Big Swang Theory

Big Swang Theory — CS2 Stats

BQ76561197994338755[U:1:34073027]Steam profile ↗✓ No bans

2,207Tracked matches43%Win rate2021Tracked since
3,755Hours in CS38Hrs last 2 wks
CSDB Rating4.4 DevelopingSupport
Premier CS Rating8,948Light Blue band · top ~59.9% of ranked players (population est.)
FaceitLevel 2Top 97.9% of ranked FACEIT players
Ladder ranks via Leetify

What changed since last observed

CSDB last observed this profile on 16 Sep 2026 (2 days ago). Ranks are recorded once per day this page is viewed.

−322Premier CS Rating · 9,270 → 8,948
+15Tracked matches · now 2,207
−6.7ppWin rate · 50.0% → 43.3%
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. 27 days played since 12 Aug 2026. Come back after the next session and the change shows above.

Is this you? Sign in with Steam to claim it and connect match tracking →

Rating over time

Premier CS Rating: 8,948 -671 21 Aug18 Sept · 8 days played
8,9149,824peak 9,82421 Aug18 Sept
9,983Peak Premier in tracked matches
27Days played since 2026-08-12

Premier CS Rating

  • 876 below peak (9,824)
  • -671 over 30 days · declining
  • Next: Blue band at 10,000 1,052 to go
  • Reached: Light Blue band
  • Light Blue band first seen 2026-09-08

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

How this compares with the same rank

Median values for Level 2 among CSDB-tracked players (n=5,197), from Valve's own lifetime stats. Aim, positioning and utility scores are deliberately not benchmarked here — those are a third-party provider's derived metrics, which CSDB does not store.

MetricThis playerLevel 2 medianLevel 3 medianvs Level 3
Headshot rate33.5%41.3%41.9%8.4% short
Shot accuracy9.1%12.7%12.2%3.1% short
Kill/death ratio0.850.960.980.13 short
Match win rate42.3%42.5%43.3%1.0% short

This profile sits below the typical Level 3 player on every metric we can compare.

Widest gap: Shot accuracy. That is the metric furthest from the Level 3 median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.

Share this profile

CSDB.GGBig Swang TheoryFACEITLevel 2STANDINGTop 97.9% of rankedPREMIER8,948 · Light Blue bandcsdb.gg/stats

The image is a snapshot; the link keeps updating. Nothing here is published anywhere — it is generated in your browser when you click.

Performance scores

Aim53
Positioning58
Utility59

0–100 skill scores via Leetify.

Recent form

COLD405010Last 10040%Win rateWLLLLWLLWL

Last 10 vs previous 10: −10pp win rate · −0.01 avg rating · −1.9pp headshot accuracy · +56ms reaction

Win rate −10pp across the last 10 against the 10 before — within the normal variation of a 10-match window (±20pp), so no real shift yet.

Last 5 · 10 · 20 matches

Last 5

  • 14 · 20% win rate
  • Avg rating -0.00
  • Avg headshot accuracy 12%
  • Avg reaction 571ms

Last 10

  • 37 · 30% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 13%
  • Avg reaction 592ms

Last 20

  • 713 · 35% win rate
  • Avg rating -0.01
  • Avg headshot accuracy 14%
  • Avg reaction 564ms

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: SupportUtility contribution stands above the rest of this profile (+1.2 against its own average).

Aim5.3
Utility5.9
Positioning5.8
Opening Duels2.5

Strong T-side opener

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

NiKo

Plays most like NiKo 71% playstyle similarity

Most alike: utility contribution, positioning profile.

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

Strengths

T openings. 61% T opening-duel success — entries that actually open the round.

Areas to improve

CT openings. Opening success drops from 61% on T to 29% on CT — first contacts on the defending side are being lost.

Reaction time. 561ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 69% 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

Aim5.3
Positioning5.8
Utility5.9
Mechanics4.2
Opening Duels3.9
Win Impact2.8

Composite 4.4/10 (Developing), 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 rating0.01+0.02
first ⅓ avg -0.01 → last ⅓ avg 0.01
Reaction time557ms−47ms
first ⅓ avg 604ms → last ⅓ avg 557ms
Headshot accuracy14.9%−0.3%
first ⅓ avg 15.2% → last ⅓ avg 14.9%

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.

Personal bests

0.21Best match rating · 13–2 · dust2, 12 Sept
31%Best headshot accuracy · 13–4 · dust2, 15 Aug
406msFastest reaction time · 13–6 · office, 17 Sept
13–1Biggest win · dust2, 23 Aug

Across the last 100 tracked matches.

Highlights

5Longest win streak
105In matches decided by ≤2 rounds
4Overtime games

Map breakdown

infernoBest map · 50% over 8dust2Weakest map · 40% over 63
MapGradePlayedRecordWin rateAvg rating
dust2C63253840%-0.00
nukeC94544%-0.01
infernoB84450%0.02
cacheC52340%0.02
office43175%0.05
vertigo31233%0.01
ancient2020%-0.02
boulder2020%-0.04
mirage21150%0.01
overpass1010%-0.04
italy1010%-0.08

Across the last 100 tracked matches.

Dust 2 is currently your weakest sufficiently-sampled map (40% over 63). Start with the 6 essential Dust 2 lineups, review the callouts, then spin up a practice server.

