Jelmah

Jelmah — CS2 Stats

NL76561198144336870[U:1:184071142]Steam profile ↗✓ No bans

421Tracked matches33%Win rate2020Tracked since
1,933Hours in CS7Hrs last 2 wks
CSDB Rating5.7 SolidPositional Player
Premier CS Rating15,094Purple band · top ~28% of ranked players (population est.)
WingmanGold Nova Master
Ladder ranks via Leetify

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CSDB.GGJelmahPREMIER15,094 · Purple bandcsdb.gg/stats

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Performance scores

Aim70
Positioning65
Utility44

0–100 skill scores via Leetify.

Recent form

COLD41–59Last 10041%Win rateLLLLWWLLLW

Last 10 vs previous 10: 0pp win rate · +0.05 avg rating · −0.5pp headshot accuracy · −20ms reaction

Win rate 0pp 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

  • 1–4 · 20% win rate
  • Avg rating 0.02
  • Avg headshot accuracy 17%
  • Avg reaction 531ms

Last 10

  • 3–7 · 30% win rate
  • Avg rating 0.03
  • Avg headshot accuracy 16%
  • Avg reaction 542ms

Last 20

  • 6–14 · 30% win rate
  • Avg rating 0.01
  • Avg headshot accuracy 16%
  • Avg reaction 552ms

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: Positional Player — Positioning stands above the rest of this profile (+1.4 against its own average).

Aim7.0
Utility4.4
Positioning6.5
Opening Duels4.4

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

jL

Plays most like jL 88% playstyle similarity

Most alike: positioning profile, aim profile.

Where you differ: lower utility contribution; 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 →

CSDB Rating breakdown

Aim7.0
Positioning6.5
Utility4.4
Mechanics6.9
Opening Duels6.3
Win Impact0.0

Composite 5.7/10 (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 rating0.00−0.02
first ⅓ avg 0.02 → last ⅓ avg 0.00
Reaction time546ms−29ms
first ⅓ avg 576ms → last ⅓ avg 546ms
Headshot accuracy15.8%−1.6%
first ⅓ avg 17.4% → last ⅓ avg 15.8%

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

0.15Best match rating · 13–3 · dust2, 13 Aug →
38%Best headshot accuracy · 6–13 · dust2, 3 Aug →
406msFastest reaction time · 4–13 · mirage, 10 Sept →
13–0Biggest win · ancient, 17 Sept →

Across the last 100 tracked matches.

Highlights

6Longest win streak
L4Current streak
5–6In matches decided by ≤2 rounds
3Overtime games

Map breakdown

dust2Best map · 56% over 25nukeWeakest map · 0% over 6
MapGradePlayedRecordWin rateAvg rating
dust2A2514–1156%0.02
infernoB2411–1346%0.02
mirageC208–1240%-0.00
cacheC125–742%0.00
anubisD71–614%-0.02
nukeD60–60%0.02
ancientD62–433%0.01

Across the last 100 tracked matches.

Nuke is currently your weakest sufficiently-sampled map (0% over 6). Start with the 6 essential Nuke lineups, review the callouts, then spin up a practice server.

Lifetime stats

69,364Lifetime kills
1.29K/D
3,162Matches
43.0%Match win rate
29.4%Headshot %
16.7%Shot accuracy
8,276MVPs
1,168Hours (in match)
1,773Bombs planted
801Bombs defused

Most-used weapons

AWP19,637
AK-4714,786
P2502,246
SSG 081,528
P901,364

Lifetime map wins

9,459dust2
5,683inferno
797cbble
358lake
330vertigo
291nuke
161train
28safehouse

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Skill profile

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

15.7%Headshot accuracy
34.1%Accuracy (enemy spotted)
36.2%Spray accuracy
80.9%Counter-strafing
9.7°Preaim
546msReaction time
55.9%T opening success
54.1%CT opening success
0.44Enemies flashed / flash
6.9%Flash assists
9.09HE damage / grenade
5.65Flashes / 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. Grenades & Utility

    Most of your flashes are blinding nobody. A handful of reliable pop-flash lineups fixes this faster than anything else.

    Enemies flashed per flash 0.4437 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Nuke

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

0% win rate across 6 tracked games — your weakest map with enough games to be worth reading into.

