Boba Tea

Boba Tea — CS2 Stats

CA76561199136253591[U:1:1175987863]Steam profile ↗✓ No bans

196Tracked matches32%Win rate2025Tracked since
CSDB Rating1.8 LearningPositional Player
Ladder ranks via Leetify
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. Today is the first observation — history builds from here and cannot be backfilled. Come back after the next session and the change shows above.

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Performance scores

Aim20
Positioning38
Utility14

0–100 skill scores via Leetify.

Recent form

COLD49438Last 10049%Win rateLWTLWWLLLL

Last 10 vs previous 10: +10pp win rate · −0.05 avg rating · +2.5pp headshot accuracy · −23ms 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

  • 221 · 40% win rate
  • Avg rating -0.08
  • Avg headshot accuracy 11%
  • Avg reaction 656ms

Last 10

  • 361 · 30% win rate
  • Avg rating -0.07
  • Avg headshot accuracy 13%
  • Avg reaction 657ms

Last 20

  • 5141 · 25% win rate
  • Avg rating -0.05
  • Avg headshot accuracy 12%
  • Avg reaction 669ms

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 PlayerPositioning stands above the rest of this profile (+1.8 against its own average).

Aim2.0
Utility1.4
Positioning3.8
Opening Duels0.9

Limited 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.

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

ZywOo

Plays most like ZywOo 71% 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. 630ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Counter-strafing. Only 57% 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

Aim2.0
Positioning3.8
Utility1.4
Mechanics1.5
Opening Duels0.1
Win Impact0.0

Composite 1.8/10 (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-0.04+0.01
first ⅓ avg -0.05 → last ⅓ avg -0.04
Reaction time629ms−108ms
first ⅓ avg 737ms → last ⅓ avg 629ms
Headshot accuracy11.5%−2.9%
first ⅓ avg 14.4% → last ⅓ avg 11.5%

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

0.07Best match rating · 13–1 · nuke, 28 May
58%Best headshot accuracy · 13–1 · nuke, 28 May
469msFastest reaction time · 5–13 · ancient, 22 Aug
13–1Biggest win · nuke, 28 May

Across the last 100 tracked matches.

Highlights

8Longest win streak
44In matches decided by ≤2 rounds

Map breakdown

infernoBest map · 63% over 16ancientWeakest map · 31% over 16
MapGradePlayedRecordWin rateAvg rating
trainB189950%-0.02
mirageA1810856%-0.05
infernoA1610663%-0.04
ancientD1651131%-0.03
nukeB157847%-0.04
dust2A74357%-0.05
overpassC52340%-0.06
cache2020%-0.05
vertigo110100%-0.06
grail110100%-0.05
office1010%-0.02

Across the last 100 tracked matches.

Ancient is currently your weakest sufficiently-sampled map (31% over 16). Start with the 6 essential Ancient 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.

11.8%Headshot accuracy
28.6%Accuracy (enemy spotted)
32.1%Spray accuracy
56.7%Counter-strafing
12.4°Preaim
630msReaction time
30.2%T opening success
30.8%CT opening success
0.33Enemies flashed / flash
1.1%Flash assists
2.94HE damage / grenade
1.81Flashes / 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 12.3825° — 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 11.8408% — 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 0.3347 — below the 0.5 mark we flag

    Grenade Lineups
Spend your practice time on Ancient

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

31% win rate across 16 tracked games — your weakest map with enough games to be worth reading into.

Ancient callouts & strategyAncient grenade lineups

Recent matches

MapScoreRatingHS%Date
train9–13-0.050%22 Aug
dust213–11-0.1117%22 Aug
inferno12–12-0.106%22 Aug
ancient5–13-0.1120%22 Aug
nuke13–8-0.039%22 Aug
mirage13–3-0.0610%22 Aug
cache9–13-0.0917%22 Aug
mirage9–13-0.0314%17 Aug
mirage5–13-0.1027%17 Aug
dust27–13-0.0513%17 Aug
nuke5–13-0.0614%16 Aug
train13–10-0.0521%16 Aug
cache7–13-0.014%16 Aug
dust27–13-0.067%7 May
mirage7–13-0.0814%7 May
train11–130.068%17 Jul
inferno13–90.0610%17 Jul
overpass0–4-0.090%17 Jul
nuke11–130.0111%13 Jul
ancient9–130.0218%13 Jul
train13–70.0012%13 Jul
mirage10–13-0.0613%12 Jul
mirage13–90.0019%11 Jul
train11–13-0.0111%11 Jul
ancient9–13-0.034%11 Jul
nuke4–13-0.080%11 Jul
inferno12–12-0.0610%11 Jul
nuke9–13-0.025%9 Jul
ancient13–20.0311%9 Jul
inferno13–7-0.0820%9 Jul
mirage13–11-0.029%9 Jul
inferno2–13-0.1011%7 Jul
train8–130.0215%7 Jul
ancient9–13-0.015%14 Jun
mirage12–12-0.0514%14 Jun
train13–2-0.019%14 Jun
nuke13–10-0.0829%14 Jun
inferno13–70.0025%14 Jun
train9–130.0214%13 Jun
ancient13–20.0111%13 Jun
nuke7–13-0.080%13 Jun
ancient8–13-0.057%2 Jun
mirage13–11-0.0416%2 Jun
train10–13-0.0618%31 May
overpass13–10-0.083%31 May
mirage13–7-0.050%31 May
inferno13–5-0.0613%31 May
ancient6–13-0.030%31 May
train10–00.0110%28 May
overpass13–30.0310%28 May
ancient13–60.0318%28 May
mirage13–6-0.0518%28 May
nuke13–10.0758%28 May
inferno13–5-0.019%28 May
nuke13–4-0.0022%24 May
inferno13–7-0.0023%24 May
overpass8–13-0.0616%24 May
inferno13–80.014%24 May
train13–5-0.0618%24 May
mirage13–5-0.0516%24 May
ancient12–12-0.114%24 May
inferno12–12-0.0610%24 May
mirage13–8-0.0213%23 May
nuke13–3-0.0315%23 May
vertigo13–7-0.0613%23 May
train12–12-0.0416%23 May
inferno13–3-0.028%23 May
ancient6–13-0.0724%22 May
mirage5–13-0.0114%22 May
nuke13–8-0.039%22 May
inferno13–20.0021%22 May
train9–13-0.0611%22 May
mirage12–12-0.0519%21 May
nuke13–9-0.100%21 May
train13–7-0.068%21 May
ancient13–50.010%21 May
dust213–8-0.1016%21 May
ancient13–70.0110%16 May
train13–7-0.0318%15 May
train3–0-0.0617%15 May
overpass3–13-0.0822%15 May
mirage7–13-0.066%15 May
ancient7–13-0.025%15 May
inferno13–3-0.0225%15 May
nuke10–13-0.0514%15 May
dust213–4-0.0026%15 May
nuke5–13-0.0825%14 May
grail13–10-0.0516%14 May
inferno7–13-0.097%1 May
ancient8–13-0.097%1 May
nuke12–12-0.0314%1 May
mirage13–4-0.0717%1 May
office11–13-0.029%22 Apr
train10–13-0.0124%22 Apr
dust213–110.066%22 Apr
mirage13–6-0.110%19 Apr
inferno5–13-0.0813%19 Apr
dust25–13-0.0950%19 Apr
train13–10-0.0714%19 Apr
ancient9–13-0.0810%14 Apr

Match data via Leetify.

Recent teammates

Milestones

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