Projections

Daily simulation center

A forecast is a range of game stories, not one final score

The simulator turns current game inputs into transparent win probabilities, score ranges, matchup drivers, bullpen effects, and player opportunities, with uncertainty visible everywhere.

Daily forecast board Today’s slate, ordered by first pitchProbable starters, posted orders, active rosters, park, first-pitch weather, recent workload, and bullpen availability

Live input assembly · September 22, 2026

Today’s projection inputs

BaseballR supplies the schedule, probable starters, posted orders, and active rosters. Park coordinates route each game to Open-Meteo: the displayed temperature, wind, rain chance, and conditions come from the forecast hour nearest first pitch, while a separate five-hour game window tracks changing rain and gust risk.

Schedule

MLB games

16

Game IDs, teams, first pitch, venue, and status.

Posted orders

Complete games

15/16

270 confirmed batting-order rows.

Active roster gate

Verified players

840

268 workload-qualified bullpen rows remain after the roster join.

Park weather

Resolved games

16/16

16 of 16 park environments resolved

Away	Home	Away starter	Home starter	Away order	Home order	Park weather	Temp	Wind	Rain	Input state
Tampa Bay Rays	New York Yankees	Nick Martinez	Carlos Rodón	confirmed	confirmed	Bronx, New York	62 F	2.9 mph	3%	ready
Toronto Blue Jays	Baltimore Orioles	Max Scherzer		missing	missing	Baltimore, Maryland	64 F	7.7 mph	25%	conditional
Washington Nationals	Detroit Tigers	Riley Cornelio	Drew Anderson	confirmed	confirmed	Detroit, Michigan	52 F	4.5 mph	0%	ready
St. Louis Cardinals	Pittsburgh Pirates	Andre Pallante	Jared Jones	confirmed	confirmed	Pittsburgh, Pennsylvania	58 F	9.8 mph	48%	ready
Milwaukee Brewers	Philadelphia Phillies	Dustin May	Zack Wheeler	confirmed	confirmed	Philadelphia, Pennsylvania	65 F	8.4 mph	9%	ready
Cleveland Guardians	Boston Red Sox	Parker Messick	Payton Tolle	confirmed	confirmed	Boston, Massachusetts	56 F	2.6 mph	0%	ready
Tampa Bay Rays	New York Yankees	Drew Rasmussen	Max Fried	confirmed	confirmed	Bronx, New York	62 F	2.9 mph	3%	ready
Cincinnati Reds	Atlanta Braves	Brandon Williamson	JR Ritchie	confirmed	confirmed	Atlanta, Georgia	74 F	1.4 mph	10%	ready
Chicago White Sox	Kansas City Royals	Anthony Kay	Daniel Lynch IV	confirmed	confirmed	Kansas City, Missouri	64 F	4.3 mph	2%	ready
Miami Marlins	Chicago Cubs	Janson Junk	Shota Imanaga	confirmed	confirmed	Chicago, Illinois	59 F	13.7 mph	0%	ready
New York Mets	Texas Rangers	Sean Manaea	MacKenzie Gore	confirmed	confirmed	Arlington, Texas	80 F	3.9 mph	6%	ready
Arizona Diamondbacks	Colorado Rockies	Michael Soroka	Kyle Freeland	confirmed	confirmed	Denver, Colorado	61 F	4.0 mph	1%	ready
Los Angeles Angels	Athletics	Yusei Kikuchi	Brady Basso	confirmed	confirmed	West Sacramento, California	58 F	5.3 mph	0%	ready
Houston Astros	Seattle Mariners	Cristian Javier	Logan Gilbert	confirmed	confirmed	Seattle, Washington	60 F	4.3 mph	0%	ready
Minnesota Twins	San Francisco Giants	Taj Bradley	Anthony Molina	confirmed	confirmed	San Francisco, California	57 F	6.7 mph	0%	ready
San Diego Padres	Los Angeles Dodgers	Michael King	Brock Stewart	confirmed	confirmed	Los Angeles, California	67 F	2.2 mph	0%	ready

Current boundary: a resolved input row is not the same as a validated forecast. Starter, lineup, active-roster bullpen, and temperature effects now enter the score model; park factors, fresh reliever workload, and out-of-time calibration remain open gates.

Player simulation board · 2,000 draws per lineup

Player outcomes now live inside the game simulation

Confirmed orders are simulated through two continuous phases: the probable starter, then the opposing active-roster bullpen. The same draws produce full-game hitter lines and starter strikeout distributions.

Starter + bullpen Monte Carlo

Home-run probability leaders

Full-game hitter draws include posted batting-order opportunity, the probable starter, the active-roster bullpen quality layer, and the run environment.

