White Boy Basketball 2011 — CS2 Stats
TM76561198107674988[U:1:147409260]Steam profile ↗✓ No bans
What changed since last observed
CSDB last observed this profile on 23 Sep 2026 (24 days ago). Ranks are recorded once per day this page is viewed.
Rating over time
Premier CS Rating
- At peak — 2,589
- Next: Light Blue band at 5,000 — 2,411 to go
Premier is CSDB’s own observation — it builds from the day a profile is first viewed and cannot be backfilled.
Compare periods
Last 30 days vs previous 30
| Metric | Last 30 | Previous 30 | Change |
|---|---|---|---|
| Matches | 41 | — | — |
| Win rate | 39% | — | — |
| K/D | 0.55 | — | — |
| Headshot % | 43% | — | — |
Measured 18 Sep 2026 → 17 Oct 2026; no observation near 60 days ago, so there is no previous window yet.
Differences between Valve's lifetime totals on the days CSDB observed this profile — every mode Valve counts, not only ranked. A window appears only when an observation sits within a few days of each end.
How this compares with the same rank
Median values for Grey band among CSDB-tracked players (n=3,645), 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.
| Metric | This player | Grey band median | Light Blue band median | vs Light Blue band |
|---|---|---|---|---|
| Headshot rate | 31.4% | 38.2% | 39.9% | 8.5% short |
| Shot accuracy | 12.8% | 3.6% | 7.0% | above |
| Kill/death ratio | 0.75 | 0.83 | 0.92 | 0.17 short |
| Match win rate | 29.0% | 40.2% | 42.3% | 13.3% short |
This profile matches the typical Light Blue band player on 1 of 4 comparable metrics.
Widest gap: Match win rate. That is the metric furthest from the Light Blue band median in relative terms — not necessarily the one holding a rank back, which no statistic here can establish.
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Performance scores
0–100 skill scores via Leetify.
Recent form
Last 10 vs previous 10: −20pp win rate · +0.02 avg rating · +3.4pp headshot accuracy · +29ms reaction
Win rate down 20pp across the last 10 against the 10 before — more than a 10-match window's normal noise (±20pp). Average match rating moved the other way (+0.02), so results shifted more than performance did.
Last 5 · 10 · 20 matches
Last 5
- 3–0–2 · 60% win rate
- Avg rating -0.05
- Avg headshot accuracy 10%
- Avg reaction 737ms
Last 10
- 4–4–2 · 40% win rate
- Avg rating -0.05
- Avg headshot accuracy 11%
- Avg reaction 741ms
Last 20
- 10–8–2 · 50% win rate
- Avg rating -0.06
- Avg headshot accuracy 10%
- Avg reaction 726ms
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).
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 ZywOo 55% 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. 709ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.
Counter-strafing. Only 50% 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
Composite 2.0/10 (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
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
Across the last 100 tracked matches.
Highlights
Map breakdown
| Map | Grade | Played | Record | Win rate | Avg rating |
|---|---|---|---|---|---|
 nuke | D | 29 | 9–20 | 31% | -0.05 |
 dust2 | A | 28 | 16–12 | 57% | -0.05 |
 cache | D | 16 | 4–12 | 25% | -0.05 |
 inferno | D | 10 | 2–8 | 20% | -0.06 |
 mirage | D | 6 | 2–4 | 33% | -0.07 |
 ancient | A | 5 | 3–2 | 60% | -0.05 |
 vertigo | — | 3 | 1–2 | 33% | -0.05 |
| office | — | 2 | 1–1 | 50% | -0.04 |
 train | — | 1 | 1–0 | 100% | -0.05 |
Across the last 100 tracked matches.
Inferno is currently your weakest sufficiently-sampled map (20% over 10). Start with the 6 essential Inferno lineups, review the callouts, then spin up a practice server.
Lifetime stats
Most-used weapons
Lifetime map wins
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.
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 MechanicsAim Training →
Your crosshair sits further from where enemies appear than it needs to. Crosshair placement is the cheapest accuracy you can buy.
Preaim 12.9791° — above the 12° mark we flag
- Best CS2 CrosshairAim Training →
Your shots are landing on bodies more often than heads — usually a crosshair-height and placement habit rather than raw aim.
