Jechtshot — CS2 Stats

US76561198065547613[U:1:105281885]Steam profile ↗✓ No bans

329Tracked matches34%Win rate2024Tracked since

CSDB Rating3.8 Learning

Premier CS Rating19,333Purple band · top ~11.2% of ranked players (population est.)

Ladder ranks via Leetify

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Performance scores

Aim38

Positioning58

Utility61

0–100 skill scores via Leetify.

Recent form

STEADY43–54–3Last 10043%Win rateWWLLWWLLWL

Last 10 vs previous 10: +20pp win rate · -0.02 avg rating

Player DNA

Aim3.8

Aggression5.2

Utility6.1

Positioning5.8

Opening Duels1.6

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 86% playstyle similarity

Most alike: utility contribution, positioning profile.

Where you differ: lower aim 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

Areas to improve

Reaction time. 610ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 63% of shots are taken properly stopped — moving-shot inaccuracy is quietly taxing every duel.

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

Aim3.8

Positioning5.8

Utility6.1

Mechanics2.9

Opening Duels1.6

Win Impact0.0

Composite 3.8/10 (Learning), 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-0.01−0.01

first ⅓ avg 0.01 → last ⅓ avg -0.01

Reaction time607ms−36ms

first ⅓ avg 643ms → last ⅓ avg 607ms

Headshot accuracy16.2%−0.9%

first ⅓ avg 17.1% → last ⅓ avg 16.2%

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

0.12Best rating — inferno 8–13

13–1Biggest win — nuke

7Longest win streak

W2Current streak

5–9In matches decided by ≤2 rounds

10Overtime games

Map breakdown

dust2Best map · 57% over 7infernoWeakest map · 35% over 23

Map	Grade	Played	Record	Win rate	Avg rating
inferno	C	23	8–15	35%	-0.00
nuke	C	18	7–11	39%	0.01
cache	B	17	8–9	47%	-0.01
anubis	C	17	7–10	41%	-0.00
ancient	B	11	5–6	45%	0.00
dust2	A	7	4–3	57%	-0.01
overpass	C	5	2–3	40%	-0.01
boulder	—	1	1–0	100%	0.09
vertigo	—	1	1–0	100%	0.01

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (35% over 23). 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.

15.4%Headshot accuracy

32.6%Accuracy (enemy spotted)

35.9%Spray accuracy

62.8%Counter-strafing

12.6°Preaim

610msReaction time

33.2%T opening success

39.3%CT opening success

0.55Enemies flashed / flash

5.9%Flash assists

11.47HE damage / grenade

9.82Flashes / 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
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.5964° — above the 12° mark we flag
Aim Training →

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.

