jomdela [k] — CS2 Stats

76561197974724726[U:1:14458998]✓ No bans

520Tracked matches48%Win rate2020Tracked since

CSDB Rating6.0 SolidHybrid Rifler

Premier CS Rating19,252Purple band · top ~11.5% of ranked players (population est.)

FaceitLevel 7Top 42.3% of ranked FACEIT players

Ladder ranks via Leetify

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Performance scores

Aim85

Positioning42

Utility50

0–100 skill scores via Leetify.

Recent form

COLD48–44–8Last 10048%Win rateLLWWLLLLLW

Last 10 vs previous 10: -30pp win rate · -0.02 avg rating

Player DNA

Primary style: Hybrid Rifler — Aim-led profile without a single dominant tendency.

Aim8.5

Aggression5.4

Utility5.0

Positioning4.2

Opening Duels1.2

Clutch0.0

Sharp aimerExcellent counter-strafing

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

Your pro match

Plays most like NiKo 89% playstyle similarity

Most alike: opening-fight frequency, opening-duel success.

Where you differ: lower positioning profile.

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

Strengths

Counter-strafing. 90% of shots taken properly stopped — movement discipline most players never reach.

Areas to improve

Positioning. Positioning trails aim by 42 points — deaths here waste a strong aim profile.

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

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

Aim8.5

Positioning4.2

Utility5.0

Mechanics8.9

Opening Duels1.2

Win Impact4.4

Composite 6.0/10 (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 rating-0.03−0.03

first ⅓ avg 0.00 → last ⅓ avg -0.03

Reaction time556ms−42ms

first ⅓ avg 598ms → last ⅓ avg 556ms

Headshot accuracy24.2%−2.6%

first ⅓ avg 26.9% → last ⅓ avg 24.2%

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.

Highlights

0.11Best rating — dust2 13–6

13–2Biggest win — anubis

8Longest win streak

L2Current streak

11–6In matches decided by ≤2 rounds

Map breakdown

ancientBest map · 86% over 7infernoWeakest map · 32% over 19

Map	Grade	Played	Record	Win rate	Avg rating
inferno	D	19	6–13	32%	-0.04
dust2	B	16	8–8	50%	-0.02
mirage	B	15	7–8	47%	-0.01
cache	C	11	4–7	36%	-0.05
nuke	A	11	6–5	55%	0.01
ancient	S	7	6–1	86%	-0.01
vertigo	B	6	3–3	50%	-0.04
anubis	A	5	3–2	60%	-0.02
train	—	4	2–2	50%	-0.03
overpass	—	4	2–2	50%	-0.04
warden	—	2	1–1	50%	0.04

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (32% over 19). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.

Faceit stats

Combat

217Matches

55%Win rate

1.40Avg K/D

70.7ADR

42%Headshot %

Clutches & streaks

18%1v1 clutch win

19%1v2 clutch win

11Longest win streak

Recent Faceit resultsWLLLL

Map	Matches	Win rate	Avg K/D	Avg kills
Inferno	6	50%	0.76	11.3
Dust2	6	83%	1.19	17.7
Ancient	4	75%	0.72	11.8
Anubis	3	33%	0.74	13.3
Mirage	3	67%	0.76	15.0
Nuke	2	50%	0.99	17.5
Train	2	50%	0.82	13.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

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

26.4%Headshot accuracy

30.4%Accuracy (enemy spotted)

34.9%Spray accuracy

90.1%Counter-strafing

8.4°Preaim

544msReaction time

37.2%T opening success

32.1%CT opening success

0.65Enemies flashed / flash

4.9%Flash assists

7.07HE damage / grenade

6.92Flashes / 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.

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 37.1577% — 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.

32% win rate across 19 tracked games — your weakest map with enough games to be worth reading into.

