# The Official (And Hopefully Not Too Cringe) 2024 ZiPS Projections

After all the rumors and money and projections, here we are, back at 0-0, with every team having at least some theoretical level of hope for the coming season. Beginning Thursday, actual games will turn these projections to shreds, but this is the best algorithmic projection I have the ability to make for 2024. Just a note that I have not committed an act of decimal cheating; ZiPS does not know that the Padres and Dodgers are 1-1.

The methodology I’m using here isn’t identical to the one we use in our Projected Standings, meaning there naturally will be some important differences in the results. So how does ZiPS calculate the season? Stored within ZiPS are the first- through 99th-percentile projections for each player. I start by making a generalized depth chart, using our Depth Charts as a jumping off point. Since these are my curated projections, I make changes based on my personal feelings about who will receive playing time as filtered through arbitrary whimsy my logic and reasoning. ZiPS then generates a million versions of each team in Monte Carlo fashion (the computational algorithms, that is — no one is dressing up in a tuxedo and playing chemin de fer like James Bond).

After that is done, ZiPS applies another set of algorithms with a generalized distribution of injury risk that changes the baseline PAs/IPs for each player. Of note is that higher-percentile projections already have more playing time than lower-percentile projections before this step. ZiPS then automatically (and proportionally) fills in playing time from the next players on the list to get to a full slate of plate appearances and innings. The model’s had a lot of updates since the pre-spring projections, so probabilities may have moved slightly more than you might have expected from the changes in wins.

The result is a million different rosters for each team and an associated winning percentage for each of those million teams. After applying the new strength of schedule calculations based on the other 29 teams, I end up with the standings for each of the million seasons. This is actually much less complex than it sounds.

The goal of ZiPS is to be less mind-blowingly awful than any other way of predicting the future. The future is tantalizingly close but beyond our ken, and if anyone figures out how to deflect astrophysicist Arthur Eddington’s arrow of time, it’s probably not going to be in service of baseball projections. So we project probabilities, not certainties.

Over the last decade, ZiPS has averaged 19.7 correct teams when looking at Vegas preseason over/under lines. I’m always tinkering with methodology, but most of the low-hanging fruit in predicting how teams will perform has already been harvested. With one major exception, most of ZiPS’ problems now are about accuracy rather than bias. ZiPS’ year-to-year misses for teams are uncorrelated, with an r-squared of one year’s miss to the next of 0.000562. Now, correlations with fewer than 20 points aren’t ideal, but the individual franchise with the highest year-to-year r-squared is the Mariners at 0.03, which isn’t terribly meaningful. If you think that certain franchises have a history of predictive over- or underperformance, you thought wrong, and I’d bet it’s the same for the other notable projection systems.

If you want to check out the pre-spring projections, which talk about the biggest things to happen up to that point, here are the links to the AL and NL projections. Since it has been requested, for these official 2024 projections, I’ve also added 80th and 20th percentile win totals to the standings tables.

ZiPS Projected Standings – AL East
Team W L GB Pct Div% WC% Playoff% WS Win% 80th 20th
Baltimore Orioles 91 71 .562 37.2% 34.8% 72.1% 8.8% 99.0 82.2
New York Yankees 87 75 4 .537 24.1% 35.2% 59.3% 5.2% 95.8 78.7
Toronto Blue Jays 87 75 4 .537 22.4% 35.9% 58.3% 5.0% 95.3 78.7
Tampa Bay Rays 83 79 8 .512 11.9% 29.2% 41.1% 2.3% 91.1 74.4
Boston Red Sox 77 85 14 .475 4.4% 17.5% 22.0% 0.7% 85.9 69.2

Since the last set of projections, the movement here can mostly be attributed to starting pitching. Corbin Burnes provides a huge boost to the Orioles, but some of the benefit of his addition is negated because of less optimistic innings totals for the injured John Means and, more significantly, Kyle Bradish. The injury to Yankees ace Gerrit Cole diminishes their outlook a bit, though they still have the American League’s third highest playoff probability. Lucas Giolito wasn’t expected to pitch the Red Sox to the postseason, but his injury makes a Boston playoff berth even less likely.

