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CS2 AI Predictions — Machine Learning Match Analysis

AI-powered CS2 match predictions generated by our machine learning model. Every prediction analyzes team form, player statistics, map pool matchups, head-to-head records and real-time betting odds to deliver data-driven picks with transparent confidence ratings and tracked accuracy.

AI

Powered by Machine Learning

Our AI prediction engine analyzes 8+ statistical dimensions per match: 3-month team form, map-specific win rates, head-to-head history, individual player ratings (ADR, KAST%, HLTV 2.0), roster stability, tournament seeding, schedule fatigue and real-time bookmaker odds. Predictions are generated automatically every 6-12 hours for all upcoming professional CS2 matches.

AI Win Rate
64.7%
Correct
297
Wrong
162
Pending
11
AI Prediction Record
297W
162L
459 decided AI predictions 64.7% accuracy

Ongoing AI Predictions 11

AI NOT_STARTED 9 Jul 2026
ADN
vs
PURE

Elimination match: ADN vs PURE — Prediction & Match Analysis

This United21 Season 52 elimination match features two lower-tier European teams with limited data. Alpha Dominion Nation (ADN) hold a 2W-6L record in their last 8 matches, while PURE went 4W-6L in their last 10. Neither team has a career win rate recorded, and there is no H2H history. The betting market strongly favors PURE at 1.22 vs ADN's 3.80, implying roughly an 82% win probability for PURE.However, the player stat comparison tells a different story: ADN average a 0.703 rating vs PURE's 0.639, with higher ADR (53.4 vs 47.3) and KAST (48.9% vs 46.2%). ADN's Kosovo-based roster — sopA, Edzz, Cashmoney, R0Kk-_, and xom — outperforms PURE's squad on every individual metric. PURE lost their opening match in United21 Season 52 to IC Prospects 0-2, suggesting they are struggling in this tournament.The odds heavily favor PURE, but the player stats favor ADN. This discrepancy may reflect PURE's better tournament record or factors not captured in the available data. Given the stat advantage for ADN and PURE's recent 0-2 loss in this same tournament, we lean toward ADN as a value pick — though the low confidence reflects the significant data limitations and the market's strong disagreement.

Predicted: Alpha Dominion Nation 60% conf.
AI NOT_STARTED 9 Jul 2026
RUST
vs
Honvéd

RUST vs Honvéd — Prediction & Match Analysis

This European Pro League Series 8 match pits two lower-tier teams against each other with no H2H history. RUSTEC's recent form is concerning — just 2W-8L in their last 10 (20% win rate) — but their career win rate of 54.0% is significantly better than Honvéd's 33.33%. Honvéd's 5W-5L recent form is more balanced, but their career record suggests they are a weaker team overall.On player stats, RUSTEC hold a clear edge: their roster averages a 1.051 rating vs Honvéd's 0.980, with higher ADR (74.1 vs 71.1) and KAST (69.8% vs 67.6%). RUSTEC's top players — supra, Brilliance, anttzz, youka, and jakekeS — have the individual quality to outperform Honvéd's roster. The stat differential is consistent across all three key metrics.The tension here is between RUSTEC's poor recent form (2W-8L) and their superior player stats and career record. The recent form slump may reflect scheduling variance or opponent quality rather than a fundamental decline. Given the player stat advantage and career win rate edge, RUSTEC are the marginal pick, but this is a low-confidence call given their recent results.

Predicted: RUSTEC 58% conf.
AI NOT_STARTED 9 Jul 2026
ALL
vs
NEM

Quarterfinal 2: ALL vs NEM — Prediction & Match Analysis

This XSE Pro League quarterfinal is a competitive matchup between two ranked teams. Alliance (#61 HLTV) and Team Nemesis (#72 HLTV) are closely matched on paper, but the data points to Nemesis as the slight edge. Nemesis's 7W-3L recent form (70%) is strong, though Alliance's 9W-1L run is exceptional — the best recent form of any team in today's slate.The player stat comparison favors Nemesis: their roster averages a 1.092 rating vs Alliance's 1.042, with higher ADR (75.0 vs 72.3) and KAST (72.2% vs 70.1%). Nemesis's CIS-based roster — featuring SELLTER, r3salt, mag1k3Y, Sdaim, and tex1y — has been building momentum since their peak ranking of #43 in February 2026. The betting market is split: Thunderpick favors Alliance (1.78) while Epicbet favors Nemesis (1.75), reflecting genuine uncertainty.Alliance's 9W-1L form is the strongest counter-argument — that level of consistency suggests the team is peaking. However, Nemesis's superior player stats and career win rate (61.39% vs 57.71%) give them the statistical edge. With no H2H history, we lean on the stats: Nemesis by a slim margin in what should be a close Bo3.

