FCC 1-2 PHI · 50% COL 2-1 DCU · 54% NEW 1-0 CFM · 47% AL- 3-0 AL- · 65% COR 1-1 VIT · 42% SPO 1-2 FCD · 60% ST. 2-1 SAN · 49% ACM 1-1 INT · 42% EST 0-1 LEM · 44% AND 1-2 KVC · 43% SKB 0-2 UNI · 62% BAR 3-0 ALA · 64% AST 1-0 FUL · 46% DEP 0-0 TAL · 37% FCC 1-2 PHI · 50% COL 2-1 DCU · 54% NEW 1-0 CFM · 47% AL- 3-0 AL- · 65% COR 1-1 VIT · 42% SPO 1-2 FCD · 60% ST. 2-1 SAN · 49% ACM 1-1 INT · 42% EST 0-1 LEM · 44% AND 1-2 KVC · 43% SKB 0-2 UNI · 62% BAR 3-0 ALA · 64% AST 1-0 FUL · 46% DEP 0-0 TAL · 37%
TuringStats
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Major League Soccer · Regular Season - 33 Q2 Stadium, Austin Not Started

Austin
vs
Portland Timbers.

Quick answer

Who will win Austin vs Portland Timbers?

3 of 10 AI models pick Austin to win (30%). A draw is in play: 6 of 10 models picked it. The mean predicted score is 1–1 at 44% average confidence (low).

Consensus of independent AI models on TuringStats, updated before kickoff. Not betting advice.

Head-to-head history → Austin form Portland Timbers form

10 AI models read this match. The plurality on 1X2 leans toward the draw (6 of 10 models). The mean predicted score (rounded from all models) is 1–1 at 44% mean confidence (Low band) — see the strip and table below.

Who do you think will win?

Vote before kick-off and compare with AI

Major League Soccer table Where Austin and Portland Timbers stand right now
— Consensus

Where the panel lands.

Vote share across models. Read this strip first, then the line-by-line table.

Austin win 30%

3 / 10 models

Draw 60%

6 / 10 models

Portland Timbers win 10%

1 / 10 models

— Model breakdown

10 picks. Receipts attached.

Line-by-line comparison of each system’s call.

#
Model
Pick
Score
Conf.
Reasoning
01
GPT-6 Luna
Draw
1–1
31%
Austin have home advantage and recently beat Portland, but both teams have losing records and leaky defenses. Portland’s stronger scoring record balances Austin’s venue edge, making a narrow, moderate-scoring draw the likeliest exact outcome.
02
Claude Sonnet 5.5
Austin win
2–1
45%
Both teams struggling defensively and mid-table with poor recent form; Austin's home venue and recent H2H win give slight edge in a likely open contest.
03
Gemini 3.8 Flash
Draw
1–1
50%
Both sides struggle with defensive consistency and sit closely matched in form. Portland score reliably but rarely keep clean sheets, pointing toward a balanced 1-1 stalemate at Q2 Stadium.
04
Grok 4.7
Draw
1–1
38%
Both sides have mixed form, leaky defenses, and frequent blanks. Austin’s home edge is offset by poor season record; H2H includes a 0-0 here, so a low 1-1 fits.
05
DeepSeek V4 Pro
Draw
1–1
48%
Both teams are defensively vulnerable and inconsistent, with Austin's home edge offset by Portland's stronger attack and recent H2H balance.
06
Qwen 3.8 Max
Draw
1–1
38%
Both teams in poor form with leaky defenses but inconsistent attacks; H2H at Q2 Stadium previously ended 0-0, suggesting a tight low-scoring draw.
07
Meta Muse Spark 1.3
Portland Timbers win
1–2
52%
Portland arrive DLDWW with stronger attack 57 goals vs Austin LLLWL; Portland rarely keep clean sheets so 1-2 fits H2H low-scoring trend.
08
Kimi K3
Austin win
2–1
48%
Austin won 2-1 at Portland in August and Portland concedes freely (58 against, 2 clean sheets); Austin's poor form but home edge and late-game scoring tilt a narrow home win.
09
GLM 5.3
Austin win
2–1
50%
Two struggling sides with leaky defenses; Austin won recent H2H at Portland and Q2 Stadium edge offsets poor form. Both teams score, Austin's late-goal tendency suggests a 2-1 finish.
10
MiMo V2.6 Pro
Draw
1–1
42%
Both sides are mid-table and inconsistent, Austin winless in four before last win, Portland drawing often; H2H shows tight, low-scoring meetings at Q2, and neither attack is in strong form.
— Scoreline frequency

How often each scoreline showed up.

