The Padres are underperforming both expectations and their underlying numbers

San Diego's run differential suggests it should be one of the best teams in baseball this season rather than struggling for a Wild Card playoff spot

Aug 12, 2023

SAN DIEGO, Calif. — The Padres have Major League Baseball’s third highest payroll and a lineup card that reads like an All Star roster, but are currently on the outside of the playoff picture looking in. Despite being forecasted to be one of the league’s best teams at the start of the year their chances at reaching the postseason are now at about 30 percent

with two months left in the regular season.

They’re running out of time. But based on Pythagorean Winning Percentage

, a metric developed by famed sabermetrician Bill James to help evaluate a team’s performance relative to expectations given its run differential, the Padres should have a considerably better record than their 56-60 clip at this point in the season.

It could mean they sneak into the playoffs if things start tilting the right way in the limited time they have given their underlying numbers. Or it could mean disappointment in a season that started with postseason aspirations, much less World Series ones.

With a run differential of +56 runs, we’d expect San Diego to be about 11 games above .500 at this point in the season rather than four games under. That 8-game gap makes the Padres the most unlucky team in the majors by a wide margin.

I mean, look at their lineup; with names like Fernando Tatis Jr., Juan Soto, Manny Machado and Xander Bogaerts, they have a murderer’s row of offensive talent. They also didn’t skimp in the pitching department signing household names like Blake Snell, Josh Hader, Yu Darvish and Joe Musgrove for lots of money this year.

But despite their depth on paper the Padres have been consistently inconsistent on the field. The latest example was losing three of four to the Dodgers last weekend after sweeping one of baseball’s top teams in the Texas Rangers at Petco Park the previous one.

If you look at overall team Wins Above Replacement (WAR

) the Padres look even better than what pythagorean expectation gives you. Neil Paine wrote this week that San Diego should be a top-five team based on this measure of how many wins a team should have.

**Packed Petco** | The Padres won 8-3 in front of a sold out crowd against the NL West-leading Dodgers on Saturday night, but ultimately lost three of the four games in the series.

The Chicago Cubs and the aforementioned Rangers make for interesting case studies using pythagorean expectation as well. The Cubs are currently on a tear having won 14 of their last 20 games including taking two out of three against the Braves, the best team in baseball, last weekend. They also outscored the NL Central-leading Cincinnati Reds by 22 runs in the series before that.

But they’ve underachieved their runs scored profile in the standings as well. We would expect Chicago to be 13 games over .500 while the two teams ahead of them in the division should be under .500. Unlike the Padres, things are trending in the right direction for the North Siders as they make a playoff push.

The Rangers, meanwhile, should have the best record in baseball based on their league-leading +175 run differential as of Friday night, but they’ve gotten relatively unlucky this season as well

There’s no doubt the Padres are a lot better than their record if you dive deeper into their numbers this season, but they’re running out of time to prove that least season’s NLCS appearance was no fluke for an organization that has experienced a dearth of playoff success.

Using Neil Paine’s method of computing a composite average of a team’s predicted wins and playoff odds courtesy of FanGraphs and Baseball-Reference.

According to MLB’s Advanced Stats glossary, “The concept strives to determine the number of games that a team *should* have won -- based its total number of runs scored versus its number of runs allowed -- in an effort to better forecast that team's future outlook.”

A metric designed to quantify the value of individual players’ entire statistical profile like batting, fielding, pitching and baserunning.

Code to recreate the above plots can be found on my Github.