Predicted: Team Nemesis 60% conf.
AI NOT_STARTED 9 Jul 2026
G1
vs
BRUTE

G1 vs BRUTE — Prediction & Match Analysis

GenOne are the clear favorites in this European Pro League Series 8 match, and the betting market agrees — odds of 1.35/1.37 imply roughly a 73% win probability. GenOne's 7W-3L recent form (70%) comfortably outpaces Brute's 6W-4L (60%), and their career win rate of 52.58% vs Brute's 37.39% reflects a significant quality gap. Most importantly, GenOne hold a 2-0 H2H record against Brute, including two clean sweeps.The player stat comparison is nuanced: Brute's roster averages a slightly higher rating (0.991 vs GenOne's 0.953) and ADR (70.9 vs 66.8), which is the main argument for an upset. However, GenOne's French roster — featuring Keoz, Djoko, Brooxsy, Chucky, and bL4SEZ — has demonstrated superior tactical cohesion in their H2H meetings. The KAST averages are nearly identical (68.1% vs 67.9%).The H2H dominance (2-0) is the decisive factor here. Brute's slightly better individual stats haven't translated into wins against GenOne, suggesting a tactical or stylistic mismatch that favors the French side. GenOne are the pick, though Brute's individual firepower means this could be competitive on individual maps.

Predicted: GenOne 67% conf.
AI NOT_STARTED 9 Jul 2026
LAG
vs
OT

Quarterfinal 2: LAG vs OT — Prediction & Match Analysis

This BLAST Open NA Qualifier quarterfinal is the most uncertain match of the day. LAG Gaming carry a 5W-5L record in their last 10 matches and a career win rate of 41.23%, while Overtake have only 3 recent matches on record (1W-2L) with no career stats available — making this a data-limited prediction. There is no H2H history between these teams.On player stats, Overtake hold a slight edge: their roster averages a 1.026 rating vs LAG's 1.012, with sacrifice (1.08 rating, 75.06 ADR) leading the way. LAG's best player Cryptic posts a 1.07 rating but the team's overall ADR (72.0) and KAST (69.7%) are marginally below Overtake's 72.8 ADR and 69.6% KAST. The differences are minimal across the board.Given the limited data on Overtake and LAG's poor career win rate (41.23%), this is effectively a coin flip. Overtake's slightly superior player ratings give them a marginal edge, but bettors should treat this as a high-variance match. The BLAST Open qualifier format means both teams are motivated, and either outcome is plausible.

Predicted: Overtake Sector 55% conf.
AI NOT_STARTED 9 Jul 2026
TYLOO
vs
9z

Quarterfinal 1: TYLOO vs 9z — Prediction & Match Analysis

9z enter this XSE Pro League quarterfinal as the slight favorites, backed by both the betting market (odds of 1.58/1.62 vs TYLOO's 2.24/2.20) and their superior global ranking (#25 vs TYLOO's #30). 9z's career win rate of 67.55% significantly outpaces TYLOO's 62.64%, and their recent IEM Cologne Major 2026 run — defeating Vitality and The MongolZ before falling to FURIA — demonstrates top-tier competitive pedigree.On player stats, 9z hold a marginal edge: their roster averages a 1.103 rating vs TYLOO's 1.091, with higher ADR (75.1 vs 73.6) and comparable KAST (72.0% vs 72.0%). TYLOO's recent form is stronger (7W-3L vs 9z's 5W-5L), which is the main argument for an upset. The H2H record favors 9z 1-0, though the sample is limited.The odds imply roughly a 38/62 split in 9z's favor, which aligns with our assessment. TYLOO's hot recent form (7W-3L) is the key variable — if they carry that momentum into this Bo3, they can compete. But 9z's higher ranking, better career stats, and recent Major experience make them the pick.

