Ben Lindbergh and Meg Rowley banter about Simeon Woods Richardson’s podcast-approved use of written notes, whether David Fry or Jurickson Profar has the most delightfully surprising stats, Kevin Pillar’s post-White Sox hot streak, MLB’s offensive outage in May, Blake Snell and other slow-starting late-starting starters, Matt Waldron’s knuckleball usage and Jeremiah Estrada’s strikeout streak, and the worst way for the zombie runner to end a game. Then (45:35) they talk to Keith Morrisroe, Nationals bullpen cart driver, about the finer points of bullpen-cart operation and receiving a tip from reliever (and rider) Steven Okert.
It may still feel like the 2024 season just got started, but Major League Baseball passed the one-third mark this past week. This is usually a good time for a full, fresh run of the ZiPS projected standings, and I think it’s especially so now after Ronald Acuña Jr.’s season-ending injury, which will have a serious impact on the NL East race.
The ZiPS projected standings use a different methodology than our Depth Chart standings, beyond only using ZiPS rather than a ZiPS/Steamer mix. 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. I then make my own changes, and the final results are correlated with, but far from identical, to Jason Martinez’s projected PAs and IPs. It varies from player to player, but the biggest systemic difference is that my “average” projected playing time for individual players reflects a larger chance of significant injury. I feel this methodology helps better express a team’s depth, something crucial as the season goes on and IL attendance grows. It has the disadvantage, though, of being quite workload intensive, meaning it’s not something that can just be auto-run every morning.
The one change in methodology from past standings is that the average playing time for the projected players is month-based. For example, ZiPS sees no innings for Jacob deGrom at all in June or July, with most of the innings (I have the average at 15) coming in September. So each time, rather than having one distribution of expected team strength for the season, ZiPS now has six distributions for each team based on the calendar month. While the resulting changes are quite small, the sad truth is that baseball projections are mature enough after a couple decades that all improvements are tiny. It’s not just the low-hanging fruit that’s gone; you now have to climb a rickety ladder held by an inebriated friend to get the ones way up there.
Let’s get into the projections before we reach a Tolkien-movie level of narrator exposition. It should go without saying, because it rarely seems to end up that way, but take this as a reminder that 0.0% is not literally 0.0%, but until mathematical elimination, a number that rounds to 0.0%.
ZiPS Projected Standings – NL East (5/29)
Team
W
L
GB
Pct
Div%
WC%
Playoff%
WS Win%
80th
20th
Philadelphia Phillies
94
68
—
.580
64.6%
28.5%
93.1%
9.2%
100.4
88.5
Atlanta Braves
90
72
4
.556
33.1%
46.8%
79.9%
7.2%
96.6
83.9
New York Mets
78
84
16
.481
2.1%
17.2%
19.4%
1.1%
84.3
71.9
Washington Nationals
71
91
23
.438
0.2%
3.3%
3.5%
0.0%
77.5
65.2
Miami Marlins
67
95
27
.414
0.0%
0.6%
0.6%
0.0%
73.0
61.0
The Phillies have seen their projections sink a bit after losing four of five games to the Rockies and Giants, but the Acuña injury is a disaster for the Braves. ZiPS sees Philadelphia and Atlanta as basically equals now, but with a five-game lead, attrition benefits Philadelphia, not Atlanta. The Mets remain as mediocre as their preseason projections said, but the Acuña injury let them claw back almost a full percentage point of divisional probability over the last week, despite their dreadful recent stretch. The Nats have played much better than their expected doormat status, but they’re not certainly not inside the house yet, and ZiPS sees their relevance on the edge of the wild card race slipping away. The Marlins’ 6-24 start to the season all but officially eliminated them from the divisional race, but after playing roughly .500 ball this month, it’s at least plausible, though incredibly unlikely, that they could make a run for the third wild card spot.
