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Smiggs

Smiggs — CS2 Stats

US76561198370763583[U:1:410497855]Steam profile ↗

977Tracked matches46%Win rate2023Tracked since
827Hours in CS
CSDB Rating2.8 Learning
Ladder ranks via Leetify

Performance scores

Aim28
Positioning37
Utility34

0–100 skill scores via Leetify.

Recent form

STEADY40–49–11Last 10040%Win rateTLWWWWWLLL

Last 10 vs previous 10: +10pp win rate · +0.01 avg rating

Player DNA

Aim2.8
Aggression2.7
Utility3.4
Positioning3.7
Opening Duels0.0
Clutch2.6

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

NiKo

Plays most like NiKo 68% playstyle similarity

Most alike: opening-duel success, 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

T-side openings. Opening success drops from 43% on CT to 16% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 619ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 64% 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

Aim2.8
Positioning3.7
Utility3.4
Mechanics3.0
Opening Duels1.6
Win Impact3.7

Composite 2.8/10 (Learning), a weighted mean of the bars with a small opposition adjustment (×0.90 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02+0.00
first ⅓ avg -0.03 → last ⅓ avg -0.02
Reaction time613ms−54ms
first ⅓ avg 667ms → last ⅓ avg 613ms
Headshot accuracy10.9%−2.4%
first ⅓ avg 13.4% → last ⅓ avg 10.9%

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

0.09Best rating — anubis 13–1
13–1Biggest win — anubis
5Longest win streak
7–7In matches decided by ≤2 rounds

Map breakdown

infernoBest map · 63% over 8mirageWeakest map · 25% over 8
MapGradePlayedRecordWin rateAvg rating
dust2C3713–2435%-0.02
nukeB178–947%-0.02
ancientC146–843%-0.02
cacheD103–730%-0.00
infernoA85–363%-0.03
mirageD82–625%-0.05
anubisB63–350%-0.01

Across the last 100 tracked matches.

Mirage is currently your weakest sufficiently-sampled map (25% over 8). Start with the 6 essential Mirage lineups, review the callouts, then spin up a practice server.

Lifetime stats

28,731Lifetime kills
0.81K/D
2,631Matches
45.9%Match win rate
38.9%Headshot %
1.5%Shot accuracy
3,076MVPs
827Hours (in match)
1,399Bombs planted
285Bombs defused

Most-used weapons

AK-479,910
M4A4 / M4A1-S9,095
MP71,848
P2000 / USP-S1,718
Glock-181,469
MAC-101,329
AWP1,270
Desert Eagle383
PP-Bizon344
Knife310

Lifetime map wins

5,907dust2
2,793nuke
2,137inferno
821vertigo
361train
144office
15lake
8italy

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

Faceit stats

Combat

152Matches
47%Win rate
0.69Avg K/D
66.8ADR
40%Headshot %

Clutches & streaks

33%1v1 clutch win
15%1v2 clutch win
5Longest win streak

Recent Faceit resultsLLWWL

MapMatchesWin rateAvg K/DAvg kills
Dust24448%0.7312.0
Mirage3636%0.7010.9
Ancient2662%0.6511.5
Inferno1656%0.6611.5
Nuke1540%0.7412.7
Anubis933%0.6612.3
Overpass250%0.7011.5

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.

10.6%Headshot accuracy
31.7%Accuracy (enemy spotted)
33.0%Spray accuracy
63.6%Counter-strafing
12.8°Preaim
619msReaction time
15.7%T opening success
42.8%CT opening success
0.43Enemies flashed / flash
1.7%Flash assists
10.61HE damage / grenade
1.97Flashes / 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. Advanced Mechanics

    Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.

    Preaim 12.8188° — above the 12° mark we flag

    Aim Training →
  2. Best CS2 Crosshair

    Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.

    Headshot accuracy 10.5858% — below the 15% mark we flag

    Aim Training →
  3. 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 0.434 — below the 0.5 mark we flag

    Grenade Lineups →
Spend your practice time on Mirage

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

25% win rate across 8 tracked games — your weakest map with enough games to be worth reading into.