Predicted: 9z 62% conf.
AI NOT_STARTED 9 Jul 2026
VOCA
vs
NT

Quarterfinal 3: VOCA vs NT — Prediction & Match Analysis

This BLAST Open NA Qualifier quarterfinal is one of the most lopsided matchups of the day. Voca arrive with a 6W-4L record in their last 10 and a career win rate of 65.67%, while NuTorious have collapsed to just 3W-7L in their last 10 (30% win rate) and carry a career win rate of only 41.18%. The gap in recent form is stark and consistent.The player stat differential is decisive. Voca's roster averages a 1.117 rating with 76.1 ADR and 72.0% KAST, led by dea (1.21 rating, 1.31 K/D), junior (1.20 rating, 1.31 K/D), and Jeorge (1.17 rating, 79.41 ADR). NuTorious, by contrast, average just 0.937 rating with 68.1 ADR and 66.5% KAST — their best player jr24racing posts only a 1.04 rating. Voca's top-3 outperforms NuTorious's entire roster.With no H2H history between these teams, we rely entirely on form and stats — both of which point overwhelmingly to Voca. NuTorious reportedly disbanded in May 2026 and reformed, which may explain their poor recent results. Voca are the strong pick here, though the Bo3 format gives NuTorious a theoretical chance to steal a map.

Predicted: Voca 74% conf.
AI NOT_STARTED 9 Jul 2026
MARS
vs
REGAIN

Quarterfinal 4: MARS vs REGAIN — Prediction & Match Analysis

Marsborne enter this BLAST Open North American Qualifier quarterfinal as the clear statistical favorite. Their 7W-3L record in the last 10 matches (70% win rate) outpaces regain's 6W-4L (60%), and their career win rate of 60.36% vs regain's 53.24% reflects a more established pedigree. Marsborne also hold the only H2H meeting on record, a 2-0 victory over regain in January 2026.The player stat comparison further favors Marsborne. Their roster averages a 1.057 rating vs regain's 1.019, with star fragger Wumbo posting a 1.27 rating and 84.49 ADR — the highest individual output in this matchup. marekiew (1.15 rating) and ogwizard (1.13) provide a deep top-3 that regain cannot match, as their best player Zucar sits at 1.16 but the drop-off to the rest of the roster is steeper.Both teams have similar KAST averages (70.4% vs 70.3%), suggesting comparable round consistency, but Marsborne's superior form, H2H edge, and higher individual ceiling make them the pick in this Bo3. This is a BLAST Open qualifier with significant stakes — Marsborne's experience in this format gives them an additional edge.

Predicted: Marsborne 63% conf.
AI RUNNING 8 Jul 2026
LDP
vs
FDB

Quarterfinal 2: LDP vs FDB — Prediction & Match Analysis

largadosypelados (LDP) face Fake do Biru (FDB) in the CCT South America Playoffs. LDP arrive with a 6W-4L record in their last 10 (60% win rate) versus FDB's 5W-5L (50%). LDP's career winrate of 65.29% (79W-42L) is significantly higher than FDB's 52.17% (36W-33L), reflecting a more established and successful organization. LDP's roster is deep: desh leads at 1.10 rating (71.52 ADR, 70.42% KAST), supported by realz1n (1.07 rating, 73.55% KAST), Alisson (1.06 rating), zmb (1.05 rating), and happ (1.05 rating). Their team average of ~1.06 rating across the top five is solid.Head-to-head history favors Fake do Biru at 4-2 in direct meetings, which is the main concern for LDP. However, the most recent H2H result went to LDP — they beat FDB 2-0 on June 27, 2026, suggesting the momentum has shifted. FDB's roster shows hardzao (1.11 rating) and detr0ittJ (1.11 rating) as their top performers, with Tuurtle (1.09) and pesadelo (1.09) providing strong support. FDB's team average is comparable to LDP's, making this a close individual matchup.The betting market prices LDP at 1.64 (implied ~61% probability) and FDB at 2.13 (implied ~47%), aligning with our assessment. LDP's superior career winrate, better recent form, and the momentum from their June 27 win over FDB give them the edge. The H2H deficit (2-4) is the main counterargument, but the trend is moving in LDP's favor. This is a competitive match with LDP holding a slight statistical advantage.

Predicted: largadosypelados 60% conf.
AI NOT_STARTED 8 Jul 2026
LEO
vs
Prestige Academy

Elimination match: LEO vs Prestige Academy — Prediction & Match Analysis

This United21 Season 52 Group B elimination match between LEO and Prestige Academy presents significant analytical challenges due to limited data for both teams. LEO have gone 0W-3L in their last 3 matches, losing to FaZe Up Next (0-2), venom (0-2), and train launcher (1-2). Prestige Academy have only 1 recorded match in the database — a 1-2 loss to Västerås. With no career stats available for either team and no head-to-head history, this is effectively a coin flip based on available data.LEO's roster shows three players with recorded stats: Kronkzz leads with a 1.11 rating and an impressive 81.57 ADR and 77.4% KAST — the highest KAST figure in this match. didde6 contributes at 0.98 rating, and DeeP at 0.94. However, two LEO players (Milo3k and FRONTEZZZ) have no recorded stats, suggesting they are newer or less experienced. Prestige Academy has no roster data available in the system, making any player-level comparison impossible.The betting market shows 1.00/1.00 odds — no market pricing available — confirming the extreme uncertainty. Given LEO's slight roster data advantage (at least three players with measurable stats vs. zero for Prestige Academy), we give LEO a marginal edge. However, this prediction carries very low confidence and should be treated as a near-coin-flip. Limited data available for both teams.

