Beginner Traceurs
New athletes learning their first vaults and precisions. The system flags landing mechanics and risk patterns before they become habits.
Upload your training videos and receive instant AI-powered feedback designed to help you improve technique, efficiency, landing mechanics, and movement quality across every parkour discipline.
Obstacle IQ is an AI movement coach built for traceurs, freerunners, and parkour athletes. You film an attempt with a phone, upload the clip, and within minutes you get a structured analysis that breaks the movement into its three phases — takeoff, flight, and landing — and grades each one.
Parkour is one of the only disciplines where the cost of a single bad rep is a hard landing on concrete. That makes objective feedback uniquely valuable: spotting a knee-collapse pattern after 12 reps is much cheaper than spotting it after 1,200 reps and a torn meniscus. The system is designed to surface those patterns before they become injuries.
Most users upload between three and eight clips per session — a precision jump, a vault, a cat leap, a wall run, and maybe a flow line through the spot. Over a few weeks the system builds a movement library you can scroll through to watch technique evolve.
Obstacle IQ is built for parkour athletes at every level — from beginners building their first technical reps to competitors refining podium-level execution.
New athletes learning their first vaults and precisions. The system flags landing mechanics and risk patterns before they become habits.
Athletes blending parkour with flips, twists, and creative lines who need feedback on both technique and flow.
Competitors prepping for World Chase Tag, Red Bull Art of Motion, or local jams where line efficiency separates podiums from finals.
Parkour creators who already film everything — Obstacle IQ turns the footage you already shoot into structured coaching feedback.
Every clip is broken into the technical sub-components a great Parkour coach would grade — the same checklist they would run mentally, applied to every rep instead of the ones they happen to be watching.
Takeoff foot position, knee bend angle, arm swing contribution, flight arc, and landing stability on the target.
Dive angle, hand placement on the obstacle, hip clearance, and exit-step rhythm.
Approach line, single-hand plant timing, leg-cross efficiency, and continuation speed off the obstacle.
Plant foot drive, hip-to-wall distance, second-step extension, and top-out grip mechanics.
Air shape, hand placement on the wall, foot smear vs. flag, and stick-vs-climb recovery.
Pause detection, regrip events, and overall efficiency of a multi-movement line through a spot.
Step rhythm between elements, energy loss across consecutive movements, and consistency under fatigue.
Parkour movement is fast, asymmetric, and unforgiving. The eye cannot reliably score what your knee did between frames 8 and 14 of a precision landing — but a frame-by-frame analysis can.
Self-review hits a hard ceiling. You can tell that a precision felt 'a bit off,' but you usually can't see that you planted the takeoff foot 8 degrees off-axis, which is why the landing felt unstable.
Objective feedback also removes the emotional weight of a session. Instead of replaying a sketchy landing in your head all day, you get a written report with specific timestamps and specific drills.
Most importantly: feedback at the time of the rep accelerates skill acquisition. A correction that lands two minutes after the attempt is dramatically more useful than the same correction three days later.
These are the patterns that appear most frequently in Parkour clips uploaded for review — and the ones that quietly cost athletes the most progress.
If the landing makes a loud thud, energy is being absorbed by joints instead of muscles. The fix is rarely 'land softer' — it is usually 'bend the knees earlier' and 'use the hips, not the shins.' Video review shows this immediately.
Athletes commonly plant the takeoff foot 5–10cm short of where they think they did, then over-rotate in the air to compensate. The AI overlay surfaces this gap clearly.
On flow lines, every regrip and every micro-pause is energy thrown away. Trained athletes look fluid because the regrips have been engineered out, not because they are mystically gifted.
Knees tracking inward on landing is the single biggest preventable injury pattern in parkour. The system flags it on every clip and prescribes hip-stability drills if the pattern repeats.
Eye fixation on the takeoff foot collapses the upper body and shortens the jump. Cue: look at the landing target through the entire jump.
Strong athletes brute-force jumps that better technique would make trivial. The cost is shoulder, knee, and ankle wear that catches up by the third year of training.
Clean approach and confident takeoff. Landing is functional but the knees track inward by approximately 6 degrees, and the right foot lands 40ms before the left, costing stick stability.
In parkour, every landing is a structural test. The athletes who train for ten years without major injury are almost always the athletes whose landings look quiet. Obstacle IQ tracks landing posture, knee tracking, hip alignment, and foot contact symmetry on every clip — the same checklist a thoughtful parkour coach would run in their head, except applied to every single rep instead of the ones they happened to be watching.
A clean flow line on a fresh body is a different movement than the same flow line on rep 12. The system tracks both pristine and fatigued versions of the same line and shows you exactly where the breakdown happens. Most athletes find that their flow lines crumble in the same predictable spot every time, and the fix is almost never a strength issue — it is a regrip habit that becomes visible only on camera.
Most traceurs are self-taught. That is a feature of the discipline. But self-coaching has predictable blind spots, and modern AI movement analysis closes most of them without compromising the autonomy that makes the sport addictive. The goal is not to standardize parkour — it is to make sure your tenth year of training looks better than your second, instead of worse.
Yes. Parkour is one of the highest-value disciplines for AI movement coaching because the technique-vs-injury margin is narrow. Frame-by-frame review surfaces patterns — knee valgus, asymmetric foot contact, hip collapse — that the athlete cannot see from inside the rep.
Obstacle IQ focuses on parkour fundamentals — precisions, vaults, wall runs, cat leaps, and flow. Tumbling and aerial tricks are evaluated for landing mechanics but not scored on aesthetic execution.
A side-profile clip from 15–25 feet away captures takeoff, flight, and landing in the same frame. For vaults, a second angle from behind the obstacle adds value.
Both. Beginners benefit the most because they avoid building bad landing habits. Advanced athletes use it to fine-tune flow lines and identify the 100ms of wasted energy that separates clean lines from rough ones.
No. A modern phone shooting 60fps at 1080p is sufficient. A tripod helps for repeatable drill work but is not required.
Obstacle IQ analyzes movement, not environments. It does not measure rails, gaps, or surface conditions. Risk assessment of the spot itself is always the athlete's responsibility.
It is a complement, not a replacement. A great coach sees you once a week. Obstacle IQ sees every clip you upload, every day, with consistent criteria and zero fatigue.
Yes. Every report has a shareable summary you can send to a coach so the next in-person session can move faster.
Yes. Freerunning movements are analyzed using the same takeoff-flight-landing framework. Aesthetic creativity is not scored, but landing mechanics and movement efficiency are.
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A coaching framework for reviewing Parkour footage — what to watch, in what order, and how to score each phase.
A first-90-days drill library for new Parkour athletes — built on landing, balance, and vault fundamentals.
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