ZiPS Projected Standings – NL Central (5/29)
Team
W
L
GB
Pct
Div%
WC%
Playoff%
WS Win%
80th
20th
Milwaukee Brewers
84
78
—
.519
36.8%
17.0%
53.8%
2.3%
90.4
78.3
Chicago Cubs
83
79
1
.512
29.0%
16.9%
45.9%
2.6%
89.1
77.0
St. Louis Cardinals
81
81
3
.500
19.2%
15.1%
34.3%
1.6%
87.1
75.0
Cincinnati Reds
78
84
6
.481
10.0%
10.3%
20.3%
0.9%
84.1
71.7
Pittsburgh Pirates
75
87
9
.463
5.0%
6.2%
11.3%
0.3%
81.4
69.5
Jackson Chourio has struggled, but Milwaukee has received solid offense contributions from almost every other position. Who had Joey Ortiz likely finishing 2024 with more WAR than Jackson Holliday? I can’t say ZiPS or I did, either. (Well, unless I lie.) ZiPS doesn’t expect Robert Gasser to maintain that microscopic ERA, but it does think he’ll get a pretty good jump from what is now a surprisingly low strikeout rate. Right now, the Brewers are the slight favorite to win the Central, but every team in the division still maintains more than a scrap of a chance. I personally think the Cubs will be the most aggressive at the deadline, but that’s a little out of ZiPS’s wheelhouse.
ZiPS Projected Standings – NL West (5/29)
Team
W
L
GB
Pct
Div%
WC%
Playoff%
WS Win%
80th
20th
Los Angeles Dodgers
95
67
—
.586
73.1%
21.3%
94.4%
16.1%
101.4
89.4
San Diego Padres
85
77
10
.525
11.6%
43.4%
55.0%
3.8%
91.2
79.1
San Francisco Giants
84
78
11
.519
9.6%
40.0%
49.6%
2.9%
90.3
78.0
Arizona Diamondbacks
82
80
13
.506
5.8%
33.1%
38.9%
2.6%
88.3
76.2
Colorado Rockies
64
98
31
.395
0.0%
0.1%
0.1%
0.0%
70.2
58.7
There were scenarios in which the Dodgers were topped in the NL West, but it doesn’t look like any of them are coming to pass. Outside of Bobby Miller’s shoulder injury, the rotation has held together quite well, and we’re getting closer to Clayton Kershaw’s possible return. The Padres and Giants have seen their divisional odds get longer since March, but their win projections remain about where they were initially expected, and both teams are serious wild card contenders. The 50th-percentile win projection for the last NL wild card berth is 85.4, a number well within the realm of possibility for both teams. So could the Diamondbacks, but their odds of getting there are a little less likely because, as of now, they’re three games behind San Diego and San Francisco. The Rockies are stubbornly hanging onto that last decimal point, though ZiPS think they’re the worst team in the National League.
ZiPS Projected Standings – AL East (5/29)
Team
W
L
GB
Pct
Div%
WC%
Playoff%
WS Win%
80th
20th
Baltimore Orioles
95
67
—
.586
47.7%
43.8%
91.5%
12.0%
101.4
89.1
New York Yankees
95
67
—
.586
47.2%
44.2%
91.4%
10.3%
101.4
89.2
Toronto Blue Jays
83
79
12
.512
3.0%
29.7%
32.7%
2.1%
88.6
76.5
Tampa Bay Rays
79
83
16
.488
1.2%
16.7%
17.9%
0.7%
85.3
73.3
Boston Red Sox
79
83
16
.488
0.9%
15.2%
16.1%
0.4%
84.9
72.7
Contrary to the preseason, the playoff picture in the AL East has cleared up considerably in two months. What was projected to possibly be a race between all five clubs, with even the Red Sox having a decent shot, has largely become a two-team competition between the Orioles and Yankees. ZiPS likes the Yankees slightly better in an “everybody stays healthy” projection, but with the injury risks all built in, ZiPS gives the Orioles the subtle nod due to their superior depth. ZiPS still believes the Blue Jays could contend for a wild card spot, because the offense can’t be this mediocre moving forward, but after struggling for two months, Toronto has basically been lapped by Baltimore and New York. ZiPS remains skeptical that the Red Sox will keep up their current win pace (at least their Pythagorean one), but the system thinks the rotation’s success is legitimate. It’s weird seeing the Rays with the worst bullpen WAR in baseball; I almost typed the Devil Rays when looking at that chart.