Predicted: LEO 52% conf.
AI RUNNING 8 Jul 2026
Keyd
vs
MIBR.A

Keyd vs MIBR.A — Prediction & Match Analysis

Keyd take on MIBR Academy in the Thunderpick World Championship 2026 South American Series #2 Group B. Keyd arrive with a 6W-4L record in their last 10 (60% win rate), edging MIBR Academy's 5W-5L (50%). More importantly, Keyd's individual player stats are significantly stronger: their top five players average around 1.09 rating, led by lash (1.11 rating, 72.68 ADR), naitte (1.10 rating, 79.04 ADR), and ckzao (1.09 rating, 76.74 ADR). MIBR Academy's best player Jerr1 sits at just 1.03 rating, with the rest of the squad below 1.00 — a clear statistical disadvantage.Head-to-head history slightly favors MIBR Academy at 2-1, but the most recent data shows Keyd beating Isurus 2-1 (May 22) and METANOIA WOLVES 2-0 (May 22), while MIBR Academy beat Isurus twice 2-0 in late June. Keyd's recent wins include a 2-1 over Game Hunters (July 6) and 2-0 over Yawara Esports (June 26). MIBR Academy's form is mixed — they lost to ex-Vexa 1-2 (July 4) and RED Canids Academy 1-2 (June 30), showing vulnerability to mid-tier opponents.The odds at 1.33-1.38 for Keyd (implied ~72-75% probability) reflect the market's confidence in Keyd's individual quality. Despite the H2H deficit, Keyd's superior player ratings and better recent form make them the pick. MIBR Academy's career winrate of 48.77% (198W-208L) is higher than Keyd's 40% (86W-129L), suggesting MIBR Academy has more experience — but Keyd's current roster quality appears to outperform their historical record.

Predicted: Keyd 63% conf.

Finished 489

AI FINISHED WRONG 12 Jun 2026
FURIA
vs
MOUZ

Round 2: FURIA vs MOUZ — Prediction & Match Analysis

MOUZ get a clean contrarian-market lean in the IEM Cologne Major 2026 Stage 3 R2 Bo3 against FURIA. The structural case rests on H2H and form: MOUZ 5-3 head-to-head, MOUZ 7W-3L recent form vs FURIA 4W-6L. Career rates are essentially tied (FURIA 59.06% on 574, MOUZ 58.37% on 747). Market pricing has FURIA at 1.56 / MOUZ 2.27 — the books reading it against the data.The FURIA case is the market readBooks are pricing FURIA as the structural favourite despite the H2H and form deficit — usually a signal the market sees something in current shape the public data hasn't fully captured. Brazilian rosters have historically been undervalued at Cologne Majors when the home-crowd narrative is absent, and FURIA's structural identity carries genuine Bo3 closeout potential.Why 65H2H plus form plus Aleksib-style 'individuals bailing us out' from xertioN's recent form all stack on MOUZ. The 65 confidence reflects backing the data stack while honestly weighting the market disagreement — Bo3 Major variance against an in-form Brazilian roster is real.

Wrong: MOUZ 65% conf.
AI FINISHED CORRECT 9 Jun 2026
Abyssal
vs
RSTR

Winners match: Abyssal vs RSTR — Prediction & Match Analysis

Rooster get a clean stacked lean in the Dfrag Open Series #5 Bo3 against Abyssal. Every metric except recent form (which is tied) aligns on Rooster: 60.7% career rate on 374 matches vs Abyssal's 44.44% on 18, a 2-1 head-to-head record, and a Thunderpick line of 1.62 / 2.16.The Abyssal case is recent formAbyssal come in at 7W-3L — matching Rooster's recent form line exactly. That's the only metric they win. The career sample (18 matches) is too small to draw any structural signal from, and the 1-2 H2H means Rooster have historically had the matchup measured.Why 73Career rate, sample depth, head-to-head, and market consensus all stack on Rooster. The 73 confidence reflects the data stack while honestly weighting Abyssal's tied recent form — Bo3 variance against a hot opponent is always real, even when the structural metrics are this one-sided.

