Jams — CS2 Stats

US76561198063506812[U:1:103241084]Steam profile ↗✓ No bans

1,465Tracked matches41%Win rate2020Tracked since

CSDB Rating6.0 SolidHybrid Rifler

Premier CS Rating18,042Purple band · top ~16.3% of ranked players (population est.)

CSDB Leaderboard#11390 of 21500 tracked

FaceitLevel 2Top 97.9% of ranked FACEIT players

WingmanLegendary Eagle

Ladder ranks via Leetify

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Performance scores

Aim69

Positioning66

Utility38

0–100 skill scores via Leetify.

Recent form

COLD36–57–7Last 10036%Win rateTLWLLWWTLL

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

Player DNA

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

Aim6.9

Aggression9.9

Utility3.8

Positioning6.6

Opening Duels5.3

Excellent counter-strafingLimited utility dependence

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 sh1ro 86% playstyle similarity

Most alike: positioning profile, opening-fight frequency.

Where you differ: lower utility contribution; 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

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

Reaction time. 634ms 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

Aim6.9

Positioning6.6

Utility3.8

Mechanics8.5

Opening Duels5.3

Win Impact1.9

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 rating0.00−0.01

first ⅓ avg 0.01 → last ⅓ avg 0.00

Reaction time631ms+58ms

first ⅓ avg 573ms → last ⅓ avg 631ms

Headshot accuracy24.2%+12.3%

first ⅓ avg 11.9% → 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

0.13Best rating — anubis 13–8

13–4Biggest win — overpass

5Longest win streak

2–6In matches decided by ≤2 rounds

2Overtime games

Map breakdown

anubisBest map · 50% over 6trainWeakest map · 0% over 5

Map	Grade	Played	Record	Win rate	Avg rating
dust2	C	17	6–11	35%	-0.00
mirage	D	16	5–11	31%	-0.01
nuke	C	13	5–8	38%	0.00
cache	D	13	4–9	31%	-0.01
inferno	C	11	4–7	36%	-0.02
vertigo	D	9	3–6	33%	0.03
anubis	B	6	3–3	50%	0.02
train	D	5	0–5	0%	-0.01
overpass	—	4	3–1	75%	0.02
ancient	—	4	2–2	50%	0.03
office	—	2	1–1	50%	0.08

Across the last 100 tracked matches.

Faceit stats

Combat

9Matches

33%Win rate

0.82Avg K/D

—ADR

41%Headshot %

Clutches & streaks

—1v1 clutch win

—1v2 clutch win

1Longest win streak

Recent Faceit resultsLLLWL

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.

23.3%Headshot accuracy

34.2%Accuracy (enemy spotted)

42.3%Spray accuracy

88.4%Counter-strafing

14.0°Preaim

634msReaction time

50.2%T opening success

52.3%CT opening success

0.38Enemies flashed / flash

6.5%Flash assists

10.73HE damage / grenade

4.14Flashes / 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 14.0408° — above the 12° mark we flag
Aim Training →
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 0.3847 — below the 0.5 mark we flag
Grenade Lineups →