Nuke callouts & strategy →Nuke grenade lineups →

Recent matches

MapScoreRatingHS%Date
nuke10–130.0710%10 Nov →
dust25–13-0.0510%10 Nov →
anubis2–13-0.0333%10 Nov →
mirage8–130.0010%7 Nov →
dust213–80.1022%7 Nov →
cache13–70.0115%7 Nov →
anubis10–130.0821%6 Nov →
ancient6–130.0114%6 Nov →
nuke8–13-0.048%2 Nov →
inferno13–90.1414%2 Nov →
ancient13–100.0110%2 Nov →
anubis8–13-0.0813%1 Nov →
anubis4–13-0.0411%1 Nov →
anubis13–11-0.0313%31 Oct →
mirage13–10-0.0512%31 Oct →
inferno4–13-0.0721%31 Oct →
anubis12–160.0211%30 Oct →
cache10–130.0722%4 Oct →
nuke6–130.0329%4 Oct →
cache2–13-0.0319%4 Oct →
anubis4–13-0.0714%1 Oct →
inferno9–13-0.0213%29 Sept →
dust29–13-0.0220%29 Sept →
ancient3–13-0.0435%28 Sept →
inferno6–13-0.035%28 Sept →
cache6–13-0.0521%18 Sept →
inferno13–80.0517%18 Sept →
mirage13–90.0013%18 Sept →
cache13–110.0617%17 Sept →
ancient13–00.039%17 Sept →
mirage13–90.0617%17 Sept →
dust213–8-0.0310%17 Sept →
nuke11–130.0513%17 Sept →
dust216–13-0.0117%16 Sept →
ancient9–130.0615%16 Sept →
mirage4–13-0.0715%14 Sept →
inferno13–40.026%14 Sept →
dust213–60.0324%14 Sept →
ancient2–13-0.0432%10 Sept →
dust213–70.0915%10 Sept →
dust213–90.0516%10 Sept →
mirage4–13-0.0316%10 Sept →
inferno10–130.0020%9 Sept →
dust213–3-0.0410%9 Sept →
inferno2–13-0.0812%9 Sept →
inferno5–13-0.0211%8 Sept →
mirage11–130.0516%8 Sept →
inferno13–70.056%8 Sept →
inferno13–70.0413%2 Sept →
dust28–13-0.0111%1 Sept →
dust26–13-0.0615%1 Sept →
inferno13–110.0115%1 Sept →
mirage2–13-0.0917%1 Sept →
dust26–130.0416%29 Aug →
nuke1–130.0521%29 Aug →
dust25–130.0318%29 Aug →
mirage10–130.0121%29 Aug →
mirage13–110.0918%29 Aug →
mirage12–16-0.0715%29 Aug →
cache5–13-0.037%29 Aug →
dust213–80.0019%29 Aug →
cache13–80.0318%27 Aug →
inferno13–70.0311%27 Aug →
inferno11–130.0314%27 Aug →
dust211–13-0.0018%26 Aug →
inferno7–13-0.0116%23 Aug →
dust213–30.0429%23 Aug →
mirage13–70.0833%23 Aug →
mirage6–13-0.0418%19 Aug →
dust23–13-0.0311%17 Aug →
inferno13–50.1012%13 Aug →
dust213–30.1524%13 Aug →
mirage8–130.0213%12 Aug →
inferno13–70.0511%12 Aug →
mirage4–13-0.0718%10 Aug →
dust28–130.0315%10 Aug →
mirage4–130.0719%10 Aug →
inferno7–13-0.0210%3 Aug →
cache13–5-0.0122%3 Aug →
dust26–13-0.0138%3 Aug →
mirage13–11-0.0216%29 Jul →
cache11–130.0521%26 Jul →
inferno7–13-0.0320%24 Jul →
mirage3–130.0211%24 Jul →
dust213–40.0310%24 Jul →
mirage13–7-0.0213%18 Jul →
cache10–13-0.0230%16 Jul →
dust213–90.1218%16 Jul →
dust213–90.0121%16 Jul →
inferno13–80.048%15 Jul →
mirage13–90.028%15 Jul →
cache4–13-0.0616%14 Jul →
inferno10–130.016%14 Jul →
inferno7–130.1120%14 Jul →
nuke11–13-0.0115%14 Jul →
cache13–8-0.0027%13 Jul →
inferno9–00.0316%13 Jul →
inferno3–13-0.0121%13 Jul →
dust28–130.0313%8 Jul →
dust213–30.0921%8 Jul →

Match data via Leetify.

Recent teammates

Milestones

100 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →

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