Correct: Rooster 73% conf.
AI FINISHED CORRECT 9 Jun 2026
MGLBROS
vs
MandL

Elimination match: MGLBROS vs MandL — Prediction & Match Analysis

MARKandLARRY get a low-confidence market-side lean in the Dfrag Open Series #5 Bo3 against MGLBROS. Both sides operate well below the public-betting threshold: MGLBROS 0W-3L recent form vs MARKandLARRY's 2W-6L, essentially zero career data on either side, and a near-even Thunderpick line of 1.81 / 1.90.The MGLBROS caseMGLBROS bring no career history visible (0-2 over their last visible series) and a 0W-3L recent form line. The case for backing them rests entirely on the near-even market price — if Thunderpick reads the matchup as essentially coin-flip, MGLBROS's underdog price (1.81) actually offers value.Why 56This is essentially a coin flip with the slight market lean as the only tiebreaker. Both rosters are below the data threshold where any prediction carries real confidence. Backing the form-edge side at 56 reflects the honest near-coin-flip nature of the matchup.

Correct: MARKandLARRY 56% conf.
AI FINISHED WRONG 9 Jun 2026
Xept
vs
NAVI.J

Lower bracket round 1 match 1: Xept vs NAVI.J — Prediction & Match Analysis

NAVI Junior get a clean structurally-stacked lean in the United21 Season 50 Bo3 against xept. Every visible metric aligns the same way: 56.81% career rate on 521 matches vs xept's zero visible career sample, 5W-5L recent form vs xept's 2W-3L (small sample), and a Thunderpick line of 1.25 / 3.50 implying roughly 80% true win probability.The xept casexept come in as an unknown roster with no visible career sample and a 2W-3L form line over just 5 visible matches. There's effectively no scouting baseline, no head-to-head, and no historical pattern to ground any upset case. The Thunderpick price (3.50) is the only concrete signal — and the book is pricing the matchup decisively in NAVI Junior's favour.Why 73Career depth, sample size, recent form, and market consensus all stack on NAVI Junior. The 73 confidence reflects the data stack while honestly weighting the unknown-opponent variance — books occasionally over-rate established sides against new projects that have private practice data the public side can't see.

Wrong: NAVI Junior 73% conf.
AI FINISHED WRONG 9 Jun 2026
INF
vs
ex-MANA

Lower bracket round 1 match 2: INF vs ex-MANA — Prediction & Match Analysis

INFURITY Gaming get a clear sample-depth lean in the United21 Season 50 Bo3 against ex-MANA eSports. The structural case is the data asymmetry: INFURITY 50% career rate on 88 matches vs ex-MANA's zero visible career sample, plus 6W-4L recent form vs ex-MANA's 0W-1L (single visible match).The ex-MANA caseex-MANA enter as essentially an unknown roster — one visible match (a loss) and no career history. The case for backing them rests entirely on the standard unknown-roster-might-be-better-than-public-data scenario. No book line is published, which removes the market tiebreaker entirely — both sides operate at the threshold of public-data visibility.Why 68Career sample depth, recent form, and the absence of any positive ex-MANA signal all stack on INFURITY. The 68 confidence reflects the structural lean while honestly weighting the unknown-opponent variance and the absence of market consensus to confirm the read.

Wrong: INFURITY Gaming 68% conf.
AI FINISHED WRONG 9 Jun 2026
BCA
vs
AM

Round 4: BCA vs AM — Prediction & Match Analysis

AM Gaming get a clean stacked lean in the NODWIN Clutch Series Season 9 Bo3 against Betclic Apogee. Every visible metric aligns the same way: 53.92% career rate vs Betclic Apogee's 51.22%, 5W-5L recent form vs Betclic Apogee's 3W-7L, a 2-1 head-to-head record, and a Thunderpick line of 1.65 / 2.10.The Betclic Apogee caseBetclic Apogee bring the deeper career sample (205 vs 102) and a marginally similar career rate. The 3W-7L recent form is the killer though — seven losses in the last ten matches is the kind of cold patch that rarely flips inside a single Bo3 against an opponent with H2H advantage and market consensus on their side.Why 70Career rate, recent form, head-to-head, and market all align on AM Gaming. The 70 confidence reflects the clean data stack while honestly weighting Betclic Apogee's career sample depth — Bo3 variance against a 205-match opponent is genuinely real.

