Independent. Educational. Not betting advice.

Search the site

Find a guide, team or tool

Probable pitchersNRFI LabStandingsParlay calculatorToday's matchups

MLB Luck Table: Actual vs Expected Wins

Runs scored and runs allowed predict a team's record better than the record predicts itself. Here is how far each club has drifted from its expected wins.

Updated · BaseballBetting.us editorial desk

Editorial illustration of a baseball sitting on one pan of an old balance scale, weighed against a four-leaf clover on the other pan

Actual vs expected wins, all 30 teams

Actual wins against Pythagorean expected wins, with one-run and extra-inning records
TeamW-LRSRARun diffExp. WLuck1-runExtras
Cincinnati Reds 75-87666826 -160 65 +10 26-179-5
Tampa Bay Rays 98-64736650 +86 90 +8 25-148-6
San Diego Padres 91-71722681 +41 85 +6 26-227-4
Philadelphia Phillies 88-74713698 +15 83 +5 25-167-6
Texas Rangers 80-82673719 -46 76 +4 23-174-2
Athletics 64-98699937 -238 60 +4 23-237-6
Arizona Diamondbacks 86-76739730 +9 82 +4 28-219-8
Toronto Blue Jays 79-83648694 -46 76 +3 20-246-7
Cleveland Guardians 85-77678667 +11 82 +3 27-227-5
Houston Astros 81-81734766 -32 78 +3 15-187-8
Minnesota Twins 77-85739797 -58 75 +2 18-235-6
Baltimore Orioles 79-82718739 -21 78 +1 18-248-8
Seattle Mariners 76-86664722 -58 75 +1 26-258-8
Atlanta Braves 94-68742626 +116 93 +1 27-218-6
Kansas City Royals 69-93690810 -120 69 0 21-264-7
Milwaukee Brewers 103-59832618 +214 103 0 27-2011-5
Miami Marlins 80-82715712 +3 81 -1 20-204-7
St. Louis Cardinals 77-85720749 -29 78 -1 24-309-10
Pittsburgh Pirates 82-80767739 +28 84 -2 28-216-10
Los Angeles Dodgers 100-62801600 +201 102 -2 31-236-1
New York Yankees 93-68739601 +138 96 -3 17-224-11
Boston Red Sox 87-75689611 +78 90 -3 21-217-4
Chicago White Sox 84-78776720 +56 87 -3 25-227-10
New York Mets 74-88699731 -32 78 -4 17-2310-8
Washington Nationals 77-85821815 +6 82 -5 18-229-5
Chicago Cubs 89-73850703 +147 95 -6 23-2111-9
Colorado Rockies 58-104752944 -192 64 -6 17-253-7
San Francisco Giants 65-97669760 -91 72 -7 16-297-7
Los Angeles Angels 62-100655752 -97 71 -9 19-296-14
Detroit Tigers 76-86723652 +71 89 -13 17-275-9

Click a header to sort. Luck = actual wins minus expected wins. Gold beat the run differential, pink fell short of it. One-run and extra-inning records are where most of that gap usually comes from.

Pythagorean record calculator

Enter any team's runs scored and allowed to see the record those runs point to, and how far the real record sits from it.

Expected win %-
Expected record-
Luck (actual - expected)-

Source: MLB Stats API (statsapi.mlb.com). 2026 regular season unless marked otherwise. Updated Oct 6, 2026, 4:51 AM ET. Expected wins = games × RS^1.83 / (RS^1.83 + RA^1.83), rounded.

A team’s record tells you what happened. Its runs scored and runs allowed tell you how well it actually played. Most of the time the two agree; when they do not, the gap is one of the most useful things a baseball bettor can know. The table above lines up all 30 clubs, actual wins against expected wins, sorted so the teams that have won the most games above their expectation sit at the top.

How to read the table

Each row gives a team’s win-loss record, its runs scored and runs allowed, the run differential, the number of wins those runs would predict, and the difference between actual and expected wins. A green plus number means the team has won more games than its runs support. A red minus number means it has won fewer. A zero means the record is exactly where the runs say it should be.

Expected wins are rounded to a whole number, so a difference of one or two games is well within normal noise. Look for the teams at the extremes, five or more games off in either direction, especially late in the season, when the sample is large.

Bill James, who created the Pythagorean expectation formula for baseball
Bill James, who created the Pythagorean expectation formula for baseball.Photo: Colette Morton and Dan Holden, CC BY-SA 2.0 via Wikimedia Commons

The Pythagorean formula

Bill James, the writer who did more than anyone to bring statistics into baseball conversation, noticed in the late 1970s that a team’s winning percentage could be predicted from runs scored and runs allowed with a simple formula. He called it the Pythagorean expectation because it looked like the famous theorem: runs scored squared, divided by runs scored squared plus runs allowed squared.