Lifetime stats

66,314Lifetime kills
0.85K/D
4,823Matches
42.3%Match win rate
33.5%Headshot %
9.1%Shot accuracy
8,086MVPs
1,824Hours (in match)
5,991Bombs planted
1,238Bombs defused

Most-used weapons

AK-4715,518
AWP8,521
Tec-93,481
SSG 082,445
P902,443
XM10142,429
Negev2,230

Lifetime map wins

23,161dust2
3,002inferno
2,453nuke
1,525office
1,494vertigo
543train
292cbble
81italy

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

Skill profile

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

14.7%Headshot accuracy
33.5%Accuracy (enemy spotted)
37.5%Spray accuracy
69.0%Counter-strafing
11.4°Preaim
561msReaction time
61.3%T opening success
29.0%CT opening success
0.51Enemies flashed / flash
1.8%Flash assists
9.76HE damage / grenade
10.67Flashes / 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. 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 14.7081% — below the 15% mark we flag

    Aim Training
  2. Advanced Mechanics

    Losing the first CT duel repeatedly usually means holding angles that favour the peeker.

    CT opening duels 29.0223% — below the 40% mark we flag

Spend your practice time on Dust 2

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

40% win rate across 63 tracked games — your weakest map with enough games to be worth reading into.

Dust 2 callouts & strategyDust 2 grenade lineups

Recent matches

MapScoreRatingHS%Date
office13–60.108%18 Sept
ancient8–13-0.026%18 Sept
dust22–13-0.058%18 Sept
boulder10–13-0.0712%18 Sept
dust25–130.0328%18 Sept
dust213–11-0.008%18 Sept
dust28–13-0.028%18 Sept
dust27–13-0.0317%18 Sept
dust213–11-0.0418%17 Sept
vertigo3–13-0.0114%17 Sept
inferno9–13-0.0114%17 Sept
nuke4–13-0.035%17 Sept
overpass7–13-0.0417%17 Sept
office13–60.0010%17 Sept
dust213–70.0227%17 Sept
nuke13–70.0213%16 Sept
cache13–100.045%16 Sept
nuke11–130.0110%16 Sept
dust211–13-0.0222%16 Sept
dust23–13-0.0123%15 Sept
nuke16–140.0512%15 Sept
inferno13–30.095%15 Sept
dust213–60.0317%15 Sept
dust213–40.1324%14 Sept
cache13–6-0.0320%14 Sept
dust210–130.0523%14 Sept
dust213–40.1021%14 Sept
dust28–130.0220%14 Sept
ancient5–13-0.0218%14 Sept
dust22–7-0.015%14 Sept
dust28–13-0.1213%14 Sept
cache11–130.0618%13 Sept
nuke13–4-0.0221%13 Sept
inferno13–30.0724%13 Sept
dust212–12-0.0226%13 Sept
dust213–6-0.078%12 Sept
dust23–130.0119%12 Sept
dust213–20.2112%12 Sept
dust213–100.0218%11 Sept
inferno12–12-0.0419%11 Sept
dust213–11-0.0021%11 Sept
nuke10–13-0.0613%11 Sept
dust23–13-0.068%11 Sept
dust27–130.005%10 Sept
cache8–13-0.0113%8 Sept
dust26–130.0215%8 Sept
dust213–110.0025%8 Sept
dust212–120.0113%7 Sept
dust25–13-0.0213%7 Sept
boulder2–13-0.0115%7 Sept
dust24–13-0.057%4 Sept
dust213–40.016%4 Sept
dust25–130.0227%4 Sept
mirage15–150.0511%28 Aug
dust212–12-0.0123%28 Aug
dust24–13-0.0613%28 Aug
vertigo13–80.0515%28 Aug
vertigo9–13-0.0010%25 Aug
dust27–13-0.0116%25 Aug
nuke13–6-0.019%25 Aug
inferno13–110.029%25 Aug
dust211–13-0.0622%24 Aug
office13–100.0711%24 Aug
office10–130.049%24 Aug
dust213–80.0717%24 Aug
dust213–10.0014%23 Aug
dust212–12-0.0217%23 Aug
dust27–13-0.0615%22 Aug
dust213–20.0124%22 Aug
nuke4–13-0.0328%21 Aug
dust213–100.0725%21 Aug
dust215–15-0.0311%21 Aug
dust213–60.1326%20 Aug
cache10–130.0310%20 Aug
dust27–13-0.1114%19 Aug
inferno6–130.026%19 Aug
dust213–110.0319%19 Aug
dust213–10-0.060%18 Aug
inferno10–13-0.026%17 Aug
mirage13–11-0.0210%17 Aug
dust212–12-0.0116%17 Aug
dust22–13-0.0820%17 Aug
dust212–12-0.0315%16 Aug
dust210–13-0.0811%16 Aug
dust29–13-0.0021%16 Aug
dust213–50.0612%15 Aug
dust29–13-0.079%15 Aug
dust28–130.0619%15 Aug
dust23–20.0518%15 Aug
dust213–4-0.0131%15 Aug
nuke2–13-0.0110%14 Aug
dust216–14-0.0213%14 Aug
dust213–6-0.0218%14 Aug
italy5–13-0.080%14 Aug
dust210–130.0510%14 Aug
dust28–13-0.0723%13 Aug
inferno13–100.0321%13 Aug
dust213–7-0.0118%13 Aug
dust211–13-0.037%13 Aug
dust212–12-0.0417%12 Aug

Match data via Leetify.

Recent teammates

Milestones

1,000 Matches
Compare this player with someone →Inventory value for this account →Where does this rating sit? Premier rank tiers →