35% win rate across 23 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
cache	13–6	-0.00	28%	29 Aug →
inferno	13–7	0.02	13%	29 Aug →
anubis	11–13	-0.00	17%	29 Aug →
cache	6–13	-0.04	18%	29 Aug →
ancient	16–14	-0.03	9%	27 Aug →
inferno	13–11	0.00	10%	27 Aug →
anubis	4–13	-0.09	15%	25 Aug →
dust2	4–13	-0.10	10%	25 Aug →
inferno	13–11	0.05	19%	24 Aug →
dust2	1–13	-0.03	20%	23 Aug →
cache	9–13	-0.02	12%	19 Aug →
dust2	13–8	-0.03	15%	19 Aug →
anubis	5–13	-0.05	7%	19 Aug →
inferno	6–13	-0.08	9%	18 Aug →
anubis	11–13	-0.02	16%	17 Aug →
inferno	6–13	-0.02	10%	16 Aug →
ancient	13–6	0.07	14%	14 Aug →
nuke	13–9	0.09	17%	14 Aug →
anubis	8–13	0.02	12%	14 Aug →
cache	7–13	-0.00	17%	12 Aug →
inferno	6–13	-0.02	15%	12 Aug →
anubis	15–15	0.03	16%	11 Aug →
nuke	2–13	-0.00	21%	11 Aug →
ancient	11–13	0.01	11%	10 Aug →
ancient	11–13	-0.02	10%	7 Aug →
inferno	13–16	-0.04	20%	7 Aug →
cache	13–2	0.01	19%	7 Aug →
cache	9–13	-0.07	10%	6 Aug →
nuke	13–1	0.06	56%	6 Aug →
inferno	6–13	0.01	16%	5 Aug →
nuke	13–5	0.01	24%	30 Jul →
anubis	13–8	0.02	23%	30 Jul →
anubis	13–6	0.02	9%	28 Jul →
cache	13–1	0.02	21%	28 Jul →
cache	16–12	0.02	2%	18 Jul →
ancient	13–5	0.01	11%	18 Jul →
anubis	15–15	-0.02	7%	18 Jul →
anubis	11–13	-0.01	10%	17 Jul →
nuke	13–2	0.11	10%	16 Jul →
cache	13–6	-0.01	5%	16 Jul →
anubis	13–5	-0.01	2%	15 Jul →
cache	10–13	-0.04	11%	14 Jul →
cache	9–13	-0.02	12%	14 Jul →
ancient	8–13	0.04	10%	14 Jul →
inferno	13–6	-0.02	16%	14 Jul →
inferno	10–13	0.03	20%	13 Jul →
nuke	8–13	0.01	10%	13 Jul →
inferno	13–2	0.07	17%	13 Jul →
cache	1–13	-0.02	16%	11 Jul →
boulder	13–4	0.09	10%	11 Jul →
nuke	11–13	-0.00	10%	9 Jul →
nuke	8–13	-0.02	12%	6 Jul →
inferno	6–13	0.00	15%	25 Jun →
cache	10–13	-0.07	14%	25 Jun →
inferno	13–11	-0.03	10%	22 Jun →
dust2	3–13	-0.00	21%	22 Jun →
nuke	2–13	-0.05	15%	9 Jun →
dust2	16–14	0.02	9%	9 Jun →
inferno	10–13	-0.08	10%	6 Jun →
vertigo	13–7	0.01	23%	6 Jun →
cache	13–3	0.06	14%	6 Jun →
nuke	6–13	-0.04	14%	2 Jun →
dust2	13–8	0.02	15%	2 Jun →
anubis	13–8	0.04	16%	1 Jun →
inferno	13–6	-0.02	13%	18 May →
inferno	16–13	-0.04	13%	17 May →
ancient	13–10	0.04	21%	16 May →
cache	13–5	0.02	20%	16 May →
cache	13–4	0.06	17%	11 May →
cache	10–13	0.01	22%	4 May →
ancient	7–13	-0.03	16%	11 Apr →
inferno	6–13	0.02	18%	11 Apr →
nuke	13–7	0.05	21%	7 Apr →
inferno	9–13	-0.02	19%	7 Apr →
ancient	4–13	-0.02	15%	3 Apr →
anubis	13–10	0.05	11%	3 Apr →
overpass	16–12	0.01	20%	29 Mar →
overpass	13–9	-0.01	17%	22 Mar →
dust2	13–9	0.05	24%	22 Mar →
overpass	11–13	0.01	14%	20 Mar →
nuke	3–13	-0.03	21%	20 Mar →
anubis	16–12	-0.07	8%	16 Mar →
ancient	4–13	-0.04	10%	14 Mar →
inferno	9–13	0.03	15%	14 Mar →
nuke	9–13	-0.04	17%	14 Mar →
overpass	11–13	-0.03	13%	14 Mar →
inferno	9–13	-0.04	15%	14 Mar →
anubis	9–13	0.04	7%	14 Mar →
nuke	6–13	-0.04	14%	13 Mar →
inferno	8–13	0.12	15%	8 Mar →
anubis	13–5	-0.02	18%	26 Feb →
nuke	6–13	0.03	13%	26 Feb →
nuke	13–10	0.03	30%	24 Feb →
inferno	15–15	-0.01	11%	23 Feb →
ancient	13–9	-0.00	9%	23 Feb →
overpass	7–13	-0.01	16%	21 Feb →
nuke	13–9	0.10	14%	19 Feb →
inferno	11–13	0.00	29%	19 Feb →
anubis	5–13	0.02	25%	18 Feb →
nuke	5–13	-0.04	30%	13 Feb →