Inferno callouts & strategy →Inferno grenade lineups →

Recent matches

Map	Score	Rating	HS%	Date
inferno	5–13	-0.04	11%	20 Aug →
inferno	8–13	-0.06	14%	19 Aug →
mirage	13–10	0.05	11%	19 Aug →
dust2	13–7	0.06	15%	19 Aug →
inferno	8–13	-0.01	21%	8 Aug →
cache	8–13	-0.06	20%	8 Aug →
vertigo	7–13	-0.04	17%	6 Aug →
mirage	2–13	-0.08	44%	6 Aug →
inferno	8–13	-0.07	0%	6 Aug →
mirage	5–2	0.03	28%	3 Aug →
vertigo	13–11	0.05	27%	3 Aug →
ancient	13–9	-0.03	17%	3 Aug →
nuke	13–11	0.04	25%	3 Aug →
inferno	12–12	0.05	100%	3 Aug →
dust2	13–7	0.07	36%	3 Aug →
dust2	12–12	0.03	29%	2 Aug →
cache	13–11	0.02	21%	2 Aug →
nuke	13–11	-0.05	30%	2 Aug →
inferno	9–13	-0.07	57%	31 Jul →
inferno	5–13	-0.08	8%	31 Jul →
dust2	5–13	-0.08	33%	31 Jul →
vertigo	13–10	-0.11	29%	31 Jul →
dust2	2–13	-0.12	30%	31 Jul →
nuke	8–13	-0.01	15%	27 Jul →
inferno	8–13	-0.06	17%	26 Jul →
nuke	6–13	-0.02	15%	26 Jul →
mirage	12–12	-0.05	26%	26 Jul →
inferno	13–10	-0.08	0%	26 Jul →
cache	13–6	-0.05	42%	26 Jul →
cache	13–8	0.01	26%	26 Jul →
anubis	13–11	0.02	14%	26 Jul →
mirage	10–13	-0.08	11%	19 Jun →
cache	5–6	-0.05	10%	19 Jun →
cache	13–11	-0.02	16%	3 Jun →
cache	11–13	-0.07	14%	3 Jun →
inferno	7–13	-0.09	8%	28 May →
nuke	9–13	-0.04	28%	28 May →
cache	8–13	-0.05	26%	28 May →
cache	2–13	-0.14	50%	12 May →
train	12–12	-0.07	18%	7 May →
vertigo	10–13	-0.10	39%	7 May →
cache	11–13	-0.08	18%	7 May →
inferno	8–13	0.02	23%	3 May →
dust2	13–3	0.00	26%	3 May →
cache	10–13	-0.04	34%	2 May →
inferno	3–9	-0.18	0%	2 May →
ancient	10–13	-0.05	41%	24 Feb →
mirage	13–3	-0.02	26%	24 Feb →
inferno	13–11	-0.00	26%	24 Feb →
mirage	12–12	-0.04	48%	24 Feb →
dust2	4–13	-0.10	14%	21 Feb →
mirage	13–10	0.00	22%	21 Feb →
ancient	13–8	0.02	13%	21 Feb →
nuke	13–8	-0.02	28%	21 Feb →
overpass	13–11	-0.06	27%	21 Feb →
dust2	8–13	-0.08	29%	21 Feb →
ancient	13–6	-0.01	23%	21 Feb →
overpass	11–13	0.04	23%	20 Feb →
dust2	12–12	-0.04	33%	20 Feb →
ancient	13–3	-0.02	7%	20 Feb →
vertigo	12–12	-0.05	28%	20 Feb →
inferno	5–13	-0.00	38%	19 Feb →
train	13–11	-0.03	29%	19 Feb →
dust2	7–13	-0.08	13%	19 Feb →
anubis	11–13	-0.01	40%	19 Feb →
mirage	10–13	-0.02	13%	19 Feb →
dust2	13–3	-0.05	43%	19 Feb →
nuke	9–13	-0.02	19%	18 Feb →
overpass	13–11	-0.10	17%	18 Feb →
inferno	13–9	-0.03	47%	18 Feb →
warden	13–10	0.01	16%	15 Feb →
mirage	13–8	0.06	39%	9 Feb →
ancient	13–10	0.02	45%	9 Feb →
nuke	13–6	-0.01	26%	9 Feb →
dust2	6–13	-0.06	27%	9 Feb →
train	5–13	-0.07	30%	8 Feb →
inferno	13–9	0.01	19%	8 Feb →
overpass	6–13	-0.05	8%	8 Feb →
warden	7–13	0.06	40%	8 Feb →
dust2	13–7	0.07	45%	8 Feb →
anubis	13–2	-0.03	29%	8 Feb →
nuke	13–8	0.04	35%	8 Feb →
mirage	13–6	0.02	33%	6 Feb →
vertigo	13–7	0.02	25%	6 Feb →
anubis	12–12	-0.03	20%	6 Feb →
mirage	6–13	-0.03	31%	5 Feb →
nuke	9–13	0.11	25%	5 Feb →
inferno	13–8	-0.08	16%	4 Feb →
anubis	13–10	-0.03	19%	4 Feb →
mirage	13–7	0.02	36%	3 Feb →
nuke	13–7	0.10	29%	3 Feb →
inferno	13–11	0.03	30%	3 Feb →
train	13–6	0.06	35%	3 Feb →
dust2	13–9	-0.02	18%	3 Feb →
ancient	13–6	-0.01	18%	3 Feb →
mirage	11–13	0.03	5%	3 Feb →
inferno	3–13	-0.01	21%	3 Feb →
dust2	13–6	0.11	48%	3 Feb →
mirage	9–13	-0.05	15%	3 Feb →
dust2	13–10	-0.01	20%	2 Feb →