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.
Sean Brady
Welterweight
129.7
CCR
Kamaru Usman
Middleweight
129.7
CCR
Bo Nickal
Middleweight
129.6
CCR
Jack Della Maddalena
Welterweight
129.3
CCR
Alexander Hernandez
Lightweight
129.3
CCR
Sam Patterson
Welterweight
128.8
CCR
Jakub Wiklacz
Bantamweight
128.8
CCR
Alex Perez
Flyweight
128.7
CCR
Cory Sandhagen
Bantamweight
128.4
CCR
Daniel Marcos
Bantamweight
128.3
CCR
Song Yadong
Bantamweight
128.3
CCR
Ateba Gautier
Middleweight
128.3
CCR
Marcus McGhee
Bantamweight
128.0
CCR
Joe Pyfer
Middleweight
127.9
CCR
Arnold Allen
Featherweight
127.9
CCR
Ikram Aliskerov
Middleweight
127.8
CCR
Bia Mesquita
Women's Bantamweight
127.4
CCR
Dustin Jacoby
Light Heavyweight
127.4
CCR
Mitch Raposo
Flyweight
127.3
CCR
Jacobe Smith
Welterweight
127.2
CCR
Brando Pericic
Heavyweight
127.1
CCR
Yan Xiaonan
Women's Strawweight
126.9
CCR
Dan Hooker
Lightweight
126.7
CCR
Gregory Rodrigues
Middleweight
126.6
CCR
Valter Walker
Heavyweight
126.6
CCR
Mick Parkin
Heavyweight
126.4
CCR
Brandon Royval
Flyweight
125.9
CCR
Payton Talbott
Bantamweight
125.8
CCR
Jacqueline Cavalcanti
Women's Bantamweight
125.6
CCR
Baisangur Susurkaev
Middleweight
125.5
CCR
Miranda Maverick
Women's Flyweight
125.3
CCR
Bogdan Guskov
Light Heavyweight
125.2
CCR
Stipe Miocic
Heavyweight
125.2
CCR
Alexia Thainara
Women's Strawweight
125.1
CCR
Mairon Santos
Featherweight
125.1
CCR
Kaan Ofli
Featherweight
125.0
CCR
Myktybek Orolbai
Welterweight
124.8
CCR
Daniil Donchenko
Welterweight
124.6
CCR
Kevin Vallejos
Featherweight
124.6
CCR
Sergei Pavlovich
Heavyweight
124.5
CCR
Caio Borralho
Middleweight
124.5
CCR
Cam Rowston
Middleweight
124.4
CCR
Elijah Smith
Bantamweight
124.3
CCR
Anthony Hernandez
Middleweight
124.2
CCR
Ramiz Brahimaj
Welterweight
124.1
CCR
Lerryan Douglas
Featherweight
124.0
CCR
Cody Haddon
Bantamweight
124.0
CCR
Rinya Nakamura
Bantamweight
123.6
CCR
Mike Malott
Welterweight
123.5
CCR
Alden Coria
Flyweight
123.5
CCR
| Rank | Fighter | Weight class | CCR | Percentile | Percentile per weight class | SLpM | TD / min |
|---|---|---|---|---|---|---|---|
| 101 | Sean Brady | Welterweight | 129.7 | 91.0% | 89.2% | 3.7 | 0.3 |
| 102 | Kamaru Usman | Middleweight | 129.7 | 90.9% | 93.9% | 3.2 | 0.1 |
| 103 | Bo Nickal | Middleweight | 129.6 | 90.9% | 93.0% | 3.4 | 0.2 |
| 104 | Jack Della Maddalena | Welterweight | 129.3 | 90.8% | 88.5% | 5.1 | 0.0 |
| 105 | Alexander Hernandez | Lightweight | 129.3 | 90.7% | 91.0% | 4.6 | 0.0 |
| 106 | Sam Patterson | Welterweight | 128.8 | 90.6% | 87.8% | 2.6 | 0.1 |
| 107 | Jakub Wiklacz | Bantamweight | 128.8 | 90.5% | 92.7% | 3.4 | 0.0 |
| 108 | Alex Perez | Flyweight | 128.7 | 90.4% | 91.9% | 3.8 | 0.1 |
| 109 | Cory Sandhagen | Bantamweight | 128.4 | 90.3% | 92.0% | 4.4 | 0.1 |
| 110 | Daniel Marcos | Bantamweight | 128.3 | 90.2% | 91.3% | 4.8 | 0.1 |
| 111 | Song Yadong | Bantamweight | 128.3 | 90.1% | 90.7% | 4.3 | 0.1 |
| 112 | Ateba Gautier | Middleweight | 128.3 | 90.0% | 92.2% | 4.0 | 0.0 |