6 of 10 models settled on 1–1. That convergence is a strong scoreline signal—many fixtures fan out wider across the panel.

  • 1–1
    6 models
  • 2–1
    3 models
  • 1–2
    1 model
Team news

Predicted lineups: Austin vs Portland Timbers

Each side's last starting XI, with players ruled out of this match marked. The confirmed lineups replace this about an hour before kickoff.

Austin

3-4-3 · XI v Real Salt Lake, 29 Oct
D. Arnaud
11 F. Torres
11 Torres
9 B. Vázquez
9 Vázquez
10 M. Uzuni
10 Uzuni
17 J. Gallagher
17 Gallagher
24 Jorge Alastuey
24 Alastuey
14 B. Šabović
14 Šabović
30 J. Rosales
30 Rosales
29 Guilherme Biro
29 Biro
6 Ilie Sánchez
6 Sánchez
3 M. Desler
3 Desler
12 D. Las
12 Las

Portland Timbers

4-3-3 · XI v St. Louis City, 29 Oct
Martí Cifuentes
99 K. Velde
99 Velde
10 David Pereira da Costa
10 Costa
7 A. Lassiter
7 Lassiter
17 C. Bassett
17 Bassett
21 D. Chará
21 Chará
80 J. Ortiz
80 Ortiz
27 J. Fory
27 Fory
4 K. Miller
4 Miller
2 J. Waterman
2 Waterman
12 R. Hernández
12 Hernández
41 J. Pantemis
41 Pantemis

Season data

Major League Soccer numbers for both sides, when they score and the players who carry them.

Austin

4-4-2
W-D-L
8-10-14
Goals
41-59
Clean sheets
5
Failed to score
6
Best win run
2
Penalties
1/1
When they score
15'30'45'60'75'90'
When they concede
15'30'45'60'75'90'

Portland Timbers

4-2-3-1
W-D-L
11-7-14
Goals
57-60
Clean sheets
2
Failed to score
7
Best win run
2
Penalties
3/4
When they score
15'30'45'60'75'90'
When they concede
15'30'45'60'75'90'

Key players · Austin

  • No player in the competition's top scorers or assisters.

Key players · Portland Timbers

  • David Pereira da Costa 6 G · 8 A · 28 apps

Top scorers · Major League Soccer

  1. 1 L. Messi Inter Miami 25
  2. 2 P. Musa FC Dallas 22
  3. 3 Rafael Navarro St. Louis City 19
  4. 4 M. Iloski Philadelphia Union 19
  5. 5 D. Bouanga Los Angeles FC 18
Venue Q2 Stadium, Austin
New at Austin Chris Applewhite (Nashville SC), C. Farrar (Austin), P. Płacheta (Oxford United)
New at Portland Timbers R. Hernández (Atlanta United FC), J. Waterman (Chicago Fire), V. Janssen (Antwerp)
— Aggregated insights

What’s moving the panel.

01
Models lean the draw

60% of models take a stalemate — cross-check score frequency and 1X2 strip before sizing.

02
Low confidence

Mean 44% across the panel with real dispersion — compare unanimous calls vs split tickets in the model table.

03
xG tilt 1.30 vs 1.10

Derived from predicted scorelines (model means), not live match data — useful for pace vs vote-share sanity checks.

04
Match context

Expected-goals tilt and home-field rhythm (see xG on this page) usually explain whether the game stays open or compresses late.

Ask the Council about this match

Pro

10 AI models vote yes or no with this match's last-5 form, head-to-head, live status and the model picks above attached — not from memory. Then keep asking the same council follow-ups.

Ask with match data Ask without data (free)

Match stats forecast

Corners, cards and shots from each side's last 10 matches at this venue, blended with the league average. Pure statistics, not an AI vote.

No AI
Metric Austin Portland Timbers Expected total Lean
Corners 4.6 5.0 9.6 Under 9.5 51% Ask AI
Yellow cards 1.2 1.7 2.9 Over 2.5 56% Ask AI
Shots 12.6 13.4 26.0 Under 26.5 55% Ask AI
Shots on target 5.2 4.9 10.1 Under 10.5 58% Ask AI

Sample: 3 matches per side. Over the last 90 days the corners lean hit 55% of 285 graded matches, cards 59% of 286. Probabilities are Poisson estimates for information only.

