCR
Ariane da Silva
Women's Flyweight
97.8
CCR
Timmy Cuamba
Bantamweight
97.8
CCR
Paul Craig
Light Heavyweight
97.8
CCR
Cory McKenna
Women's Strawweight
97.8
CCR
TJ Dillashaw
Bantamweight
97.7
CCR
Ibo Aslan
Light Heavyweight
97.6
CCR
Jennifer Maia
Women's Flyweight
97.6
CCR
Song Kenan
Welterweight
97.6
CCR
Josefine Knutsson
Women's Strawweight
97.6
CCR
Marnic Mann
Women's Strawweight
97.5
CCR
Elise Reed
Women's Strawweight
97.5
CCR
Nicolae Negumereanu
Light Heavyweight
97.4
CCR
Danyelle Wolf
Women's Featherweight
97.4
CCR
Manuel Torres
Lightweight
97.4
CCR
Viktoriia Dudakova
Women's Strawweight
97.4
CCR
Nate Diaz
Welterweight
97.2
CCR
Manolo Zecchini
Featherweight
97.2
CCR
Bea Malecki
Women's Bantamweight
97.2
CCR
Ramon Taveras
Featherweight
97.2
CCR
Rhys McKee
Welterweight
97.2
CCR
Bruna Brasil
Women's Strawweight
97.1
CCR
Dan Argueta
Bantamweight
97.1
CCR
Anthony Smith
Light Heavyweight
97.1
CCR
Benoit Saint Denis
Lightweight
97.1
CCR
Mounir Lazzez
Welterweight
97.0
CCR
Amanda Ribas
Women's Strawweight
97.0
CCR
Ricardo Ramos
Featherweight
97.0
CCR
Maxim Grishin
Light Heavyweight
97.0
CCR
Josh Culibao
Featherweight
96.9
CCR
Zhang Mingyang
Light Heavyweight
96.8
CCR
Bruno Souza
Featherweight
96.8
CCR
Melsik Baghdasaryan
Featherweight
96.8
CCR
Cameron Saaiman
Bantamweight
96.8
CCR
Jose Johnson
Flyweight
96.7
CCR
Cheyanne Vlismas
Women's Strawweight
96.7
CCR
| Rank | Fighter | Weight class | CCR | Percentile | Percentile per weight class | SLpM | TD / min |
|---|---|---|---|---|---|---|---|
| 651 | Michal Figlak | Lightweight | 98.3 | 41.7% | 40.7% | 4.0 | 0.0 |
| 652 | Li Jingliang | Welterweight | 98.2 | 41.6% | 39.6% | 4.3 | 0.1 |
| 653 | Sean Sharaf | Heavyweight | 98.2 | 41.5% | 36.8% | 7.4 | 0.1 |
| 654 | Ange Loosa | Welterweight | 98.1 | 41.4% | 38.8% | 5.7 | 0.2 |
| 655 | Makhmud Muradov | Middleweight | 98.1 | 41.3% | 43.5% | 2.9 | 0.4 |
| 656 | Billy Quarantillo | Featherweight | 98.1 | 41.3% | 42.7% | 7.8 | 0.1 |
| 657 | Khusein Askhabov | Featherweight | 98.1 | 41.2% | 42.0% | 2.0 | 0.0 |
| 658 | Chris Weidman | Catch Weight | 98.0 | 41.1% | 42.9% | 3.4 | 0.0 |
| 659 | Damon Jackson | Lightweight | 98.0 | 41.0% | 40.0% | 3.2 | 0.2 |
| 660 | Ramazan Emeev | Welterweight | 98.0 | 40.9% | 38.1% | 2.7 | 0.2 |
| 661 | Yanis Ghemmouri | Bantamweight | 97.9 | 40.8% | 37.3% | 2.3 | 0.0 |
| 662 | Bolaji Oki | Lightweight | 97.9 | 40.7% | 39.3% | 6.2 | 0.1 |
| 663 | Austin Hubbard | Lightweight | 97.8 | 40.6% | 38.6% | 4.3 | 0.2 |
| 664 | Josh Fremd | Middleweight | 97.8 | 40.5% | 42.6% | 2.5 | 0.0 |
| 665 | Ante Delija | Heavyweight | 97.8 | 40.4% | 35.5% | 4.3 | 0.0 |
| 666 | Ariane da Silva | Women's Flyweight | 97.8 | 40.4% | 49.1% | 4.9 | 0.0 |
| 667 | Timmy Cuamba | Bantamweight | 97.8 | 40.3% | 36.7% | 2.9 | 0.1 |