Wrong: AM Gaming 70% conf.
AI CANCELED 9 Jun 2026
INOX
vs
BBP

Round 1: INOX vs BBP — Prediction & Match Analysis

INOX Division get a clean stacked lean in the CCT Europe Series 4 Bo3 against Bebop. Every visible metric aligns on the same side: 7W-3L recent form vs Bebop's 5W-5L, a 1-0 head-to-head record, and a Thunderpick line of 1.30 / 3.16 implying roughly 77% true win probability for INOX.The Bebop case is career sampleBebop bring 69 career matches at 52.17% — the only visible structural baseline in the matchup, since INOX carry no public career sample. That's a real signal given how thin the data layer is. The 5W-5L form is respectable in isolation, and the underdog price offers value if scouting visibility is incomplete on either side.Why 70Form gap, head-to-head, and market consensus stack on INOX. The 70 confidence is held below 75 because Bebop's career baseline (69 matches at 52%) is the only concrete signal in the matchup — Bo3 variance against the only side with a visible competitive history is real.

Predicted: INOX Division 70% conf.
AI FINISHED CORRECT 9 Jun 2026
ex-RUBY
vs
RUST

Round 1: ex-RUBY vs RUST — Prediction & Match Analysis

ex-RUBY get a market-aligned career-rate lean in the CCT Europe Series 4 Bo3 against RUSTEC. The structural case rests on the career baseline and book signal: ex-RUBY 61.25% on 80 matches vs RUSTEC's 54% on 200, with Thunderpick pricing ex-RUBY at 1.53 / 2.29 despite RUSTEC's slight form edge.The RUSTEC case is form and sampleRUSTEC bring a 6W-4L recent form line slightly ahead of ex-RUBY's 5W-5L, plus the deeper career sample (200 vs 80). The H2H is split 1-1 — neither side has a clean historical edge. Market consensus and career rate stack on ex-RUBY; form and sample depth pull toward RUSTEC.Why 65Career-rate gap (7 points) plus market consensus outweigh RUSTEC's narrow form edge and sample-depth advantage. The 65 confidence reflects the honest tension — this is exactly the kind of matchup where the book sees something in ex-RUBY's structural shape that the headline numbers don't capture.

Correct: ex-RUBY 65% conf.
AI FINISHED CORRECT 9 Jun 2026
Lavked
vs
MISA

Winners match: Lavked vs MISA — Prediction & Match Analysis

Lavked get a market-aligned career-rate lean in the European Pro League Series 7 Bo3 against Misa Esports. Both sides come in at 7W-3L recent form, which removes the trajectory tiebreaker. The structural differentiator is career rate and market consensus: Lavked 65.38% on 26 matches vs Misa's 54.37% on 103, with Thunderpick pricing Lavked at 1.32 / 3.10.The Misa case is sample depthMisa's 103-match sample is nearly 4x deeper than Lavked's 26. The career rate (54.37%) is less impressive but built across a much longer span. The 7-3 form line matches Lavked exactly — which means Misa enter on equal trajectory but with materially more competitive history to draw on under pressure.Why 65Market consensus plus career rate stack on Lavked, but Misa's sample depth and tied form keep this from being a high-confidence lock. Backing the book read at 65 reflects the structural lean without overextending — small-sample favourites at 1.32 prices are exactly the kind of bet that occasionally produces upset surprises.

Correct: Lavked 65% conf.
AI FINISHED CORRECT 9 Jun 2026
CS
vs
ex-RUBY

Round 4: CS vs ex-RUBY — Prediction & Match Analysis

ex-RUBY get a low-confidence career-rate lean in the NODWIN Clutch Series Season 9 Bo3 against CYBERSHOKE Esports. The market sits essentially even at 1.92 / 1.78, both sides come in at 5W-5L, and the head-to-head is a clean 1-1 split. The only structural differentiator is career rate.The CYBERSHOKE case is sample depthCYBERSHOKE carry 409 career matches at 53.55% (219-190) — a deep visible competitive history with a respectable rate. ex-RUBY hold a marginally higher rate (61.25%) but on a 5x smaller sample (80 matches). The 1-1 H2H removes any historical pattern, and the market split confirms how evenly the books read the matchup.Why 58This is essentially a coin flip between two evenly-matched rosters. ex-RUBY's career-rate edge is the only meaningful differentiator, and that's modest given the sample-size mismatch. Backing the slight-favourite side at 58 reflects the honest near-coin-flip nature of the matchup.