Mirage callouts & strategy →Mirage grenade lineups →

Recent matches

MapScoreRatingHS%Date
dust212–12-0.045%28 Aug →
nuke8–13-0.048%28 Aug →
ancient13–70.0012%27 Aug →
anubis13–10-0.029%27 Aug →
dust213–9-0.0213%27 Aug →
dust213–6-0.0211%27 Aug →
cache13–6-0.0216%27 Aug →
cache5–70.0319%27 Aug →
nuke10–13-0.026%27 Aug →
dust28–13-0.083%27 Aug →
cache13–5-0.0113%26 Aug →
anubis13–10-0.066%26 Aug →
dust213–5-0.0610%26 Aug →
dust21–8-0.068%26 Aug →
inferno11–13-0.0616%25 Aug →
dust212–12-0.0110%25 Aug →
nuke11–13-0.0712%25 Aug →
dust213–60.0115%25 Aug →
ancient2–13-0.1116%24 Aug →
dust28–130.068%24 Aug →
dust27–90.006%24 Aug →
cache9–130.0312%24 Aug →
nuke13–8-0.035%24 Aug →
inferno12–120.018%24 Aug →
ancient13–50.0016%23 Aug →
dust212–12-0.0110%23 Aug →
nuke13–90.0210%23 Aug →
cache6–13-0.0312%23 Aug →
dust210–13-0.0218%23 Aug →
mirage1–13-0.0111%23 Aug →
nuke13–9-0.0213%23 Aug →
ancient9–13-0.0320%23 Aug →
dust21–13-0.066%22 Aug →
dust26–13-0.0221%22 Aug →
ancient13–11-0.0611%22 Aug →
inferno13–10-0.0116%21 Aug →
dust210–13-0.0911%21 Aug →
nuke7–130.0012%21 Aug →
dust210–13-0.0815%21 Aug →
dust23–13-0.0922%20 Aug →
nuke10–13-0.0710%20 Aug →
anubis12–120.0413%20 Aug →
dust213–11-0.0218%20 Aug →
inferno13–10-0.0414%16 Aug →
inferno13–9-0.058%16 Aug →
ancient12–12-0.0610%16 Aug →
dust213–30.0111%16 Aug →
dust29–130.0216%16 Aug →
ancient4–13-0.0413%16 Aug →
nuke13–11-0.056%15 Aug →
ancient7–13-0.0211%15 Aug →
nuke12–12-0.017%15 Aug →
dust213–30.0310%15 Aug →
cache12–12-0.0418%14 Aug →
mirage10–13-0.087%14 Aug →
ancient13–6-0.0217%14 Aug →
inferno13–4-0.0716%14 Aug →
dust25–13-0.0120%14 Aug →
dust213–11-0.0217%14 Aug →
anubis13–10.0910%14 Aug →
inferno9–130.039%13 Aug →
cache8–130.0115%12 Aug →
ancient13–60.0814%12 Aug →
dust213–70.0512%12 Aug →
dust24–13-0.0517%12 Aug →
nuke13–60.0511%12 Aug →
nuke13–110.0210%12 Aug →
nuke12–12-0.0517%11 Aug →
ancient13–70.0212%11 Aug →
dust213–10-0.0511%11 Aug →
dust210–13-0.0214%11 Aug →
nuke2–13-0.0711%11 Aug →
inferno13–8-0.028%10 Aug →
dust28–13-0.009%10 Aug →
cache5–13-0.0115%10 Aug →
dust29–20.029%10 Aug →
mirage11–13-0.063%10 Aug →
cache6–11-0.0023%9 Aug →
dust213–9-0.0418%8 Aug →
dust26–13-0.0814%8 Aug →
ancient11–13-0.049%8 Aug →
dust213–11-0.0610%8 Aug →
nuke13–80.039%7 Aug →
dust210–130.0218%7 Aug →
mirage10–13-0.0810%7 Aug →
anubis6–13-0.0717%7 Aug →
nuke13–90.0110%7 Aug →
dust210–13-0.0226%7 Aug →
cache13–6-0.0113%3 Aug →
mirage13–11-0.0115%3 Aug →
dust210–130.0116%3 Aug →
ancient9–130.032%3 Aug →
anubis7–13-0.019%2 Aug →
dust212–12-0.0128%2 Aug →
mirage11–13-0.0416%2 Aug →
ancient7–130.027%2 Aug →
mirage12–12-0.0624%2 Aug →
nuke7–13-0.0513%2 Aug →
mirage13–5-0.025%2 Aug →
dust26–13-0.1221%2 Aug →

Match data via Leetify.

Recent teammates

Milestones

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

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