ZiPS Projected Standings – AL Central (5/29)
Team
W
L
GB
Pct
Div%
WC%
Playoff%
WS Win%
80th
20th
Cleveland Guardians
93
69
—
.574
58.7%
27.7%
86.3%
7.9%
99.2
87.1
Minnesota Twins
88
74
5
.543
22.8%
38.6%
61.4%
4.8%
93.8
81.4
Kansas City Royals
86
76
7
.531
15.7%
37.1%
52.8%
2.1%
92.0
80.1
Detroit Tigers
80
82
13
.494
2.9%
14.6%
17.4%
0.6%
85.2
73.1
Chicago White Sox
56
106
37
.346
0.0%
0.0%
0.0%
0.0%
62.1
50.1
ZiPS was the Cleveland believer of the projection systems coming into the season, but not even it could’ve expected the Guardians to win two-thirds of their games. I’m not going get mad at my computer for not realizing that David Frywould play like the second coming of Ted Williams. But if the Guardians are bound for some regression, the AL Central is not exactly full of teams that could overrun them. ZiPS remains extremely skeptical of the Royals, but they’ve banked enough wins that they’re not going to disappear from the race anytime soon. The computer now thinks the AL Central will have 1.2 wild card spots (on average), a big jump from 0.5. After an abomination of a start to the season, the White Sox have played just well enough that they still have a 20% chance of avoiding 100 losses. That’s something, I guess.
ZiPS Projected Standings – AL West (5/29)
Team
W
L
GB
Pct
Div%
WC%
Playoff%
WS Win%
80th
20th
Seattle Mariners
85
77
—
.525
48.6%
10.3%
58.9%
3.8%
91.3
79.5
Texas Rangers
82
80
3
.506
27.3%
10.9%
38.2%
2.4%
88.2
76.1
Houston Astros
81
81
4
.500
21.5%
9.5%
31.0%
2.1%
87.0
74.6
Los Angeles Angels
72
90
13
.444
2.4%
1.6%
4.0%
0.1%
78.1
65.9
Oakland A’s
65
97
20
.401
0.1%
0.1%
0.2%
0.0%
70.5
58.5
The Astros must play under a fortunate star because this has to be their best-case scenario considering their abysmal start to the season. With the Rangers treading water and playing some lousy baseball of late, the Mariners doing the usual Mariners .540 thing, and the Angels looking like a lost cause, nobody ran away with the division while the Astros sputtered. The Logan Roy of the AL West, Houston’s future may have some serious questions, but the team has weathered what was likely its worst stretch of pitcher injuries. The lack of a frontrunner in the West has kept Oakland theoretically in the mix, but the team lacks depth to remain single-digit games back from first place for much longer, and its owner is probably far too apathetic about his club’s short-term fate to make any big additions at the deadline. At least Mason Miller is a lot of fun.
As usual, I’m including the ZiPS playoff matrix, which shows the percentile results for the win total of each playoff spot’s eventual victor. For example, while the Orioles and Yankees are both projected to win 95 games, ZiPS projects that the average eventual result for the team that wins the AL East will be 99.3 wins.
ZiPS Playoff Matrix (5/29)
To Win
10th
20th
30th
40th
50th
60th
70th
80th
90th
AL East
92.3
94.6
96.4
97.9
99.3
100.8
102.4
104.2
106.7
AL Central
89.0
91.3
92.8
94.3
95.6
97.0
98.5
100.3
102.8
AL West
82.6
84.7
86.3
87.7
89.0
90.3
91.8
93.4
95.8
To Win
10th
20th
30th
40th
50th
60th
70th
80th
90th
AL Wild Card 1
88.8
90.4
91.6
92.6
93.6
94.7
95.9
97.3
99.4
AL Wild Card 2
85.5
86.8
87.8
88.7
89.5
90.3
91.2
92.3
93.8
AL Wild Card 3
83.1
84.3
85.2
86.1
86.8
87.6
88.4
89.3
90.7
To Win
10th
20th
30th
40th
50th
60th
70th
80th
90th
NL East
89.4
91.9
93.7
95.3
96.8
98.3
99.9
101.7
104.3
NL Central
83.4
85.4
86.9
88.2
89.4
90.6
92.0
93.5
95.8
NL West
89.6
91.9
93.5
95.1
96.5
98.0
99.7
101.6
104.4
To Win
10th
20th
30th
40th
50th
60th
70th
80th
90th
NL Wild Card 1
87.1
88.6
89.8
90.8
91.8
92.8
93.9
95.2
97.2
NL Wild Card 2
84.0
85.3
86.3
87.2
88.0
88.8
89.7
90.7
92.2
NL Wild Card 3
81.7
82.9
83.9
84.7
85.4
86.1
87.0
87.9
89.2
In order to not have to reference the preseason projections, I’m also including a sortable table of how the playoff/divisional/World Series probabilities have changed since the preseason projections.