Correct: ex-RUBY 58% conf.
AI FINISHED CORRECT 9 Jun 2026
MANA
vs
OXUJI

Elimination match: MANA vs OXUJI — Prediction & Match Analysis

Oxuji Esports get a low-confidence form-side lean in the European Pro League Series 7 Bo3 against MANA eSports. The structural case rests on the recent trajectory: Oxuji 7W-3L vs MANA's 5W-5L, a 20-point form-winrate edge. Career rates are essentially tied — MANA 53.06% on 147 matches, Oxuji 50.65% on 77 — and no book line is published.The MANA case is sample depthMANA carry the deeper career sample (147 vs 77) at a marginally higher rate. That's a meaningful structural edge in Bo3 closeout scenarios — but a 20-point recent-form gap is the kind of momentum signal that usually matters more than career baseline in Tier 2/3 Bo3s. No head-to-head data exists to ground a historical pattern.Why 60Career baseline and recent form pull in opposite directions with no market consensus to break the tie. Backing the form-momentum side at minimum confidence reflects the honest tension — Bo3 variance against a deeper-sample opponent is real.

Correct: Oxuji Esports 60% conf.
AI FINISHED CORRECT 8 Jun 2026
Leo
vs
HS

Leo vs HS — Prediction & Match Analysis

Leo Team and HyperSpirit meet for the first time in recorded head-to-head history in this CCT Europe Closed Qualifier Play-In Bo3. Both teams are in the lower tier of European CS2, making this a difficult match to predict with high confidence. Leo Team enter with a 4W-6L record in their last 10 matches, while HyperSpirit show a slightly better 5W-5L. However, Leo Team's two most recent results — 2-0 wins over NEW VISION and Lilmix — suggest they are finding form at the right time.Leo Team hold a statistical edge in average roster rating (1.02 vs HyperSpirit's 1.00), led by OneUn1que (1.15 rating, 80.78 ADR) as their standout performer. HyperSpirit's roster is more evenly distributed, with BRK (1.05), ragga (1.04), Ciocardau (1.04), d1maje (1.04), and e1543 (1.04) all clustered tightly — no clear star but also no obvious weak link. Leo Team's career winrate of 53.46% edges HyperSpirit's 48.56%, suggesting Leo Team has historically been the stronger team.The market prices Leo Team at 1.50 vs HyperSpirit's 2.40, reflecting Leo Team's career record advantage and their recent back-to-back wins. With no H2H data to reference, we lean Leo Team on the strength of their career winrate, individual rating edge, and market consensus. This is a low-confidence call — HyperSpirit's balanced roster and 5W-5L form make them a credible upset threat.

Correct: Leo Team 56% conf.

How Our CS2 AI Predictions Work

Our CS2 AI prediction engine uses machine learning to analyze every upcoming professional Counter-Strike 2 match. The AI model processes 8+ statistical dimensions simultaneously: team form over the last 90 days, map-specific win rates, head-to-head history between the two rosters, individual player performance metrics (HLTV 2.0 rating, ADR, KAST%, opening duel win rates), roster stability, tournament seeding context, schedule fatigue and real-time betting odds from multiple bookmakers.

Unlike manual predictions that rely on human intuition and can be influenced by bias, our AI predictions are purely data-driven. The model weighs each factor according to its predictive power, with recent performance carrying the highest weight. Every 6-12 hours, the AI scans for upcoming matches without predictions and generates a complete analysis including a recommended pick, confidence rating, pros/cons for each team and a written analytical summary.

CS2 AI Predictions vs Traditional Predictions

Traditional CS2 predictions rely on human analysts who may be influenced by narrative bias, recency bias or emotional attachment to specific teams. AI predictions eliminate these biases by processing raw statistical data objectively. The AI model evaluates every match using the same rigorous methodology, whether it's a tier-1 grand final or a tier-2 qualifier match. This consistency produces more reliable results over large sample sizes.

Our AI prediction accuracy is tracked transparently at the top of this page. Every prediction is logged with its outcome, allowing you to verify the model's reliability across different tournament tiers, match formats and confidence ranges. The model continuously improves as more data accumulates, refining its understanding of which statistical signals are most predictive of match outcomes.

Using AI Predictions for CS2 Betting

AI-generated CS2 predictions are particularly valuable for identifying value bets. When the AI assigns a confidence rating that implies a higher win probability than what bookmaker odds suggest, that represents a statistical edge. For example, if the AI predicts Team A at 68% confidence but the bookmaker odds imply only a 55% probability, the discrepancy suggests potential value on Team A.