Rank	Player	Team	Opponent	Probability	Mean
1	Eduardo Valencia	Detroit Tigers	Washington Nationals	50.6%	0.65
2	Max Clark	Detroit Tigers	Washington Nationals	35.1%	0.41
3	Shay Whitcomb	San Francisco Giants	Minnesota Twins	28.7%	0.32
4	Matt Olson	Atlanta Braves	Cincinnati Reds	28.3%	0.32
5	Ben Rice	New York Yankees	Tampa Bay Rays	26.7%	0.30
6	Kyle Schwarber	Philadelphia Phillies	Milwaukee Brewers	25.6%	0.28
7	Munetaka Murakami	Chicago White Sox	Kansas City Royals	25.6%	0.29
8	Griffin Conine	Miami Marlins	Chicago Cubs	25.4%	0.28
9	Hunter Goodman	Colorado Rockies	Arizona Diamondbacks	25.0%	0.28
10	Yordan Alvarez	Houston Astros	Seattle Mariners	24.1%	0.27

Starter + bullpen Monte Carlo

Hit probability leaders

Each hitter continues through the same batting order when the simulation moves from the starter phase to the bullpen.

Rank	Player	Team	Opponent	Probability	Mean
1	Michael Harris II	Atlanta Braves	Cincinnati Reds	78.9%	1.31
2	Ildemaro Vargas	Arizona Diamondbacks	Colorado Rockies	78.8%	1.26
3	Gabriel Moreno	Arizona Diamondbacks	Colorado Rockies	78.2%	1.28
4	Otto Lopez	Miami Marlins	Chicago Cubs	76.2%	1.24
5	Drake Baldwin	Atlanta Braves	Cincinnati Reds	75.9%	1.22
6	Eduardo Valencia	Detroit Tigers	Washington Nationals	75.3%	1.18
7	Randy Arozarena	Seattle Mariners	Houston Astros	75.3%	1.22
8	Ozzie Albies	Atlanta Braves	Cincinnati Reds	75.2%	1.15
9	Ketel Marte	Arizona Diamondbacks	Colorado Rockies	75.0%	1.20
10	Joshua Kuroda-Grauer	Athletics	Los Angeles Angels	74.8%	1.15

Starter + bullpen Monte Carlo

Extra-base-hit probability leaders

Doubles, triples, and home runs are simulated as mutually exclusive plate-appearance outcomes.

Rank	Player	Team	Opponent	Probability	Mean
1	Eduardo Valencia	Detroit Tigers	Washington Nationals	50.6%	0.65
2	Sean Murphy	Atlanta Braves	Cincinnati Reds	43.2%	0.53
3	Corbin Carroll	Arizona Diamondbacks	Colorado Rockies	43.0%	0.52
4	Kody Clemens	Minnesota Twins	San Francisco Giants	40.1%	0.48
5	Matt Olson	Atlanta Braves	Cincinnati Reds	39.9%	0.49
6	Pete Crow-Armstrong	Chicago Cubs	Miami Marlins	39.9%	0.48
7	Wyatt Langford	Texas Rangers	New York Mets	39.4%	0.47
8	Deyvison De Los Santos	Miami Marlins	Chicago Cubs	38.9%	0.47
9	Ketel Marte	Arizona Diamondbacks	Colorado Rockies	38.4%	0.45
10	Tommy Pham	Chicago White Sox	Kansas City Royals	38.1%	0.48

Starter + bullpen Monte Carlo

Two-plus total-base leaders

The total-base board preserves each simulated event mix instead of treating every hit as equivalent.

Rank	Player	Team	Opponent	Probability	Mean
1	Eduardo Valencia	Detroit Tigers	Washington Nationals	57.0%	3.13
2	Michael Harris II	Atlanta Braves	Cincinnati Reds	53.4%	2.26
3	Pete Crow-Armstrong	Chicago Cubs	Miami Marlins	51.3%	2.15
4	Ketel Marte	Arizona Diamondbacks	Colorado Rockies	51.0%	2.06
5	Gabriel Moreno	Arizona Diamondbacks	Colorado Rockies	50.9%	1.95
6	Ildemaro Vargas	Arizona Diamondbacks	Colorado Rockies	50.4%	1.90
7	Matt Olson	Atlanta Braves	Cincinnati Reds	49.8%	2.30
8	Otto Lopez	Miami Marlins	Chicago Cubs	49.7%	1.83
9	Wyatt Langford	Texas Rangers	New York Mets	49.7%	2.16
10	Randy Arozarena	Seattle Mariners	Houston Astros	48.6%	1.93

Starter + bullpen Monte Carlo

Five-plus strikeout leaders

Probable starters draw a game-specific batters-faced distribution against the posted opposing order.