Spend your practice time on Train

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 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
nuke	12–12	-0.03	100%	16 Aug →
mirage	6–13	0.02	29%	16 Aug →
inferno	13–8	0.02	15%	2 Jul →
nuke	9–13	-0.01	100%	2 Jul →
mirage	4–13	-0.02	14%	2 Jul →
inferno	13–6	0.00	8%	28 Jun →
cache	13–5	-0.03	13%	28 Jun →
nuke	12–12	-0.08	33%	28 Jun →
train	8–13	0.08	13%	28 Jun →
nuke	2–7	-0.01	50%	28 Jun →
cache	7–13	-0.02	14%	27 Jun →
dust2	13–5	0.06	19%	27 Jun →
dust2	13–9	0.01	20%	22 Jun →
cache	13–9	0.00	28%	22 Jun →
cache	8–13	-0.01	13%	22 Jun →
mirage	13–16	0.00	10%	20 Jun →
dust2	13–6	0.04	0%	20 Jun →
cache	2–9	-0.01	0%	20 Jun →
vertigo	12–12	-0.01	29%	15 Jun →
nuke	13–10	0.04	0%	14 Jun →
inferno	16–13	0.03	14%	14 Jun →
overpass	10–13	0.02	15%	14 Jun →
mirage	13–7	0.00	13%	14 Jun →
inferno	6–13	0.01	19%	13 Jun →
anubis	3–13	-0.03	36%	13 Jun →
cache	11–13	0.05	19%	13 Jun →
inferno	4–13	-0.08	25%	13 Jun →
cache	8–13	-0.03	25%	13 Jun →
mirage	7–13	0.03	0%	13 Jun →
ancient	13–10	0.04	20%	11 Jun →
overpass	13–8	-0.02	6%	11 Jun →
cache	3–13	-0.07	56%	5 Jun →
vertigo	7–13	0.01	44%	5 Jun →
mirage	13–6	0.01	0%	3 Jun →
ancient	13–5	0.07	38%	3 Jun →
dust2	9–13	-0.05	20%	3 Jun →
nuke	8–13	-0.01	5%	2 Jun →
train	12–12	0.02	25%	31 May →
dust2	8–13	0.01	17%	31 May →
mirage	9–13	-0.00	15%	29 May →
dust2	6–2	-0.09	0%	20 May →
inferno	8–13	-0.04	0%	20 May →
dust2	6–13	-0.01	25%	19 May →
mirage	11–13	0.04	22%	16 May →
anubis	2–9	-0.06	0%	16 May →
nuke	13–7	0.07	13%	14 May →
cache	5–13	-0.01	17%	14 May →
inferno	11–13	-0.02	0%	14 May →
vertigo	13–10	0.07	100%	10 May →
dust2	0–13	-0.05	33%	10 May →
mirage	6–13	-0.01	27%	10 May →
overpass	13–4	0.05	30%	10 May →
cache	13–9	0.03	23%	10 May →
inferno	13–9	-0.04	9%	10 May →
nuke	13–11	0.13	25%	10 May →
anubis	3–13	-0.03	8%	8 May →
cache	4–13	0.00	25%	8 May →
nuke	11–13	-0.00	0%	30 Apr →
inferno	3–13	-0.04	0%	30 Apr →
cache	5–13	0.01	14%	29 Apr →
cache	13–8	-0.02	0%	29 Apr →
train	12–12	-0.13	10%	23 Apr →
mirage	1–13	-0.05	18%	23 Apr →
vertigo	8–13	-0.01	13%	23 Apr →
ancient	12–12	0.04	0%	23 Apr →
train	8–13	-0.01	0%	23 Apr →
dust2	5–13	0.05	0%	22 Apr →
mirage	10–13	0.01	13%	22 Apr →
vertigo	11–13	0.00	0%	22 Apr →
dust2	9–13	0.03	17%	22 Apr →
vertigo	5–13	0.02	0%	20 Apr →
office	9–13	0.09	50%	19 Apr →
office	13–4	0.06	0%	19 Apr →
mirage	13–6	-0.04	9%	19 Apr →
dust2	10–13	-0.07	7%	19 Apr →
nuke	13–6	-0.01	0%	18 Apr →
mirage	13–7	-0.05	13%	18 Apr →
overpass	13–10	0.02	0%	18 Apr →
nuke	13–8	-0.05	0%	18 Apr →
anubis	13–6	0.07	20%	18 Apr →
dust2	8–13	-0.05	18%	18 Apr →
dust2	13–11	0.05	17%	16 Apr →
inferno	5–13	-0.01	30%	16 Apr →
mirage	13–7	-0.01	40%	15 Apr →
vertigo	6–3	0.11	0%	11 Apr →
mirage	6–13	-0.01	40%	11 Apr →
vertigo	13–10	0.01	14%	5 Apr →
anubis	13–8	0.13	13%	5 Apr →
nuke	10–13	0.03	0%	5 Apr →
dust2	13–10	0.01	0%	5 Apr →
dust2	9–13	-0.01	12%	4 Apr →
train	12–12	0.01	10%	3 Apr →
dust2	4–13	-0.04	8%	3 Apr →
vertigo	8–13	0.04	0%	3 Apr →
nuke	6–13	-0.05	0%	3 Apr →
dust2	8–13	0.02	12%	3 Apr →
mirage	5–13	-0.01	18%	2 Apr →
ancient	9–13	-0.01	0%	2 Apr →
inferno	11–13	-0.02	33%	1 Apr →
anubis	13–10	0.02	0%	29 Mar →