I like to make up statistics. Why? Because it’s fun, mostly. There’s so much baseball analysis on the internet these days that without shaking things up, it’s hard to say something truly interesting. Isolated power? You’ve seen it a million times. Strikeout rate, or even strikeout rate implied by whiff rate? Boring. xWhatever, something with BACON in it? We’ve done that before.
Most of my random gimmick stats don’t really catch on. But I’ve used two this year that I think have some real analytical interest to them, and they’re not exactly on the FanGraphs leaderboard page. So I’m going to maintain some Google Sheets with them highlighted, and I’m also going to intermittently highlight the best performers.
Remember whomps per whiff? That one is just fun to say, and particularly fun to hear Vinnie Pasquantinosay. Also, it seems like it’s doing something right. Here are the top 10 hitters in baseball by that statistic this year, minimum 500 pitches seen:
Oh look, another statistic that tells you Juan Soto is amazing. What he’s doing this year is truly ridiculous. He’s absolutely clobbering the ball and yet rarely swinging and missing. He’s as far ahead of Ryan O’Hearn in second as O’Hearn is ahead of Taylor Ward in 10th. He has more barrels and 30 fewer whiffs than Shohei Ohtani. Read the rest of this entry »
I think everyone has moments where they wonder just what the hell they’ve done with their lives. I’ve been blessed with the divine spark of human consciousness, and a body to tote those thoughts around in, and what have I accomplished? I had one of those moments recently while I was holding a friend’s baby, trying to make her laugh. What a delightful and important but most of all profound thing, to create a whole other person and cultivate her — from scratch — into a happy adult.
Or the next best thing, creating art. I’ll speak to what I know: music. I’m left in awe of songs that, through dynamic contrast and precision of rhythm and density of countermelody, seem to be carrying that divine spark themselves — the second movement of Beethoven’s 7th symphony, or Typhoon’s “Prosthetic Love.” So much care and emotion went into such composition that it’s hard not to be bowled over by the emotional transference of the artistic process even as you’re astounded by how precisely the pieces have been crafted and how seamlessly they fit together.
Again: What am I doing with my life to show that I value this gift? How am I using this spark to shape the world into a better place? How am I passing this light on to others? This thought burst out and grabbed me recently when I was poking around our site’s pitcher defense leaderboards and noticed something interesting about Josh Fleming. Read the rest of this entry »
For the last few years, I’ve been checking the accuracy rate of the ball-strike calls made by umpires, dividing the number of correct calls by the total number of takes. It’s a blunt approach, but because umpires make so many thousands of calls each year, it yields solid results. On Tuesday, I pulled the numbers for the 2024 season, and I found something I didn’t expect: Accuracy is going down rather than up. In every single season since the beginning of the pitch tracking era in 2008, umpires have gotten better at calling balls and strikes according to the Statcast strike zone. This is the first time I’ve ever pulled the numbers and seen a lower accuracy rate. However, this is also the first time I’ve checked the numbers this early in the season, and it turns out umpires tend to make better calls as the season goes on. Since 2017, accuracy in March, April, and May has been 0.19 percentage points lower than accuracy over the full season (though the difference in 2023 was just 0.03 percentage points). Here’s what that looks like in a graph.
You know how at the beginning of every season, there are a couple blown calls during a nationally televised game (or at least, calls that appeared to be wrong according to the on-screen strike zone), and certain people start complaining that umpires are terrible and they’re getting worse? Those people always catch me off guard. I usually forget about the missed calls when the season ends, but those people somehow manage to keep their umpire anger at a high idle through the entirety of the offseason so that the instant baseball returns, they’re ready to shout about the umpires again without any need to ramp up. I don’t know how they do it without pulling an oblique, but in a sense, those angry people are right. Even though the umpires are always getting better year after year, they’re nearly always more accurate toward the end of the season than at the beginning — so much so that when the season starts, they’re worse than they were at the end of the previous season. For a month or two, the umpires really have gotten worse. We often say early in the season that pitchers are ahead of hitters. It turns out they’re ahead of umpires too.
