Finished Match Overview METANOIA Wolves vs MIBR fe in CS 2

CS2

CCT SA 2026 Series #6

METANOIA Wolves

2:009/27

MIBR fe

13Map 111

13Map 210

Winio Prediction

Before draft

18%

Prediction: MIBR fe

82%

Match breakdown

1 of 2 correct

Our predictions vs actual result

Match winnerwrong
Total mapscorrect

Prediction factors

49 factors analysed · key ones shown

Winio prediction

MIBR fe to win

82%18%

Average roster strength

1325

1528

Form over 10 matches

50%

40%

Time with current roster

1 day

409 days

Strongest player

1394

1566

Model accuracy

Full archive

Form & Head-to-Head

Last five matches and head-to-head over a year.

Rosters & Form

Our rating for every player, powered by the Winio algorithm

player form over the last 10 maps, regardless of team

Additional predictions

Total maps

68.5%

Prediction: 2 maps

31.5%

2 maps3 maps

Pistol rounds

Round 1 (1st half)

46.5%

Prediction: MIBR fe

53.5%

METANOIA WolvesMIBR fe

Round 13 (2nd half)

45.5%

Prediction: MIBR fe

54.5%

METANOIA WolvesMIBR fe

METANOIA Wolves vs MIBR fe — CS2 Match Analysis, September 27 2026

Explore a detailed breakdown of the METANOIA Wolves vs MIBR fe match at CCT SA 2026 Series #6. Winio's analytical model processed every phase of the game, identified the decisive factors, and measured how closely the pre-match prediction matched the actual result.

CS2 Post-match Analysis: What's Inside

Final result and prediction accuracy. Compare the pre-match win probability with the actual outcome and see which factors proved decisive.
Key moments that changed the game. A breakdown of the critical events that shaped the result: turning points, map control shifts, and individual performances.
Full match statistics. Detailed metrics for both teams and every player: rating, ADR, KAST, map efficiency, and other indicators that explain the final score.
Comparison with previous meetings. See how this match fits into the teams' head-to-head history and which patterns repeated.

Use finished match data to understand how Winio's model performs over time. Each completed match adds to the prediction history available at the Ended Matches section.