Howard — CS2 Stats

76561199043270950[U:1:1083005222]Steam profile ↗✓ No bans

3,481Tracked matches41%Win rate2020Tracked since

CSDB Rating4.9 DevelopingPositional Player

Premier CS Rating10,674Blue band · top ~51.3% of ranked players (population est.)

CSDB Leaderboard#162221 of 232078 tracked

WingmanGold Nova II

Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 19 Sep 2026 (yesterday). Ranks are recorded once per day this page is viewed.

No change since then. Play, then come back: the next observation lands here.

Track this profile

CSDB reads this profile's Premier rating from its tracked match history, and records Faceit ELO once on every day the page is viewed. 36 days played since 3 Jul 2026. Come back after the next session and the change shows above.

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Rating over time

Premier CS Rating: 10,674 +305 3 Jul – 19 Sept · 3 days played

10,674Peak Premier in tracked matches

36Days played since 2026-07-03

Premier CS Rating

At peak — 10,674
+305 over 90 days
Next: Purple band at 15,000 — 4,326 to go
Reached: Blue band · Light Blue band

Premier comes from this profile’s tracked match history, so it reaches back as far as those matches do.

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Performance scores

Aim59

Positioning56

Utility52

0–100 skill scores via Leetify.

Recent form

STEADY39–53–8Last 10039%Win rateLWWLWLWWLL

Last 10 vs previous 10: +20pp win rate · +0.00 avg rating · −2.0pp headshot accuracy · +9ms reaction

Win rate up 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp).

Last 5 · 10 · 20 matches

Last 5

3–2 · 60% win rate
Avg rating 0.02
Avg headshot accuracy 22%
Avg reaction 625ms

Last 10

5–5 · 50% win rate
Avg rating -0.03
Avg headshot accuracy 20%
Avg reaction 609ms

Last 20

8–12 · 40% win rate
Avg rating -0.03
Avg headshot accuracy 21%
Avg reaction 605ms

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).

Aim5.9

Utility5.2

Positioning5.6

Opening Duels1.9

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

Plays most like NiKo 77% playstyle similarity

Most alike: positioning profile, utility contribution.

Where you differ: lower opening-duel success; 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. 613ms 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

Aim5.9

Positioning5.6

Utility5.2

Mechanics7.1

Opening Duels2.4

Win Impact2.1

Composite 4.9/10 (Developing), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.03−0.00

first ⅓ avg -0.03 → last ⅓ avg -0.03

Reaction time611ms−65ms

first ⅓ avg 676ms → last ⅓ avg 611ms

Headshot accuracy20.5%+1.6%

first ⅓ avg 18.9% → last ⅓ avg 20.5%

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

0.13Best match rating · 13–2 · vertigo, 20 Sept →

52%Best headshot accuracy · 13–11 · office, 25 Aug →

406msFastest reaction time · 12–12 · office, 2 Sept →

13–1Biggest win · nuke, 18 Aug →

Across the last 100 tracked matches.

Highlights

4Longest win streak

3–6In matches decided by ≤2 rounds

2Overtime games

Map breakdown

nukeBest map · 53% over 15infernoWeakest map · 22% over 9

Map	Grade	Played	Record	Win rate	Avg rating
office	C	20	8–12	40%	-0.02
cache	C	19	7–12	37%	-0.02
nuke	B	15	8–7	53%	-0.03
inferno	D	9	2–7	22%	-0.03
train	C	9	4–5	44%	-0.02
dust2	C	8	3–5	38%	-0.02
ancient	D	6	2–4	33%	-0.06
vertigo	—	3	1–2	33%	0.01
anubis	—	3	0–3	0%	-0.07
mirage	—	2	1–1	50%	-0.04
shelter	—	2	2–0	100%	-0.02
overpass	—	2	0–2	0%	-0.05
boulder	—	1	0–1	0%	-0.06
alpine	—	1	1–0	100%	0.02

Across the last 100 tracked matches.

Inferno is currently your weakest sufficiently-sampled map (22% over 9). 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.

20.7%Headshot accuracy

31.3%Accuracy (enemy spotted)

30.3%Spray accuracy

81.7%Counter-strafing

10.9°Preaim

613msReaction time

40.6%T opening success

39.0%CT opening success

0.63Enemies flashed / flash

2.7%Flash assists

11.24HE damage / grenade

7.08Flashes / 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
Losing the first CT duel repeatedly usually means holding angles that favour the peeker.
CT opening duels 38.9522% — 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.