ZiPS Projected Standings – AL Central
Team W L GB Pct Div% WC% Playoff% WS Win% 80th 20th
Minnesota Twins 86 76 .531 41.8% 15.7% 57.5% 4.5% 94.1 77.0
Cleveland Guardians 85 77 1 .525 38.4% 16.6% 55.1% 3.9% 93.3 76.7
Detroit Tigers 78 84 8 .481 13.2% 11.6% 24.8% 0.8% 85.8 69.3
Kansas City Royals 73 89 13 .451 5.9% 6.5% 12.5% 0.2% 81.4 65.0
Chicago White Sox 63 99 23 .389 0.6% 0.8% 1.5% 0.0% 71.5 54.8

People might still be shocked to see the White Sox with a 1.5% chance of making the postseason, but one of the things I’ve learned after doing this for 20 years is that people – even the most sophisticated ones – tend to underrate how often improbable things happen. Luckily, with so many years in the books, I’ve had the ability to do a lot of calibration! In most simulations, the division features a fairly tight race between the Twins and Guardians for the title and the Tigers finishing third. And because the Central is relatively weak, a Royals playoff appearance would be unlikely but not unreasonably so.

ZiPS Projected Standings – AL West
Team W L GB Pct Div% WC% Playoff% WS Win% 80th 20th
Houston Astros 88 74 .543 37.0% 26.2% 63.2% 6.3% 96.5 79.4
Texas Rangers 86 76 2 .531 28.4% 27.0% 55.5% 4.5% 94.4 77.6
Seattle Mariners 86 76 2 .531 27.4% 27.3% 54.7% 4.3% 94.0 77.6
Los Angeles Angels 77 85 11 .475 6.9% 14.7% 21.6% 0.7% 85.6 68.7
Oakland A’s 63 99 25 .389 0.2% 0.9% 1.1% 0.0% 71.6 54.7

The big change here is a slightly more negative distribution of the innings for Astros pitchers, narrowing their lead over the Rangers and Mariners. I appreciate ZiPS’ bringing the M’s just that much closer to the Seattle Mariners .540 meme. The A’s now project to finish a fraction of a win ahead of the White Sox in the AL basement, which is some kind of victory, I guess.

ZiPS Projected Standings – NL East
Team W L GB Pct Div% WC% Playoff% WS Win% 80th 20th
Atlanta Braves 95 67 .586 62.6% 21.4% 84.0% 15.2% 103.3 86.0
Philadelphia Phillies 85 77 10 .525 17.9% 33.4% 51.2% 3.7% 93.3 76.7
New York Mets 83 79 12 .512 12.9% 28.2% 41.1% 2.3% 91.2 74.0
Miami Marlins 79 83 16 .488 6.3% 20.2% 26.6% 1.0% 87.1 70.4
Washington Nationals 66 96 29 .407 0.3% 2.0% 2.3% 0.0% 74.1 57.4

ZiPS does give the Braves a 1% chance at winning 116 games! Atlanta lost a bit in the probabilities because of some changes in the generalized playing time model that fills in the backups. Even if ZiPS sees the playoffs as a bit less certain for this team than it did six weeks ago, the Braves still have the highest projected win total in the majors. The Marlins took a sizable hit after some negative injury news, a pretty big deal for them since the pitching staff is their source of upside. It sure ain’t the hitting!

ZiPS Projected Standings – NL Central
Team W L GB Pct Div% WC% Playoff% WS Win% 80th 20th
St. Louis Cardinals 83 79 .512 27.8% 16.0% 43.8% 2.6% 90.7 74.4
Chicago Cubs 82 80 1 .506 27.9% 15.6% 43.5% 2.5% 91.0 74.2
Cincinnati Reds 80 82 3 .494 20.8% 14.3% 35.1% 1.6% 89.0 71.6
Milwaukee Brewers 78 84 5 .481 14.7% 12.6% 27.3% 1.0% 86.8 70.0
Pittsburgh Pirates 75 87 8 .463 8.9% 9.0% 17.9% 0.5% 83.7 67.3

ZiPS loves Pete Crow-Armstrong and is suspicious of Cody Bellinger matching his 2023 numbers, but bringing him back was still enough to push the Cubs into a near-statistical tie in what was already projected to be a very close race. The Brewers took a hit with the loss of Burnes, and as a result, they slightly boosted the projections for the other four teams in the division.

