AI MODEL READ

PRE-LINEUP

HOU vs SF

Houston Astros at San Francisco Giants

Tuesday, August 11, 2026

SIMULATION · ONE TRIAL, EVERY MARKET

Watch the model run this game.

One representative trial from the HOU @ SF simulation — real per-AB batter, outcome, and score progression from the spine. Every game-level market updates in lock-step with each play.

HOUSTONHOU
0·0
SAN FRANCISCOSF
TOP 10-11 OUT

FIELD

HOU DUGOUTSF DUGOUT330395330LIVE · BETFLY

PITCH SEQUENCE

League Avg (R) vs HP

CH82.9
SL84.1
CV79.2
CH83.6
SL84.7

OUTCOME DISTRIBUTION

League Avg in this spot

HR
3%
HIT
9%
BB
9%
K
24%
OUT
55%

BATTER PROPS · LEAGUE AVG

HR YES (O0.5)
12%
HITS O0.5
40%
TOTAL BASES O1.5
24%

PITCHER PROPS · HP

KS O5.5
55%

GAME MARKETS · LIVE

updating per event

MONEYLINE

SF to win

41%

TOTAL

Over 8.5

58%

RUN LINE

SF -1.5

45%

TEAM TOTAL SF

Over 4.5

52%

FIRST 5 INN

SF wins F5

51%
LAST PLAYLeague Avg at the plate · pitch 1 of 5

event 1 / 86 · pitching

Every card on the board is a live read. As the game changes, the math changes with it — every prop, every market line, in real time. Cards turn green when they hit, red when they miss.

I · GAME-LEVEL MODEL

Win probability + total.

GAME WINNER

Houston vs San Francisco Winner?

51%

5,000-TRIAL SIMULATION

II · MATCHUP BREAKDOWN

Who has the advantage tonight.

The same numbers our 5,000-trial sim ran on — starter quality, projected strikeouts, and every bat in both lineups — not opinions.

PITCHING EDGEHOU

HOU STARTER

Hunter Brown

AVERAGE
6.1
PROJECTED Ks
101
PITCHING+

GO-TO PITCHES

4-Seam Fastball · 34% · 23% whiffSinker · 29% · 21% whiffCurveball · 20% · 35% whiff

SF STARTER

Carson Whisenhunt

SHAKY
4.1
PROJECTED Ks
89
PITCHING+

GO-TO PITCHES

Changeup · 38% · 44% whiff4-Seam Fastball · 36% · 13% whiffSlider · 23% · 29% whiff

Watch out: 4-Seam Fastball is getting hit hard lately.

Carson Whisenhunt grades poor (Pitching+ 89) vs Hunter Brown grades avg (Pitching+ 101)

III · EVERY MARKET WE RAN

Swipe the whole board.

One card per hitter and pitcher, plus the game markets — the sim's own number on every line it priced, with the reasoning that produced it.

25 simulated lines · raw sim

1 / 4

HOU SF

Game Markets

HOU @ SF · full-game reads

7 MARKETS

Moneyline

HOU to win

59%

1st 5 Innings

SF F5

32%

Game Total

Over 8.5

38%

1st 5 Total

Over 4.5

45%

Run Line

SF -1.5

25%

Team Total

HOU Over 4.5

43%

Team Total

SF Over 4.5

29%

THE READ

HOU projects to outscore SF by 1.03 runs across 5,000 trials.

  • Projected runs: HOU 4.38, SF 3.35
  • Hunter Brown (HOU) vs Carson Whisenhunt (SF)
  • Run on league-average lineups — refreshes when lineups post
HB

Hunter Brown

HOU SP · vs. SF

SP

Strikeouts

5+ Ks

76%

Strikeouts

6+ Ks

59%

Strikeouts

7+ Ks

42%

Strikeouts

8+ Ks

25%

Strikeouts

9+ Ks

13%

Outs Recorded

15+ outs

82%

Outs Recorded

18+ outs

33%

Hits Allowed

5+ hits

40%

Hits Allowed

6+ hits

26%

THE READ

Strikeout-heavy projection — the sim has him at 6.1 Ks, with the ladder still live into the 8+ rung.

  • Sim projects 6.1 strikeouts
  • 76% to reach 5+ against SF
CW

Carson Whisenhunt

SF SP · vs. HOU

SP

Strikeouts

5+ Ks

40%

Strikeouts

6+ Ks

23%

Strikeouts

7+ Ks

11%

Strikeouts

8+ Ks

5%

Strikeouts

9+ Ks

2%

Outs Recorded

15+ outs

24%

Outs Recorded

18+ outs

4%

Hits Allowed

5+ hits

36%

Hits Allowed

6+ hits

24%

THE READ

Middle-of-the-road strikeout projection at 4.1 Ks.

  • Sim projects 4.1 strikeouts
  • 40% to reach 5+ against HOU

BATTER CARDS
UNLOCK WHEN LINEUPS POST

The sim can't run a hitter until it knows he's in the lineup. Clubs post about two hours before first pitch, and every bat gets a card with HR, hits, total bases and RBI.

IV · METHODOLOGY

How this read was built.

  • Simulation. 5,000 Monte Carlo trials of this game using real play-by-play data, confirmed lineups, pitcher quality, bullpen depth, defensive runs saved, catcher framing, umpire K-zones, and per-batter rates regressed with empirical Bayes.
  • What the number means. The share of those 5,000 trials in which the outcome happened — the model's own estimate, not a claim that a sportsbook has mispriced it. We publish it next to the reasoning that produced it and let the settlement record below speak for itself.
  • Settlement. Every read on this page is graded by Kalshi's own settlement market once the game ends. The post-game version of this page shows what was confirmed and what was missed.

DISCLOSURE

BetFly is not a sportsbook, prediction market, or wagering operator. The model reads above are sabermetric simulation output — not advice or a recommendation on whether or how to bet. See our Disclaimer for the full risk disclosure.