| 668 | Paul Craig | Light Heavyweight | 97.8 | 40.2% | 49.4% | 2.4 | 0.0 |
| 669 | Cory McKenna | Women's Strawweight | 97.8 | 40.1% | 50.7% | 2.6 | 0.2 |
| 670 | TJ Dillashaw | Bantamweight | 97.7 | 40.0% | 36.0% | 3.5 | 0.1 |
| 671 | Ibo Aslan | Light Heavyweight | 97.6 | 39.9% | 48.1% | 5.5 | 0.0 |
| 672 | Jennifer Maia | Women's Flyweight | 97.6 | 39.8% | 47.4% | 5.1 | 0.0 |
| 673 | Song Kenan | Welterweight | 97.6 | 39.7% | 37.4% | 4.6 | 0.0 |
| 674 | Josefine Knutsson | Women's Strawweight | 97.6 | 39.6% | 49.3% | 5.1 | 0.1 |
| 675 | Marnic Mann | Women's Strawweight | 97.5 | 39.6% | 47.9% | 1.3 | 0.1 |
| 676 | Elise Reed | Women's Strawweight | 97.5 | 39.5% | 46.6% | 3.4 | 0.0 |
| 677 | Nicolae Negumereanu | Light Heavyweight | 97.4 | 39.4% | 46.8% | 4.5 | 0.1 |
| 678 | Danyelle Wolf | Women's Featherweight | 97.4 | 39.3% | 66.7% | 1.3 | 0.0 |
| 679 | Manuel Torres | Lightweight | 97.4 | 39.2% | 37.9% | 6.0 | 0.1 |
| 680 | Viktoriia Dudakova | Women's Strawweight | 97.4 | 39.1% | 45.2% | 3.5 | 0.1 |
| 681 | Nate Diaz | Welterweight | 97.2 | 39.0% | 36.7% | 5.7 | 0.0 |
| 682 | Manolo Zecchini | Featherweight | 97.2 | 38.9% | 41.3% | 3.7 | 0.0 |
| 683 | Bea Malecki | Women's Bantamweight | 97.2 | 38.8% | 40.8% | 7.1 | 0.0 |
| 684 | Ramon Taveras | Featherweight | 97.2 | 38.7% | 40.6% | 3.9 | 0.0 |
| 685 | Rhys McKee | Welterweight | 97.2 | 38.7% | 36.0% | 3.9 | 0.0 |
| 686 | Bruna Brasil | Women's Strawweight | 97.1 | 38.6% | 43.8% | 2.4 | 0.1 |
| 687 | Dan Argueta | Bantamweight | 97.1 | 38.5% | 35.3% | 2.5 | 0.3 |
| 688 | Anthony Smith | Light Heavyweight | 97.1 | 38.4% | 45.5% | 3.6 | 0.0 |
| 689 | Benoit Saint Denis | Lightweight | 97.1 | 38.3% | 37.2% | 5.6 | 0.3 |
| 690 | Mounir Lazzez | Welterweight | 97.0 | 38.2% | 35.3% | 9.5 | 0.0 |
| 691 | Amanda Ribas | Women's Strawweight | 97.0 | 38.1% | 42.5% | 4.3 | 0.1 |
| 692 | Ricardo Ramos | Featherweight | 97.0 | 38.0% | 39.9% | 2.6 | 0.1 |
| 693 | Maxim Grishin | Light Heavyweight | 97.0 | 37.9% | 44.2% | 3.7 | 0.0 |
| 694 | Josh Culibao | Featherweight | 96.9 | 37.8% | 39.2% | 3.7 | 0.0 |
| 695 | Zhang Mingyang | Light Heavyweight | 96.8 | 37.8% | 42.9% | 6.6 | 0.0 |
| 696 | Bruno Souza | Featherweight | 96.8 | 37.7% | 38.5% | 3.7 | 0.0 |
| 697 | Melsik Baghdasaryan | Featherweight | 96.8 | 37.6% | 37.8% | 4.4 | 0.0 |
| 698 | Cameron Saaiman | Bantamweight | 96.8 | 37.5% | 34.7% | 5.5 | 0.1 |
| 699 | Jose Johnson | Flyweight | 96.7 | 37.4% | 33.8% | 2.4 | 0.1 |
| 700 | Cheyanne Vlismas | Women's Strawweight | 96.7 | 37.3% | 41.1% | 5.7 | 0.0 |
Analytics guide
CCR
What it calculates
Current Competitiveness Rating (CCR): a composite score—like an Elo rating in chess—that evaluates advanced striking, grappling, pace, and opponent-quality stats into one number.
