Jarvis Jorkmaxx

Jarvis Jorkmaxx — CS2 Stats

DK76561199238349782[U:1:1278084054]Steam profile ↗✓ No bans

161Tracked matches63%Win rate2022Tracked since
CSDB Rating6.8 SolidAll-Rounder
Ladder ranks via Leetify

Performance scores

Aim83
Positioning58
Utility50

0–100 skill scores via Leetify.

Recent form

STEADY57–38–5Last 10057%Win rateWWWLLWTWLT

Last 10 vs previous 10: −10pp win rate · −0.06 avg rating · −2.6pp headshot accuracy · +51ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 3–2 · 60% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 31%
  • Avg reaction 599ms

Last 10

  • 5–3–2 · 50% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 30%
  • Avg reaction 614ms

Last 20

  • 11–6–3 · 55% win rate
  • Avg rating 0.04
  • Avg headshot accuracy 31%
  • Avg reaction 589ms

Newest first, from the last 100 tracked matches. Each block is its own sample — one result moves a 5-match win rate by 20 points.

Player DNA

Primary style: All-Rounder — No style dimension stands clear of the others in this profile.

Aim8.3
Utility5.0
Positioning5.8
Opening Duels4.2

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

What this cannot see yet: which weapons you use — so CSDB cannot identify an AWPer, and no style here implies a rifle or a sniper. It also cannot see how often you take opening duels, only how often you win them, nor where you hold, so roles that depend on those (entry, lurk, anchor) are deliberately absent rather than guessed. All of it needs round-by-round demo data, which is the next thing being built.

Your pro match

m0NESY

Plays most like m0NESY 95% playstyle similarity

Most alike: aim profile, utility contribution.

Where you differ: lower positioning profile; lower opening-duel success.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

Utility. Utility contribution runs far behind the mechanical game — the cheapest rating gain on this profile is thrown, not aimed.

T-side openings. Opening success drops from 54% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 589ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim8.3
Positioning5.8
Utility5.0
Mechanics7.0
Opening Duels3.8
Win Impact9.3

Composite 6.8/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×1.00 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating0.04−0.04
first ⅓ avg 0.07 → last ⅓ avg 0.04
Reaction time598ms−20ms
first ⅓ avg 619ms → last ⅓ avg 598ms
Headshot accuracy29.7%+3.5%
first ⅓ avg 26.3% → last ⅓ avg 29.7%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Personal bests

0.23Best match rating · 13–0 · office, 6 Feb →
100%Best headshot accuracy · 13–6 · anubis, 12 Sept →
391msFastest reaction time · 13–8 · office, 25 Aug →
16–0Biggest win · train, 29 Oct →

Across the last 100 tracked matches.

Highlights

11Longest win streak
W3Current streak
6–10In matches decided by ≤2 rounds
39Overtime games

Map breakdown

overpassBest map · 80% over 10infernoWeakest map · 42% over 24
MapGradePlayedRecordWin rateAvg rating
officeC2511–1444%0.06
infernoC2410–1442%0.05
mirageS1410–471%0.04
overpassS108–280%0.06
nukeA95–456%0.06
dust2A74–357%0.07
ancientS54–180%0.02
anubis—33–0100%0.02
vertigo—21–150%-0.03
train—11–0100%0.06

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (42% over 24). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

29.2%Headshot accuracy
35.0%Accuracy (enemy spotted)
37.7%Spray accuracy
81.5%Counter-strafing
9.7°Preaim
589msReaction time
35.6%T opening success
54.4%CT opening success
0.51Enemies flashed / flash
5.0%Flash assists
7.59HE damage / grenade
10.38Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

  1. Advanced Mechanics

    You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.