ZiPS Projected Standings – NL West
Team W L GB Pct Div% WC% Playoff% WS Win% 80th 20th
Los Angeles Dodgers 93 69 .574 49.3% 29.7% 79.0% 11.9% 101.1 84.2
Arizona Diamondbacks 86 76 7 .531 20.5% 34.9% 55.5% 4.4% 94.4 77.8
San Francisco Giants 85 77 8 .525 17.2% 32.1% 49.4% 3.4% 93.2 76.1
San Diego Padres 83 79 10 .512 12.7% 28.5% 41.2% 2.3% 91.3 74.0
Colorado Rockies 67 95 26 .414 0.2% 1.9% 2.1% 0.0% 74.5 59.0

The NL West contenders fighting with the Dodgers – which means the three other teams that are not the Rockies – all received a boost because, since the pre-spring projections, they each added one of the top starting pitchers available, either in free agency or via trade, this offseason. The Diamondbacks, Giants, and Padres are better after having acquired, respectively, Jordan Montgomery, Blake Snell, and Dylan Cease, but the moves haven’t changed the relative positions of these teams in the projected standings. Even so, these deals — along with San Francisco’s signing of Matt Chapman — have created more scenarios in which the Dodgers can be bested for the divisional title, though they remain the favorites.

One thing you see a lot on social media, especially from sites that repost these projections, is outrage that “the best team will only have X wins.” The Orioles are projected to have the best record in the AL, at 91-71, but that doesn’t mean that ZiPS projects 91 wins to lead the AL. Those 91 wins represent Baltimore’s 50th percentile performance in those million simulations, and it is astronomically unlikely that all 30 teams hit their 50th-percentile projections. On average, you should expect three teams to hit their 90th percentile, six to hit their 80th, nine to hit their 70th, and so on and so forth. But again, it’s rarely going to be that neat. So here’s the percentile matrix for the number of wins it would take to secure each of the six playoff spots.

ZiPS Playoff Matrix
To Win 10th 20th 30th 40th 50th 60th 70th 80th 90th
AL East 89.3 92.0 94.0 95.8 97.4 99.1 100.9 103.0 105.9
AL Central 83.0 86.0 88.1 90.0 91.8 93.6 95.6 97.9 101.1
AL West 86.6 89.4 91.5 93.4 95.1 96.8 98.7 100.9 103.9
To Win 10th 20th 30th 40th 50th 60th 70th 80th 90th
AL Wild Card 1 87.4 89.2 90.6 91.8 93.0 94.2 95.5 97.0 99.2
AL Wild Card 2 84.1 85.8 87.0 88.0 89.0 90.1 91.2 92.5 94.4
AL Wild Card 3 81.6 83.1 84.3 85.3 86.2 87.1 88.2 89.4 91.1
To Win 10th 20th 30th 40th 50th 60th 70th 80th 90th
NL East 88.3 91.4 93.6 95.6 97.5 99.4 101.5 104.2 107.8
NL Central 83.5 86.2 88.1 89.8 91.4 93.0 94.8 96.8 99.6
NL West 88.8 91.7 93.8 95.7 97.5 99.2 101.1 103.3 106.4
To Win 10th 20th 30th 40th 50th 60th 70th 80th 90th
NL Wild Card 1 87.4 89.3 90.6 91.8 93.0 94.2 95.5 97.1 99.2
NL Wild Card 2 84.0 85.7 87.0 88.0 89.0 90.0 91.1 92.4 94.2
NL Wild Card 3 81.5 83.1 84.2 85.2 86.2 87.1 88.1 89.3 91.0

Dan Szymborski is a senior writer for FanGraphs and the developer of the ZiPS projection system. He was a writer for ESPN.com from 2010-2018, a regular guest on a number of radio shows and podcasts, and a voting BBWAA member. He also maintains a terrible Twitter account at @DSzymborski.