— Match context

Form, history, team news.

Austin
#14 · 34 PTS · GD -18
Last 5
L W L L L
6 GF · 12 GA
Recent fixtures
  • Real Salt Lake 1-2 L
  • Sporting Kansas City 1-2 W
  • Vancouver Whitecaps 1-2 L
  • Los Angeles FC 3-1 L
  • Nashville SC 1-4 L
Team news
M. Desler — Groin Injury B. Vazquez — Knee Injury O. Wolff — Groin Injury R. Taylor — Knee Injury Guilherme Biro — Red Card D. Pereira — Hamstring Injury J. Nelson — Leg Injury B. Hines-Ike — Injury M. Uzuni — Lower-Body Injury J. Bell — Pelvis Injury P. Placheta — Lower-Body Injury J. Rosales — Yellow Cards
Portland Timbers
#11 · 40 PTS · GD -3
Last 5
W W D L D
9 GF · 9 GA
Recent fixtures
  • St. Louis City 2-3 W
  • Charlotte 3-2 W
  • Colorado Rapids 0-0 D
  • Los Angeles Galaxy 2-0 L
  • Sporting Kansas City 3-3 D
Team news
D. Da Costa — Shoulder Injury O. Fernandez — Foot Injury Z. McGraw — Back Injury J. Mosquera — Red Card J. Fory — Red Card A. Bonetig — Lower-Body Injury D. Chara — Lower-Body Injury J. Caicedo — Inactive C. Bassett — Injury K. Miller — Red Card G. Guerra — Abdominal strain K. Velde — Personal Reasons

Confidence trend

Cumulative average confidence in table order.

First model Last model

Betting tips (AI-signal view)

Educational only — not financial advice. We summarize how the AI picks cluster so you can cross-check with your own staking plan.

  • Lean with the plurality: when 30% of models side with Austin, treat that as the default script unless late team news breaks the assumptions.
  • Watch the draw lane at 60% — tight Major League Soccer games often compress toward stalemates when both midfields win the second-ball.
  • If you chase “best bets today” narratives, require alignment between the headline pick and the score-frequency table; conflicting signals usually mean thinner edge.

Odds & analysis (implied probabilities)

Implied fair percentages from the model vote share (normalized to 100%) approximate how a balanced market might price the 1X2 if it mirrored this panel — useful for odds analysis homework even though we do not quote sportsbook ticks here.

Austin
~30%
implied lean
Draw
~60%
implied lean
Portland Timbers
~10%
implied lean

Over / under prediction (totals)

Model-derived xG sums to 2.40 goals in expectation. A notional totals line near 2.7 is consistent with that pace (rounded for readability). If your sportsbook posts a similar number, compare juice and live team news before deciding either side of the total.

Handicap prediction (spread-style read)

When Austin is priced as the stronger side in the model vote, a −1 handicap narrative only clears if the most common scorelines include multi-goal wins. Cross-check the score-frequency list: if tight one-goal wins dominate, Asian handicaps near pick’em or −0.5 / −0.75 splits often fit the story better than a full −1.5 sell.

BTTS prediction (both teams to score)

With combined offensive weight near 2.40 xG, a heuristic “both teams score” prior lands around 55% yes before defensive adjustments. If several top models forecast clean-sheet pathways, downgrade BTTS enthusiasm even when the raw xG sum looks juicy.

Best bet framing (consensus-led)

Our headline best bet label follows the consensus recommendation: Austin win. Pair that with the confidence band (Low) — high dispersion across models usually argues for smaller stake or pass, even when the headline pick looks tempting for a today prediction card on social.

Match overview

Looking for a today prediction on Austin vs Portland Timbers in Major League Soccer? TuringStats aggregates multiple AI scorelines into one readable page so you can see who the models favor, the mean predicted score shown in the hero (1 - 1; the frequency chart below lists the most common exact scorelines), and implied splits before kickoff.

This prediction hub is written for readers comparing betting tips-style language with transparent model votes — not a single black-box call. The headline read is Austin win, with vote shares roughly 30% / 60% / 10% home, draw, and away (rounded).

If you are asking who will win Austin vs Portland Timbers, start with the consensus strip and model table, then cross-check form and injuries in Match context further down — that order keeps the strongest signals first.

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