    T opening duels 35.6125% — below the 40% mark we flag

Spend your practice time on Inferno

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

42% win rate across 24 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

MapScoreRatingHS%Date
office13–8-0.0318%25 Aug →
office13–100.0640%25 Aug →
mirage16–140.0121%8 Jun →
inferno1–4-0.0550%10 Feb →
dust24–10-0.0323%10 Feb →
office13–60.1638%9 Feb →
office12–120.0531%9 Feb →
mirage13–10-0.0325%8 Feb →
office5–130.0124%8 Feb →
office12–12-0.0530%8 Feb →
office13–50.0030%8 Feb →
office4–13-0.0448%8 Feb →
office13–70.0424%8 Feb →
dust213–100.1813%8 Feb →
office11–90.1540%6 Feb →
office13–60.0629%6 Feb →
office9–130.0059%6 Feb →
office13–00.2333%6 Feb →
inferno12–120.0326%6 Feb →
inferno11–130.0625%11 Dec →
dust213–80.0413%1 Dec →
dust213–10.0725%1 Dec →
mirage8–13-0.0122%1 Dec →
overpass16–13-0.0235%29 Nov →
mirage13–160.0227%29 Nov →
mirage4–130.0238%29 Nov →
office13–110.0925%25 Nov →
nuke13–10.1824%25 Nov →
nuke13–60.0636%10 Mar →
inferno7–13-0.0128%9 Mar →
nuke8–20.0115%26 Feb →
mirage13–3-0.0148%26 Feb →
ancient13–2-0.0220%26 Feb →
inferno14–16-0.0337%24 Feb →
mirage13–110.0031%24 Feb →
ancient6–00.0930%24 Feb →
mirage13–80.0316%21 Feb →
nuke13–80.0728%21 Feb →
vertigo13–60.0420%4 Jan →
ancient9–2-0.0122%4 Jan →
inferno13–40.0731%10 Sept →
inferno8–130.0731%10 Sept →
office8–130.0127%5 Aug →
office0–13-0.0426%20 Jul →
vertigo0–2-0.110%10 Jul →
mirage13–100.0730%3 Jul →
office11–130.1131%23 Jun →
inferno6–30.0444%23 Jun →
anubis13–90.0724%23 Jun →
mirage13–80.2028%23 Jun →
inferno5–13-0.0223%23 Jun →
inferno13–20.1020%23 Jun →
ancient13–70.0621%16 Jun →
overpass7–70.0462%14 Apr →
office13–10.1652%7 Apr →
office6–130.0139%7 Apr →
anubis13–40.0422%7 Apr →
office13–30.0826%7 Apr →
office9–130.1356%26 Mar →
office8–130.1028%26 Mar →
overpass13–50.0337%10 Jan →
inferno16–130.0244%10 Jan →
overpass6–80.0745%10 Jan →
inferno11–130.0229%14 Sept →
anubis13–6-0.06100%12 Sept →
nuke8–13-0.0131%11 Sept →
mirage4–160.0124%27 Aug →
inferno9–160.1839%26 Aug →
inferno6–160.0719%26 Aug →
nuke14–160.0624%26 Aug →
overpass16–110.1129%26 Aug →
dust29–160.0824%16 Aug →
nuke13–160.0221%14 Aug →
ancient10–16-0.0024%14 Aug →
inferno16–140.1219%11 Aug →
inferno16–100.0621%10 Aug →
office11–160.0940%27 Jul →
office14–160.0445%27 Jul →
dust216–130.0424%16 Jul →
mirage16–90.1025%16 Jul →
office7–16-0.0133%16 Jul →
inferno5–16-0.0533%22 Jun →
nuke15–150.1129%18 Jun →
inferno11–160.0829%16 Jun →
overpass16–110.0518%16 Jun →
inferno15–150.1318%15 Jun →
inferno1–160.0133%5 Apr →
inferno16–110.1031%5 Apr →
dust214–160.1127%26 Jan →
nuke16–130.0726%2 Dec →
inferno16–120.0723%30 Nov →
overpass16–60.1023%25 Nov →
overpass16–60.0921%24 Nov →
overpass16–40.0713%24 Nov →
inferno16–50.0521%29 Oct →
train16–00.0626%29 Oct →
overpass16–20.0726%29 Oct →
inferno16–70.1827%16 Oct →
mirage16–20.1132%16 Oct →
mirage16–140.0824%13 Oct →

Match data via Leetify.

Recent teammates

Milestones

100 Matches11-Win Streak
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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