For each season, I broke down the overall accuracy in two-month increments, essentially dividing the season into thirds. I also broke down the accuracy during spring training and the playoffs, although there are plenty of factors that make those numbers suspect. During spring training, the umpiring pool is much wider. Perhaps more importantly, there are far, far fewer tracked pitches during spring training, both because the number of games is so small and because not every stadium is set up for Statcast. That results in a much smaller, much less reliable sample. The playoffs are also a much smaller sample, but they’re also, at least in theory, selecting for better umpires. Working the playoffs is seen as an honor and a reward for performing well in the regular season. We should expect accuracy to be at its lowest during spring training and highest during the playoffs.
Generally speaking, the results fit our preconceptions. Spring training accuracy is very low and it features the volatility that we’d expect from a small dataset. Umpires are also more accurate in the playoffs. The red line is March, April and May, and as you can see, it’s nearly always below everything but the spring training line. Not only do umpires start getting better in June, but they keep getting better right through the end of the season, which is why the light blue line for August, September, and October is usually above the yellow line for June and July. The trend is a little bit easier to see if we focus just on pitches in the shadow zone, the area that’s one baseball’s width from the edge of the zone on either side.
In the graph above, the dotted line represents that season’s overall accuracy on calls in the shadow zone. Each data point represents the number of percentage points above or below that year’s average. Not only do the calls get better as the season goes on, there’s a definite gap between the first two months and the rest of the season. Umpires are decidedly worse in those first two months. However, 2023 was a real outlier. It was first time since 2008 that umpires were more accurate in the beginning of the season than the end.
With that, I want to bring you back to 2024. So far this season, umpires have gotten 92.46% of calls right, down from 92.81% in 2023 and just two thousandths of a percentage point higher than in 2022. Based on everything I’ve shown you, we should expect umpires to get better over the rest of the season. However, the drop-off from last year is noticeable. Accuracy over the first two months of the season has only fallen once before, from 2009 to 2010, when it dropped by 0.16 percentage points. So far this season, accuracy has fallen by twice that amount: 0.32 percentage points. That’s a tiny change, on the order of one call per game, but that doesn’t make it any less real. We’ll have to wait and see how the rest of the season goes, but perhaps this year really could end up being different. Or, if it follows the pattern of the past decade and a half, accuracy will soon be in its way up.
Ben Lindbergh and Meg Rowley banter about the career and competitive implications of Ronald Acuña Jr.’s latest season-ending injury, the retirement of infamous ump Angel Hernandez, the aesthetics of umps issuing warnings, the Brewers’ success sans Craig Counsell and David Stearns, a new unwritten rule against any(?) bunting, White Sox players vs. White Sox skipper Pedro Grifol, Tim Anderson’s offense, Aaron Judge’s defense, and team meetings prior to Patrick Corbin starts. Then (1:02:12) they talk to official MLB historian John Thorn and Negro Leagues researcher Larry Lester about MLB adding Negro Leagues stats to its official major league historical record, pensions for surviving Negro Leagues players, the East-West Classic, and more, plus a few follow-ups (1:43:07).
When Steven Kwan left the Guardians’ May 4 victory after straining his left hamstring, the Guardians owned the American League’s second-best record (21-12) as well as a 1.5-game lead in the AL Central. While Kwan was their most productive hitter at the time, they’ve thrived in his absence, going 15-6 thanks in part to a nine-game winning streak that ended at the hands of the Rockies on Monday. All of that has netted them the league’s second-best record (36-18)… and a 2.5-game lead in the Central. Baseball is a funny game sometimes.
The Guardians haven’t gained as much ground as you might expect given that the Royals ran off an eight-game winning streak that began on the same day as Cleveland’s streak and have gone 14-7 in Kwan’s absence; meanwhile, the Yankees have gone 15-5 to supplant the Orioles (12-7) as the team with the league’s best record. Still, the streak did create some daylight between the Guardians and the Twins, who were tied for second in the division with the Royals but have since gone 10-11 to fall to 6.5 games back.
A soft schedule probably didn’t hurt the Guardians, either. After winning the rubber game of their three-game series with the Angels sans Kwan, they took two of three from the Tigers, lost three of four to the White Sox (oops), then took two of three from the Rangers before sweeping consecutive three-game series from the Twins, Mets, and Angels. Collectively those teams have a weighted winning percentage of .418, with the Twins (.547 via a 29-24 record) the only ones at or above .500.