Rank	Player	Team	Opponent	Probability	Mean
1	JR Ritchie	Atlanta Braves	Cincinnati Reds	81.8%	6.69
2	Brady Basso	Athletics	Los Angeles Angels	81.3%	6.57
3	Drew Anderson	Detroit Tigers	Washington Nationals	81.2%	6.56
4	Sean Manaea	New York Mets	Texas Rangers	80.2%	6.44
5	Zack Wheeler	Philadelphia Phillies	Milwaukee Brewers	78.6%	6.29
6	Taj Bradley	Minnesota Twins	San Francisco Giants	76.7%	6.21
7	Drew Rasmussen	Tampa Bay Rays	New York Yankees	72.6%	5.85
8	Logan Gilbert	Seattle Mariners	Houston Astros	67.5%	5.55
9	Shota Imanaga	Chicago Cubs	Miami Marlins	62.9%	5.31
10	Brock Stewart	Los Angeles Dodgers	San Diego Padres	61.7%	5.26

Starter + bullpen Monte Carlo

Seven-plus strikeout leaders

The upper-tail board responds to starter workload, the opposing order, and both pitcher and hitter strikeout rates.

Rank	Player	Team	Opponent	Probability	Mean
1	JR Ritchie	Atlanta Braves	Cincinnati Reds	51.2%	6.69
2	Drew Anderson	Detroit Tigers	Washington Nationals	50.0%	6.56
3	Brady Basso	Athletics	Los Angeles Angels	48.9%	6.57
4	Sean Manaea	New York Mets	Texas Rangers	46.7%	6.44
5	Zack Wheeler	Philadelphia Phillies	Milwaukee Brewers	45.0%	6.29
6	Taj Bradley	Minnesota Twins	San Francisco Giants	44.0%	6.21
7	Drew Rasmussen	Tampa Bay Rays	New York Yankees	36.5%	5.85
8	Logan Gilbert	Seattle Mariners	Houston Astros	31.3%	5.55
9	Brock Stewart	Los Angeles Dodgers	San Diego Padres	27.1%	5.26
10	Shota Imanaga	Chicago Cubs	Miami Marlins	26.9%	5.31

How to read it: each percentage is the share of simulated games in which the player reached that threshold. Posted batting-order opportunity, starter matchup, bullpen quality, park, and weather all move the distribution.

Game projections

The entire slate in one scan

Each game card shows the simulated win split, score center, uncertainty, and current input status.

