u/FightSignal
▲ 326 r/mmamemes
Dagestan sees an Irishman standing and takes it personally
u/FightSignal — 3 days ago
▲ 1 r/UFCLabs
Dern vs Robertson:
Dern's striking accuracy went from the low 30s to 41%. Her takedown defense jumped from 0% to 38%. She used to just look for submissions on the ground but now she throws ground strikes too. Her submission attempts dropped but her ground damage went up
Robertson's biggest weakness was takedown defense at 16% but now it's 39%. Plus she learned how to strike, doubled her distance strikes from 0.7 to 1.4 per min and added KO wins. Her fights also got 4+ mins longer on average and she's won way more decisions
So both got more complete. Dern's better at defending takedowns and striking. Robertson can stand with you and go the distance.
Robertson's takedown accuracy was probably never great anyway so Dern's defense doesn't matter as much. But Robertson's striking is still not as sharp as Dern's.
Dern probably out-strikes her but Robertson's tough and won't get taken down as easy anymore. Who you got?
u/FightSignal — 6 days ago
▲ 7 r/UFCLabs
Magomed Ankalaev vs Bogdan Guskov
Ank's takedown defense is at 87.5% and he added a leg kick game (90% accuracy, almost 1/min).
His striking gets more accurate as the fight goes on (improves like 7% by round 3)
Guskov used to absorb 6.9 strikes a min but now it's 4.09. His striking doubled from 2.1 to 4.5 per min and his accuracy went from 32% to 55%
Plus he added ground strikes and submissions and went from nothing to 1.5 per min on the mat
So Guskov got way better at everything. But Ank's takedown defense is insane and so does his leg kicks
If this goes later rounds, Ank probably gets better. Guskov needs to land early before those leg kicks start breaking him down
u/FightSignal — 29 days ago
▲ 1 r/UFCposting
Went down a rabbit hole trying to understand fight predictive analytics
Was a bit curious how these UFC prediction models actually work so I spent some time reading about it
Not a data guy at all but here's what I picked up
Most fight predictive analytics come from a few places:
Old fight data: career stats, how guys finish fights, striking numbers, wrestling stats. Every model uses this. The problem is it treats a fight from 5 years ago the same as last month which doesn't really make sense.
Line movement: when a fight goes from -150 to -200 a day before the card, it means sharp bettors are moving it. These are people with actual information. Some models just ignore this completely which seems like a waste.
Expert opinions: These include YouTube analysts, MMA writers, coaches on podcasts. The tricky part is figuring out who's actually good vs who just sounds confident. Following count means nothing here.
What people are saying: Reddit, Twitter, Tapology. Mostly noise but when everyone is clearly wrong about a fight that gap can be pretty useful as a signal on its own.
The tools I found most interesting are the ones that try to combine all of this and weight each source by how reliable it's actually been historically. Rather than just treating a random Reddit comment the same as an analyst who's been calling fights accurately for years.
BTW, while doing the research, I came across FightSignal and it seems to be doing something along these lines. Pulling in expert opinions, community sentiment, line movement and combining them rather than running one model in isolation.
Anyone here actually worked with UFC data or built anything like this?
u/FightSignal — 1 month ago
▲ 606 r/mmamemes
No UFC this weekend, Mexico fans knocking each other out at the World Cup lol
u/FightSignal — 2 months ago