| 113 | Marcus McGhee | Bantamweight | 128.0 | 90.0% | 90.0% | 5.4 | 0.0 |
| 114 | Joe Pyfer | Middleweight | 127.9 | 89.9% | 91.3% | 3.5 | 0.1 |
| 115 | Arnold Allen | Featherweight | 127.9 | 89.8% | 91.6% | 4.2 | 0.1 |
| 116 | Ikram Aliskerov | Middleweight | 127.8 | 89.7% | 90.4% | 5.7 | 0.2 |
| 117 | Bia Mesquita | Women's Bantamweight | 127.4 | 89.6% | 85.7% | 4.5 | 0.2 |
| 118 | Dustin Jacoby | Light Heavyweight | 127.4 | 89.5% | 92.2% | 6.5 | 0.0 |
| 119 | Mitch Raposo | Flyweight | 127.3 | 89.4% | 90.5% | 1.8 | 0.1 |
| 120 | Jacobe Smith | Welterweight | 127.2 | 89.3% | 87.1% | 6.9 | 0.3 |
| 121 | Brando Pericic | Heavyweight | 127.1 | 89.2% | 89.5% | 11.0 | 0.0 |
| 122 | Yan Xiaonan | Women's Strawweight | 126.9 | 89.1% | 91.8% | 3.4 | 0.1 |
| 123 | Dan Hooker | Lightweight | 126.7 | 89.1% | 90.3% | 4.5 | 0.0 |
| 124 | Gregory Rodrigues | Middleweight | 126.6 | 89.0% | 89.6% | 5.6 | 0.1 |
| 125 | Valter Walker | Heavyweight | 126.6 | 88.9% | 88.2% | 2.0 | 0.4 |
| 126 | Mick Parkin | Heavyweight | 126.4 | 88.8% | 86.8% | 4.7 | 0.1 |
| 127 | Brandon Royval | Flyweight | 125.9 | 88.7% | 89.2% | 5.9 | 0.1 |
| 128 | Payton Talbott | Bantamweight | 125.8 | 88.6% | 89.3% | 5.9 | 0.1 |
| 129 | Jacqueline Cavalcanti | Women's Bantamweight | 125.6 | 88.5% | 83.7% | 5.3 | 0.0 |
| 130 | Baisangur Susurkaev | Middleweight | 125.5 | 88.4% | 88.7% | 6.0 | 0.2 |
| 131 | Miranda Maverick | Women's Flyweight | 125.3 | 88.3% | 84.2% | 2.8 | 0.1 |
| 132 | Bogdan Guskov | Light Heavyweight | 125.2 | 88.3% | 90.9% | 4.6 | 0.0 |
| 133 | Stipe Miocic | Heavyweight | 125.2 | 88.2% | 85.5% | 2.6 | 0.0 |
| 134 | Alexia Thainara | Women's Strawweight | 125.1 | 88.1% | 90.4% | 3.7 | 0.3 |
| 135 | Mairon Santos | Featherweight | 125.1 | 88.0% | 90.9% | 3.3 | 0.0 |
| 136 | Kaan Ofli | Featherweight | 125.0 | 87.9% | 90.2% | 2.5 | 0.0 |
| 137 | Myktybek Orolbai | Welterweight | 124.8 | 87.8% | 86.3% | 2.8 | 0.6 |
| 138 | Daniil Donchenko | Welterweight | 124.6 | 87.7% | 85.6% | 8.1 | 0.0 |
| 139 | Kevin Vallejos | Featherweight | 124.6 | 87.6% | 89.5% | 5.7 | 0.1 |
| 140 | Sergei Pavlovich | Heavyweight | 124.5 | 87.5% | 84.2% | 4.2 | 0.0 |
| 141 | Caio Borralho | Middleweight | 124.5 | 87.4% | 87.8% | 3.3 | 0.1 |
| 142 | Cam Rowston | Middleweight | 124.4 | 87.4% | 87.0% | 5.5 | 0.1 |
| 143 | Elijah Smith | Bantamweight | 124.3 | 87.3% | 88.7% | 3.7 | 0.1 |
| 144 | Anthony Hernandez | Middleweight | 124.2 | 87.2% | 86.1% | 4.5 | 0.4 |
| 145 | Ramiz Brahimaj | Welterweight | 124.1 | 87.1% | 84.9% | 2.0 | 0.2 |
| 146 | Lerryan Douglas | Featherweight | 124.0 | 87.0% | 88.8% | 8.2 | 0.0 |
| 147 | Cody Haddon | Bantamweight | 124.0 | 86.9% | 88.0% | 8.9 | 0.2 |
| 148 | Rinya Nakamura | Bantamweight | 123.6 | 86.8% | 87.3% | 2.7 | 0.2 |
| 149 | Mike Malott | Welterweight | 123.5 | 86.7% | 84.2% | 3.9 | 0.1 |
| 150 | Alden Coria | Flyweight | 123.5 | 86.6% | 87.8% | 4.7 | 0.1 |
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.