22% win rate across 9 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	4–13	-0.00	30%	20 Sept →
vertigo	13–2	0.13	22%	20 Sept →
nuke	13–4	0.00	22%	20 Sept →
office	8–13	0.01	24%	19 Sept →
ancient	13–11	-0.03	13%	19 Sept →
anubis	7–13	-0.10	16%	19 Sept →
dust2	13–4	-0.06	26%	19 Sept →
office	13–10	-0.08	11%	18 Sept →
nuke	5–13	-0.06	17%	18 Sept →
anubis	4–13	-0.06	17%	18 Sept →
ancient	11–13	-0.08	29%	16 Sept →
mirage	13–3	-0.02	11%	16 Sept →
office	5–13	0.03	20%	16 Sept →
inferno	13–10	-0.04	16%	15 Sept →
anubis	9–13	-0.04	10%	15 Sept →
nuke	9–13	-0.10	26%	15 Sept →
office	8–13	-0.01	48%	15 Sept →
mirage	5–13	-0.05	19%	14 Sept →
ancient	10–13	-0.02	14%	14 Sept →
nuke	4–1	0.04	25%	14 Sept →
nuke	13–5	0.03	15%	13 Sept →
office	13–6	0.03	24%	12 Sept →
cache	5–13	-0.05	25%	12 Sept →
train	11–13	-0.02	19%	12 Sept →
dust2	6–13	-0.00	27%	12 Sept →
vertigo	12–12	-0.06	11%	12 Sept →
inferno	6–13	-0.05	32%	11 Sept →
cache	2–13	-0.02	19%	11 Sept →
nuke	13–9	-0.02	18%	8 Sept →
office	13–4	-0.08	25%	8 Sept →
inferno	11–13	-0.06	24%	7 Sept →
nuke	13–9	-0.05	10%	7 Sept →
cache	11–13	-0.05	11%	7 Sept →
office	4–13	-0.06	11%	6 Sept →
inferno	2–8	-0.03	31%	6 Sept →
nuke	6–13	-0.04	15%	6 Sept →
cache	7–13	-0.03	29%	4 Sept →
office	13–3	0.13	28%	4 Sept →
dust2	13–9	0.02	26%	2 Sept →
train	13–6	-0.02	18%	2 Sept →
office	12–12	-0.07	22%	2 Sept →
cache	13–10	-0.04	25%	2 Sept →
cache	4–13	-0.05	14%	1 Sept →
nuke	13–3	-0.06	19%	1 Sept →
inferno	5–13	-0.04	19%	1 Sept →
inferno	5–13	-0.02	18%	31 Aug →
nuke	7–13	-0.03	16%	31 Aug →
cache	13–8	-0.01	32%	31 Aug →
dust2	13–10	-0.00	21%	28 Aug →
ancient	6–13	-0.09	13%	28 Aug →
train	13–11	-0.04	16%	27 Aug →
nuke	4–13	-0.00	27%	27 Aug →
dust2	12–12	-0.02	18%	27 Aug →
cache	2–13	-0.02	18%	27 Aug →
office	4–13	-0.02	26%	27 Aug →
office	0–13	0.00	17%	26 Aug →
inferno	13–3	0.03	21%	25 Aug →
nuke	6–13	-0.10	13%	25 Aug →
train	4–13	-0.03	12%	25 Aug →
cache	13–5	0.00	13%	25 Aug →
office	13–11	-0.04	52%	25 Aug →
nuke	13–2	-0.00	13%	22 Aug →
cache	13–2	0.02	15%	22 Aug →
dust2	7–13	-0.06	13%	22 Aug →
cache	7–13	-0.06	23%	20 Aug →
train	10–13	0.06	22%	18 Aug →
nuke	13–1	0.08	31%	18 Aug →
inferno	6–13	-0.06	24%	15 Aug →
office	6–13	-0.07	23%	15 Aug →
dust2	2–13	0.00	24%	15 Aug →
office	12–12	0.03	17%	15 Aug →
nuke	8–13	-0.12	8%	11 Aug →
vertigo	7–13	-0.03	15%	11 Aug →
inferno	15–15	-0.04	16%	6 Aug →
ancient	13–9	-0.08	15%	6 Aug →
cache	13–7	0.02	18%	6 Aug →
shelter	13–8	0.05	34%	30 Jul →
ancient	15–15	-0.06	12%	30 Jul →
train	12–12	-0.04	15%	29 Jul →
cache	13–10	-0.02	27%	29 Jul →
cache	7–13	-0.02	19%	28 Jul →
office	13–5	-0.02	19%	28 Jul →
boulder	10–13	-0.06	11%	20 Jul →
office	10–13	-0.03	19%	18 Jul →
cache	11–13	-0.05	14%	18 Jul →
office	7–13	-0.03	23%	15 Jul →
cache	12–12	-0.03	4%	15 Jul →
shelter	13–3	-0.08	26%	15 Jul →
train	13–10	-0.05	17%	8 Jul →
cache	3–13	-0.00	20%	8 Jul →
dust2	6–13	-0.03	9%	8 Jul →
office	5–13	-0.12	17%	8 Jul →
alpine	13–9	0.02	19%	7 Jul →
cache	13–10	0.01	35%	7 Jul →
office	13–4	0.04	14%	7 Jul →
train	8–13	-0.01	21%	7 Jul →
overpass	11–13	-0.06	21%	6 Jul →
train	13–5	-0.04	24%	6 Jul →
office	13–8	0.07	33%	3 Jul →
overpass	6–13	-0.04	11%	3 Jul →