Each AI prediction includes a detailed analytical summary explaining the reasoning behind the pick, plus individual pros and cons for both teams. This transparency allows you to understand the AI's logic and make informed decisions. Combine AI predictions with your own knowledge of the CS2 scene for the most effective betting strategy.

CS2 AI Predictions FAQ

How does CS2 AI prediction work?

Our CS2 AI prediction system uses machine learning to analyze match data. For each upcoming match, the AI processes team form (last 90 days), map pool win rates, head-to-head records, individual player statistics (rating, ADR, KAST%, HS%), roster stability, tournament context and real-time betting odds. The model weighs these factors and outputs a predicted winner with a confidence percentage. Predictions are generated automatically every 6-12 hours.

How accurate are CS2 AI predictions?

Our AI prediction accuracy is tracked transparently on this page with a full win/loss record. The accuracy varies by match type and tournament tier — the model typically performs best on tier-1 BO3 matches where more historical data is available. Each prediction includes a confidence rating that reflects how strongly the statistical signals align. Higher confidence predictions (70%+) tend to have significantly better accuracy than lower confidence ones.

What is the difference between AI predictions and expert predictions?

AI predictions are generated entirely by machine learning models using statistical data, eliminating human bias. Expert predictions combine data analysis with qualitative insights like player motivation, team dynamics and map meta shifts. Both approaches have strengths — AI excels at processing large datasets consistently, while human experts can factor in intangible elements. On CS2Bet, all predictions are generated by our AI model for maximum objectivity and consistency.

How often are CS2 AI predictions updated?

The AI prediction engine runs every 6-12 hours, scanning for upcoming matches without predictions and generating new analyses. Predictions are typically published 12-48 hours before match start time, giving you ample time to review the analysis and compare against bookmaker odds. Once published, predictions are not revised — the original pick and confidence rating stand as a permanent record.

Can I use CS2 AI predictions for PrizePicks and player props?

AI match predictions focus on match winners and series outcomes. For player-specific projections like PrizePicks and player props, visit our dedicated CS2 PrizePicks and Player Props pages which provide individual player statistical projections. However, AI match predictions can inform player prop decisions — if the AI predicts a team to win convincingly, star players on that team may be more likely to exceed their projected stats.

What data sources does the CS2 AI prediction model use?

The AI model uses professional CS2 match data covering all major tournaments, leagues and qualifiers. Data includes match results, round-by-round scores, individual player statistics per map, roster composition history, tournament brackets and real-time betting odds from multiple bookmakers. The model only uses verified, structured data — it does not scrape social media or use unverified sources.

Inside the CS2 AI Prediction Model

Our AI prediction engine is built on a machine learning pipeline trained on thousands of professional Counter-Strike 2 match results. The model learns which statistical patterns most reliably predict match outcomes, then applies those learned relationships to every upcoming match in real time.

Data Inputs and Feature Engineering

The AI ingests structured data across eight dimensions for every match: team form over the last 90 days weighted by recency, map-specific win rates for each team across the active map pool, head-to-head records between the two rosters, individual player statistics including HLTV 2.0 rating, ADR and KAST percentage, roster stability scores reflecting recent lineup changes, tournament context such as group stage versus playoffs, schedule density measuring potential fatigue, and real-time bookmaker odds from multiple sportsbooks. Each data point is normalized and fed into the model as a numerical feature.

Confidence Ratings and Transparency

Every AI prediction includes a confidence percentage that reflects how strongly the statistical signals align. A 75% confidence rating means the model's internal probability estimate heavily favors one side across most input dimensions. A 55% rating indicates a closely contested matchup where signals are mixed. We publish these ratings transparently so you can calibrate your trust in each prediction. High-confidence picks above 70% historically outperform lower-confidence outputs, but lower-confidence predictions often correspond to matches where bookmaker odds offer the most value.

Track Record and Continuous Improvement

The AI model's full win/loss record is displayed at the top of this page with no selective filtering. Every prediction is logged permanently with its outcome, allowing you to evaluate accuracy across tournament tiers, match formats and confidence ranges. The model retrains periodically on new match data, incorporating the latest results to refine its understanding of which features carry the most predictive power. This continuous learning loop means the AI adapts to meta shifts, roster changes and evolving competitive dynamics without manual intervention.

Combining AI Predictions with Betting Strategy

AI predictions are most valuable when compared against bookmaker odds to identify statistical edges. When the AI's confidence rating implies a higher win probability than the odds suggest, that discrepancy may represent a value betting opportunity. Use the AI's analytical summary and team-level pros and cons to understand the reasoning, then apply disciplined bankroll management to size your wagers appropriately.