Game 1 · scheduled slateNarrow lean

AwayTampa Bay Rays44.6%

HomeNew York Yankees55.4%

Mean score4.1 – 4.5Model total8.5One-run game36.9%

New York Yankees 55.4%20,000 draws · confirmed orders · matched starters

Game 2 · scheduled slateClear lean

AwayToronto Blue Jays33.1%

HomeBaltimore Orioles66.9%

Mean score4.0 – 5.3Model total9.2One-run game32.6%

Baltimore Orioles 66.9%20,000 draws · conditional orders · matched starters

Game 3 · scheduled slateClear lean

AwayWashington Nationals28.9%

HomeDetroit Tigers71.1%

Mean score4.4 – 6.2Model total10.6One-run game28.6%

Detroit Tigers 71.1%20,000 draws · confirmed orders · matched starters

Game 4 · scheduled slateClear lean

AwaySt. Louis Cardinals36.3%

HomePittsburgh Pirates63.7%

Mean score3.8 – 4.9Model total8.7One-run game34.3%

Pittsburgh Pirates 63.7%20,000 draws · confirmed orders · matched starters

Game 5 · scheduled slateNear toss-up

AwayMilwaukee Brewers47.5%

HomePhiladelphia Phillies52.5%

Mean score3.8 – 3.9Model total7.7One-run game38.8%

Philadelphia Phillies 52.5%20,000 draws · confirmed orders · matched starters

Game 6 · scheduled slateNear toss-up

AwayCleveland Guardians51.7%

HomeBoston Red Sox48.3%

Mean score3.6 – 3.4Model total7.0One-run game40.8%

Cleveland Guardians 51.7%20,000 draws · confirmed orders · matched starters

Game 7 · scheduled slateNear toss-up

AwayTampa Bay Rays46.4%

HomeNew York Yankees53.6%

Mean score3.5 – 3.7Model total7.2One-run game40.2%

New York Yankees 53.6%20,000 draws · confirmed orders · matched starters

Game 8 · scheduled slateNarrow lean

AwayCincinnati Reds40.8%

HomeAtlanta Braves59.2%

Mean score5.0 – 5.8Model total10.8One-run game32.7%

Atlanta Braves 59.2%20,000 draws · confirmed orders · matched starters

Game 9 · scheduled slateNear toss-up

AwayChicago White Sox48.0%

HomeKansas City Royals52.0%

Mean score4.2 – 4.4Model total8.6One-run game36.3%

Kansas City Royals 52.0%20,000 draws · confirmed orders · matched starters

Game 10 · scheduled slateNarrow lean

AwayMiami Marlins41.6%

HomeChicago Cubs58.4%

Mean score4.5 – 5.2Model total9.7One-run game33.9%

Chicago Cubs 58.4%20,000 draws · confirmed orders · matched starters

Game 11 · scheduled slateClear lean

AwayNew York Mets33.1%

HomeTexas Rangers66.9%

Mean score3.9 – 5.2Model total9.2One-run game32.9%

Texas Rangers 66.9%20,000 draws · confirmed orders · matched starters

Game 12 · scheduled slateClear lean

AwayArizona Diamondbacks70.1%

HomeColorado Rockies29.9%

Mean score5.4 – 3.8Model total9.2One-run game31.7%

Arizona Diamondbacks 70.1%20,000 draws · confirmed orders · matched starters

Game 13 · scheduled slateClear lean

AwayLos Angeles Angels37.8%

HomeAthletics62.2%

Mean score3.7 – 4.6Model total8.3One-run game36.1%

Athletics 62.2%20,000 draws · confirmed orders · matched starters

Game 14 · scheduled slateClear lean

AwayHouston Astros27.6%

HomeSeattle Mariners72.4%

Mean score4.0 – 5.9Model total9.9One-run game29.7%

Seattle Mariners 72.4%20,000 draws · confirmed orders · matched starters

Game 15 · scheduled slateClear lean

AwayMinnesota Twins62.5%

HomeSan Francisco Giants37.5%

Mean score4.8 – 3.8Model total8.6One-run game35.1%

Minnesota Twins 62.5%20,000 draws · confirmed orders · matched starters

Game 16 · scheduled slateClear lean

AwaySan Diego Padres38.4%

HomeLos Angeles Dodgers61.6%

Mean score3.8 – 4.6Model total8.4One-run game35.6%

Los Angeles Dodgers 61.6%20,000 draws · confirmed orders · matched starters

Feature simulation · 20,000 draws

Cleveland Guardians at Boston Red Sox

The closest matchup on today’s scheduled slate pairs the score distribution with the players most likely to produce a defining performance.

Model leanCleveland Guardians51.7%

Cleveland Guardians3.680% range 1–6

at

Boston Red Sox3.480% range 1–6

Winning-margin distributionAway ← outcome → Home

Away by 5+

4.4%

Away by 3-4

13.3%

Away by 2

13.2%

Away by 1

20.7%

Home by 1

20.1%

Home by 2

12.7%

Home by 3-4

12.0%

Home by 5+

3.6%

Why the model lands hereLeague ranks

1. Posted-lineup offenseCleveland Guardians99 vs 96 blended wRC+ after platoon, contact-quality, and recent-form adjustments
2. Probable starterCleveland GuardiansParker Messick 3.06 over 5.9 expected IP vs Payton Tolle 3.43 over 5.6 expected IP
3. Available bullpenBoston Red Sox3.81 vs 3.47 FIP blend with active reliever selector
4. Park and weatherRun environment56 F temperature adjustment; park factor 1

Projected standout performancesHighest-upside player outcomes in this matchup

2+ home runs

Wilyer Abreu

0.8%Boston Red Sox vs. Cleveland Guardians · expected 0.12

10+ strikeouts

Parker Messick

2.6%Cleveland Guardians vs. Boston Red Sox · expected 5.00

3+ total bases

Chase DeLauter

20.0%Cleveland Guardians vs. Boston Red Sox · expected 1.46

7+ strikeouts

Parker Messick

21.6%Cleveland Guardians vs. Boston Red Sox · expected 5.00

Public model audit

What the archived forecasts have actually done

Every number below comes from a prediction saved before first pitch and graded after the game became final.

Correct winner58.2%808 settled games

Final-total error3.50Mean absolute runs

Player props graded91,947Across published event types

Average prop gap1.6%Prediction vs. observed rate

Reading the audit: accuracy describes winner selection, while the calibration gap asks whether an event projected at a given rate occurred at roughly that rate. The sample is still growing and is reported without hiding misses.

Forecast boundary: these are probabilistic research outputs, not betting advice. The public audit is updated from forecasts archived before first pitch.

The board is rebuilt from the latest available schedule, probable starters, posted lineups, active rosters, park conditions, first-pitch weather, recent workload, and bullpen availability. These are probabilistic research outputs rather than betting advice.