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Borussia M.Gladbach v Paderborn — Prediction, Odds & Stats

Saturday 31 October 2026 · GER-Bundesliga · 2627

Bundesliga xG Prediction generated

AI prediction

ai-blend v1.0 daily
Borussia M.Gladbach win
53.0%
Draw
24.0%
Paderborn win
23.0%

Raw model output; no calibration record for this fixture's bands yet.

Top 5 scorelines

  1. 1-1 11.4%
  2. 1-0 11.0%
  3. 2-1 9.7%
  4. 2-0 9.4%
  5. 0-1 6.7%

Goals

Over 2.551.6% Under 2.548.4%
BTTS yes52.8% BTTS no47.2%
Borussia M.Gladbach 1+81.8% Borussia M.Gladbach 2+50.8%
Paderborn 1+64.5% Paderborn 2+27.8%

Expected goals 1.70 – 1.04. Every market above is read off one scoreline distribution.

Footing

AI confidence
89/100
Data quality
80/100
Model agreement
99%
★ Best pick
Nothing on a measured band prices above 1.18 here.
★ Most likely to land
Nothing on a measured band prices above 1.18 here.

Positive factors

  • Borussia M.Gladbach have created 1.65 xG a match over their last five while Paderborn have allowed 1.89.
  • At home Borussia M.Gladbach average 2.05 xG a match.

Risk factors

  • Paderborn have only 7 matches on record.
Why the model thinks this

The price

Borussia M.Gladbach have an estimated 53.0% win probability, against 24.0% for the draw and 23.0% for Paderborn. Expected goals from the ensemble are 1.70 for Borussia M.Gladbach and 1.04 for Paderborn.

Why Borussia M.Gladbach

Borussia M.Gladbach have created 1.65 xG a match over their last five while Paderborn have allowed 1.89. At home Borussia M.Gladbach average 2.05 xG a match.

Why the draw is live

The draw sits at 24.0%. Draws run at 25% in this competition.

Why Paderborn can win

Paderborn carry the stronger rating, 1500 Elo against 1433. Paderborn have created 1.13 xG a match over their last five while Borussia M.Gladbach have allowed 2.31. Away from home Paderborn average 0.79 xG a match. Their last eleven was closer to full strength: Borussia M.Gladbach were missing 1.11 expected goal involvements a match against 0.29.

Key players

Borussia M.Gladbach's leading contributors by expected goal involvements a match: Haris Tabakovic (0.45), Tim Kleindienst (0.38), Franck Honorat (0.26). Paderborn's leading contributors by expected goal involvements a match: Laurin Curda (0.28), Steffen Tigges (0.24), Marvin Pieringer (0.23).

Availability

3 of Borussia M.Gladbach's top three contributors did not start their last match. 1 of Paderborn's top three contributors did not start their last match.

The matchup, as far as the data reaches

Borussia M.Gladbach: 43% possession, 13.4 shots a match, 17.0 faced, 0.27 xG a match from set pieces. Paderborn: 46% possession, 14.6 shots a match, 16.2 faced, 0.24 xG a match from set pieces.

Inputs last refreshed: matches 2026-10-26 10:06 · team_stats 2026-10-26 06:08 · availability 2026-10-26 14:59 · prediction 2026-09-18 10:37 ·

Borussia M.Gladbach are the model's most likely outcome at 53.0%. The likeliest scoreline is 1-1 at 11.4%. Confidence 89/100, data quality 80/100. These are probabilities, not certainties: the less likely outcome happens as often as its number says.

Written from the numbers the model saw, not by a language model; nothing here is a statistic the snapshot does not hold. How predictions work.

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Was this pick made in advance?
A model whose name ends -oos is out of sample: it was fitted only on matches played before this one, so its pick is a genuine forecast rather than hindsight. Anything without that suffix was fitted on all available data.

What the chances say

Borussia M.Gladbach have scored 17 from 16.5 expected and conceded 25 from 23.1 — both ends in line with the chances, so the recent record is a fair reflection.

WLWLLLLLLW last 10 scored 17 from 16.5 xG conceded 25 from 23.1 xG

Paderborn are conceding sharply fewer than expected — 4.2 goals saved beyond what the chances suggest.

DLLWLDW last 7 scored 6 from 7.9 xG conceded 9 from 13.2 xG

Finishing swings far more than chance creation, so a gap this size usually narrows. Over ten matches it is suggestive, not settled — a genuinely elite finisher beats expected goals for years.

What the model said

ModelHome / Draw / Away Expected goalsLikeliest score O2.5BTTS
ai-blend 1.70–1.04 0% 0% 0%
dc-xg 1.81–1.12 1-1 11% 56% 56%

A model whose name ends -oos was produced by the walk-forward backtest: it was fitted only on matches played before this one, so the pick is genuinely out of sample.

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On this page

Match

What this page is for

One fixture in full. The model's probability for every market it prices, the prices stored against them, the teams expected to feature, and for a match already played, the shot map and the xG timeline.

How to read the shot map

Every shot is placed where it was taken and sized by its chance of being scored. A cluster of small marks from distance and a clean sheet is a side that was busy without ever threatening; two big marks and a defeat is a side that had the better of it and lost anyway. Both happen constantly, and both are invisible in the score.

How to read the xG timeline

The steps are chances as they arrived, so the shape shows who was on top and when. A flat line that jumps once near the end is a smash and grab.

Things to watch

The stored prediction is the one made before the match, kept deliberately so it can be judged afterwards. It is not re-fitted with hindsight.

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