Headshot accuracy 9.2023% — below the 15% mark we flag
- Best CS2 SettingsAim Training →
Slow first shots are as often a setup problem as a reflex one — framerate, sensitivity and crosshair visibility all move this number.
Reaction time 708.8934ms — above the 700ms mark we flag
Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.
20% win rate across 10 tracked games — your weakest map with enough games to be worth reading into.
Recent matches
| Map | Score | Rating | HS% | Date | |
|---|---|---|---|---|---|
| nuke | 12–12 | -0.07 | 0% | 9 Oct → | |
| dust2 | 13–8 | -0.02 | 20% | 9 Oct → | |
| cache | 13–9 | 0.01 | 11% | 8 Oct → | |
| train | 13–2 | -0.05 | 10% | 8 Oct → | |
| dust2 | 12–12 | -0.09 | 11% | 30 Sept → | |
| dust2 | 11–13 | -0.04 | 11% | 30 Sept → | |
| cache | 6–13 | -0.04 | 10% | 27 Sept → | |
| dust2 | 9–13 | -0.04 | 8% | 27 Sept → | |
| dust2 | 13–10 | -0.04 | 26% | 24 Sept → | |
| vertigo | 1–13 | -0.10 | 8% | 24 Sept → | |
| nuke | 13–5 | -0.01 | 10% | 24 Sept → | |
| cache | 13–11 | -0.04 | 3% | 24 Sept → | |
| dust2 | 13–8 | -0.03 | 9% | 24 Sept → | |
| ancient | 13–9 | -0.10 | 8% | 23 Sept → | |
| nuke | 4–13 | -0.11 | 8% | 23 Sept → | |
| dust2 | 5–13 | -0.09 | 13% | 22 Sept → | |
| nuke | 13–7 | -0.08 | 6% | 22 Sept → | |
| dust2 | 13–9 | -0.10 | 15% | 22 Sept → | |
| dust2 | 2–13 | -0.07 | 8% | 22 Sept → | |
| nuke | 4–13 | -0.07 | 0% | 21 Sept → | |
| inferno | 2–13 | -0.10 | 9% | 21 Sept → | |
| dust2 | 7–13 | -0.11 | 0% | 21 Sept → | |
| dust2 | 13–11 | -0.07 | 11% | 19 Sept → | |
| nuke | 11–13 | -0.04 | 10% | 19 Sept → | |
| nuke | 13–9 | -0.05 | 5% | 18 Sept → | |
| cache | 12–12 | -0.11 | 17% | 18 Sept → | |
| dust2 | 6–13 | -0.07 | 3% | 18 Sept → | |
| inferno | 9–13 | -0.06 | 15% | 18 Sept → | |
| ancient | 13–10 | -0.05 | 6% | 17 Sept → | |
| nuke | 12–12 | -0.06 | 4% | 16 Sept → | |
| dust2 | 13–4 | -0.00 | 10% | 16 Sept → | |
| dust2 | 13–6 | -0.09 | 18% | 15 Sept → | |
| dust2 | 6–0 | -0.12 | 0% | 15 Sept → | |
| mirage | 3–13 | -0.11 | 0% | 14 Sept → | |
| nuke | 6–13 | -0.06 | 7% | 11 Sept → | |
| cache | 8–13 | -0.09 | 6% | 10 Sept → | |
| dust2 | 13–5 | 0.01 | 13% | 10 Sept → | |
| cache | 10–13 | -0.04 | 2% | 9 Sept → | |
| nuke | 13–8 | -0.06 | 9% | 9 Sept → | |
| mirage | 13–4 | -0.09 | 9% | 8 Sept → | |
| dust2 | 8–13 | -0.08 | 16% | 6 Sept → | |
| nuke | 1–13 | -0.07 | 8% | 4 Sept → | |
| mirage | 11–13 | -0.07 | 14% | 4 Sept → | |
| cache | 2–12 | -0.04 | 0% | 2 Sept → | |
| dust2 | 7–13 | -0.07 | 20% | 2 Sept → | |