Later researchers tested the formula against decades of MLB results and found that an exponent a little under 2 fits better. The value 1.83 is the standard many analysts settled on, and it is the one we use. The table multiplies the resulting winning percentage by games played and rounds it:

Expected wins = games × RS^1.83 / (RS^1.83 + RA^1.83)

A worked example: a team that scores 750 runs and allows 650 over 162 games comes out at about 91.5 expected wins, so 92 after rounding. A team that scores and allows 700 lands at exactly 81, a .500 team. The rough rule of thumb that falls out of this is that about ten runs of differential are worth one win.

There are refinements, such as Pythagenpat, which adjusts the exponent to the scoring level of the season, but for a daily table the 1.83 version is close enough and easy to check by hand.

What over- and under-performance usually means

When a team beats its expected wins by a lot, the explanation is almost always the same: it has won an unusual number of close games. A club that goes 25-12 in one-run games while scoring barely more runs than it allows will look far better in the standings than on the field.

Some of that can be real. A dominant closer and a deep bullpen do help a team win close games, and a manager who uses them well can add a win or two over a season. But most of the gap is random. One-run games are close to coin flips, and a team that has won a big share of them has usually been lucky with timing: a hit that fell in the ninth, a double play that ended a rally.

The classic example is the 2012 Baltimore Orioles. They finished 93-69 with a run differential of just +7, which the formula would put at around 82 wins, and they went 29-9 in one-run games. They made the playoffs anyway, which is the part people remember. The next season they went 85-77. Their luck did not reverse; it just stopped.

Under-performers work the same way in reverse. A team with a strong run differential and a middling record has usually lost more than its share of close games, often because of a shaky bullpen. If the bullpen is fixed, or simply has better luck, the record tends to catch up with the runs.

Regression to the mean, and how bettors use it

“Regression to the mean” is the statistical way of saying that extreme results tend to be followed by less extreme ones. It does not mean a lucky team is due to lose. Past luck is not repaid. It means that over the rest of the season, a team’s run differential is a better guide to its future than its record.

For bettors, the most direct use is in futures, especially season win totals and division prices. The market leans on records and headlines. A team that is 12 games over .500 on a +20 run differential gets priced as a contender, while a team at .500 with a +60 differential gets less attention than it deserves. When the two disagree, the run differential usually wins over time, and a futures price built on the record can be too high or too low.

It helps with single games too, in a smaller way. On our matchup data page, each game shows both teams’ wins vs expected, so you can see at a glance when a favorite’s record is flattering it. Before you act on any of this, convert the price into a break-even rate with our betting calculators, and if moneylines and run lines are still new, start with our guide to reading baseball betting lines. Keep stakes within a budget you set in advance; betting is for adults 21 and older, and 1-800-GAMBLER is there if it stops being fun.

The limits of a luck table

The formula uses runs, and runs carry their own noise. A team that scored 14 in one blowout has a differential that overstates its typical game. Early in the season, a single lopsided series can move a team’s expected wins by two or three, so in April and May we would treat the table as a curiosity rather than evidence.

It also ignores what happens next. A team that traded away its best starter at the deadline or lost its closer to injury is not the team that built its run differential. And it cannot see the schedule ahead: a club with an easy final month will likely add wins whatever its luck so far.

Finally, it measures the past, not a price. Starting pitching still decides individual games, and our probable pitchers board shows who is on the mound today. First-inning tendencies are on our NRFI page, and the homepage links every guide and table on the site. For a disciplined way to put all of this together, our strategy guide covers bankroll and bet selection.

The teams near the bottom of the table can be the most interesting ones to watch in the second half. A club with a losing record and a positive run differential is the one most likely to be quietly underpriced, and the one most fans will have stopped paying attention to.

Frequently asked questions

What is Pythagorean expected wins in baseball?

It is an estimate of how many games a team should have won based on its runs scored and runs allowed. Bill James introduced the formula, and it tends to predict a team's future record better than its actual win-loss record does.

Why is the Pythagorean exponent 1.83?

Bill James originally used an exponent of 2, which is where the name comes from. Later testing against decades of MLB results found that a value around 1.83 fits real records a little more closely, so it became the common standard.

What does it mean when a team outperforms its expected wins?

It usually means the team has won more close games than its overall run production would suggest, often through a strong one-run record, a good bullpen or simple good fortune. Some of that edge can be real, but most of it tends to fade over the rest of a season.

Is a team that underperforms its run differential due for a winning streak?

Not due, but likely to do better from here on than its record suggests. Past bad luck does not have to be paid back, so the expected improvement applies to the games still to be played, not a correction of the ones already lost.

How do bettors use Pythagorean records?

They compare a team's expected wins with its actual record to find clubs the market may be over- or under-rating. It is most useful for season win totals and other futures, where a small edge in team quality adds up over many games.