Why it matters
Weights recent performance much more heavily than older fights and incorporates factors like age. Use it to see who is fighting at an elite level right now.
TSR
What it calculates
True Skill Rating (TSR): the same composite approach applied across a fighter’s full UFC body of work, like an Elo rating built from advanced stats.
Why it matters
Does not overweight recency or adjust for age—it is a pure career evaluative metric. Helpful for separating sustained elite careers from short hot streaks.
SLpM
What it calculates
Total Significant Strikes Landed ÷ Total Fight Time (minutes)
Why it matters
Captures offensive pace and sustained scoring output — high SLpM forces opponents to fight at your tempo.
SApM
What it calculates
Total Significant Strikes Absorbed ÷ Total Fight Time (minutes)
Why it matters
Shows defensive efficiency and risk exposure — low SApM usually means better defense, distance management, and fewer damaging exchanges.
KD/M
What it calculates
Total Knockdowns ÷ Total Fight Time (minutes)
Why it matters
Measures a fighter’s ability to create high-impact, fight-changing moments that swing rounds or lead to finishes.
TD/M
What it calculates
Total Takedowns Landed ÷ Total Fight Time (minutes)
Why it matters
Signals wrestling pace and phase control — fighters who can reliably force grappling exchanges can neutralize dangerous strikers.
CTRL
What it calculates
Total Control Time ÷ Total Fight Time (minutes)
Why it matters
Quantifies positional dominance and round-winning leverage — control time often correlates with judges’ scoring and opponent suppression.
SUB/M
What it calculates
Total Submission Attempts ÷ Total Fight Time (minutes)
Why it matters
Reflects finishing threat on the mat — frequent submission attacks force defensive reactions that open up control and damage.
Rev
What it calculates
Total Reversals ÷ Total Fight Time (minutes)
Why it matters
Highlights scrambling and escape ability — reversals turn bad positions into scoring opportunities and can flip momentum.
C/15
What it calculates
(Total Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Standardizes grappling control to a 15-minute baseline so fighters with different bout lengths can be compared fairly.
TOP/15
What it calculates
(Total Top Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Separates high-quality control (top position) from other control contexts — strong top control is a reliable path to winning rounds.
CLN/15
What it calculates
(Total Clinch Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Measures fence control and pace management — clinch time can mute opponent offense and bank scoring minutes.
GRD/15
What it calculates
(Total Ground Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Shows takedown follow-through and top pressure — ground control often creates long stretches of safe scoring and attrition.
CAGE
What it calculates
(Total Cage Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Quantifies time spent driving position against the fence — useful for understanding style matchups and opponent disruption.
BACK
What it calculates
(Total Back Control Time ÷ Total Fight Time) × 15 minutes
Why it matters
Back control is premium dominance — it strongly predicts submission threat and long, uncontested control sequences.
CHIN
What it calculates
Model score (0–100): durability under damaging strikes
Why it matters
A quick durability signal — higher scores suggest a fighter can survive danger and remain competitive deep into fights.
TDAtt
What it calculates
Career total takedown attempts (UFC bouts)
Why it matters
Represents grappling intent and game-planning tendency — high attempt totals usually indicate a wrestler-first approach.
TDLnd
What it calculates
Career total takedowns landed (UFC bouts)
Why it matters
Proof of conversion and control potential — landed takedowns often precede control time, damage, and submission attempts.
TDAg
What it calculates
Career total opponent takedown attempts faced (UFC bouts)
Why it matters
Shows how often opponents choose to wrestle them — a proxy for perceived defensive striking threat or exploitable takedown defense.
TDDef
What it calculates
Career total opponent takedown attempts defended (UFC bouts)
Why it matters
Highlights defensive wrestling volume — strong defense keeps fights in a preferred phase and preserves striking efficiency.