| dust2 | 13–8 | -0.07 | 6% | 1 Sept → | |
| nuke | 7–13 | -0.07 | 17% | 27 Aug → | |
| cache | 13–11 | -0.11 | 18% | 19 Aug → | |
| inferno | 6–9 | -0.04 | 8% | 14 Aug → | |
| office | 10–13 | -0.04 | 10% | 14 Aug → | |
| dust2 | 9–13 | -0.03 | 6% | 14 Aug → | |
| inferno | 13–8 | -0.10 | 13% | 13 Aug → | |
| cache | 13–4 | -0.04 | 31% | 13 Aug → | |
| vertigo | 10–13 | -0.03 | 11% | 12 Aug → | |
| dust2 | 13–3 | -0.04 | 11% | 11 Aug → | |
| dust2 | 13–5 | 0.01 | 10% | 11 Aug → | |
| nuke | 2–13 | -0.08 | 27% | 11 Aug → | |
| cache | 9–13 | -0.07 | 14% | 7 Aug → | |
| office | 13–6 | -0.04 | 13% | 5 Aug → | |
| nuke | 13–8 | -0.07 | 28% | 5 Aug → | |
| nuke | 13–10 | -0.11 | 16% | 4 Aug → | |
| cache | 12–12 | -0.03 | 10% | 4 Aug → | |
| inferno | 9–13 | -0.04 | 19% | 31 Jul → | |
| vertigo | 13–8 | -0.03 | 17% | 26 Jul → | |
| nuke | 6–13 | -0.08 | 14% | 26 Jul → | |
| nuke | 7–13 | 0.06 | 16% | 22 Jul → | |
| dust2 | 13–6 | -0.05 | 21% | 22 Jul → | |
| nuke | 3–13 | -0.04 | 0% | 13 Jul → | |
| ancient | 11–13 | -0.02 | 14% | 9 Jul → | |
| nuke | 9–13 | 0.02 | 7% | 8 Jul → | |
| nuke | 9–13 | 0.01 | 10% | 8 Jul → | |
| inferno | 3–13 | -0.05 | 0% | 30 Jun → | |
| ancient | 13–10 | -0.04 | 13% | 30 Jun → | |
| nuke | 6–13 | -0.04 | 8% | 30 Jun → | |
| mirage | 3–13 | -0.06 | 9% | 17 Jun → | |
| nuke | 10–13 | -0.11 | 5% | 17 Jun → | |
| nuke | 5–13 | 0.00 | 24% | 12 Jun → | |
| nuke | 13–8 | -0.04 | 8% | 6 Jun → | |
| inferno | 10–13 | -0.07 | 19% | 4 Jun → | |
| cache | 6–13 | -0.04 | 13% | 4 Jun → | |
| dust2 | 12–12 | -0.09 | 13% | 18 May → | |
| cache | 5–13 | -0.04 | 12% | 6 May → | |
| cache | 4–13 | -0.03 | 10% | 3 May → | |
| nuke | 2–13 | -0.06 | 14% | 2 May → | |
| cache | 9–13 | -0.02 | 13% | 1 May → | |
| cache | 12–12 | -0.03 | 14% | 28 Apr → | |
| nuke | 10–13 | -0.09 | 5% | 19 Apr → | |
| nuke | 12–12 | -0.07 | 2% | 8 Apr → | |
| nuke | 13–7 | -0.09 | 21% | 8 Apr → | |
| ancient | 8–13 | -0.02 | 8% | 2 Apr → | |
| mirage | 13–11 | -0.03 | 11% | 2 Apr → | |
| dust2 | 13–10 | 0.02 | 4% | 25 Mar → | |
| mirage | 2–13 | -0.08 | 0% | 25 Mar → | |
| inferno | 3–13 | -0.10 | 25% | 25 Mar → | |
| inferno | 10–13 | -0.03 | 20% | 24 Mar → | |
| dust2 | 6–13 | -0.03 | 18% | 24 Mar → | |
| dust2 | 13–6 | -0.03 | 12% | 19 Mar → | |
| nuke | 13–5 | -0.01 | 14% | 19 Mar → | |
| inferno | 13–7 | 0.01 | 8% | 19 Mar → | |
| dust2 | 13–7 | 0.06 | 15% | 18 Mar → |
Match data via Leetify.
Recent teammates
Milestones
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