Kwan’s injury is a convenient inflection point for analysis. If it’s still somewhat arbitrary, it does offer a window into the Guardians’ overall performance, as well as how they’ve maintained a .714 winning percentage without him. Read the rest of this entry »
Hi! It has been made to clear to me that my use of f = m * a as a narrative device herein was quite distracting, chiefly because in this context it’s incorrect. I apologize in advance to renowned baseball physicist Prof. Alan Nathan, should he ever read this; to all other physics enthusiasts who have remarked on the mistake; and to me, for embarrassing me. Ideally you will see past it and appreciate the meat and potatoes of the post for what they are: that there is possibly declining marginal utility to bat acceleration in a way we don’t seem to witness for bat speed. Thanks, and sorry again!
I can’t possibly begin to cover all the excellent work concerning Statcast’s new bat tracking data. Now as much as ever, it’s important to support your local Baseball Prospectuses, PitcherLists, Baseball Americas, FanGraphses and freelance Substack writers. We move quickly in these parts. There’s so much analysis to consume, all of it superb.
When confronted with this new data, one of my first instincts was to see which metrics from other areas of sabermetric analysis could be replicated within the bat tracking framework. Enter 90th-percentile exit velocity (90EV); it’s a powerful shorthand metric that distills a lot of information about the top end of a hitter’s exit velocity distribution into a single number. It’s not perfect, and other metrics outperform it, but it’s easy to see how it has become popular in contemporary analysis, especially in prospecting and scouting circles. Read the rest of this entry »
We knew the best hitter in baseball this year would be a multi-positional talent. We knew he would play for one of the top teams in the league. We knew the value of his contract would begin with the words “seven hundred” and the first syllable of his last name would be a source of complex carbohydrates. What we didn’t know is that it would be Guardians catcher/outfielder/first baseman/third baseman/DH David Fry, who is making $741,100 this season and currently leads the majors (min. 50 PA) in OBP (.488), OPS (1.079), wOBA (.459), and wRC+ (204).
The Brewers took Fry in the seventh round of the 2018 draft, eventually sending him to the Guardians during the 2021-22 offseason as the player to be named later in a trade for right-hander J.C. Mejía. Fry had first appeared on the Brewers’ top prospect list ahead of the 2020 season, when Eric Longenhagen ranked him 24th in a weak system, noting the positional flexibility that made him “an interesting potential bench piece.” That assessment largely stuck as Fry rose through the minor leagues (and switched organizations), although he was downgraded from a 40 FV to a 35+ FV in 2021 and eventually fell out of the Guardians’ top 50 ahead of the 2023 season. Eric tweaked his evaluation that year, subtly downgrading Fry from “interesting potential bench piece” to “interesting 26th man candidate.” It was a fair assessment at the time; Fry was roughly a league-average hitter in his first full season at Triple-A (105 wRC+). Entering his age-27 campaign, there wasn’t much reason to bet on his upside.
Yet, Fry was hard to ignore during his first full spring in big league camp in 2023. He bookended that spring training with home runs in his first and last at-bats and hit well in between, too, finishing with a 154 wRC+ in 19 games. Although he didn’t make the Guardians’ Opening Day roster, he surely made a good impression; after a solid month back at Triple-A, he earned his call to the show. Playing catcher, first base, corner outfield, and a little bit of third (with a couple of pitching appearances to boot), Fry showed off his versatility while hitting well enough (106 wRC+) to collect major league paychecks for the rest of the year. Entering 2023, ZiPS projected a .291 wOBA from Fry, and he boosted that projection to a .306 wOBA before the start of this season. Nobody would call his performance last year a breakout, but he put himself on the inside track to play a role for Cleveland once again in 2024. Read the rest of this entry »
Several preseason favorites are sliding down these rankings as we barrel toward the third month of the season, while other clubs — most notably the Guardians — are continuing their surprisingly strong starts.
This season, we’ve revamped our power rankings. The old model wasn’t very reactive to the ups and downs of any given team’s performance throughout the season, and by September, it was giving far too much weight to a team’s full body of work without taking into account how the club had changed, improved, or declined since March. That’s why we’ve decided to build our power rankings model using a modified Elo rating system. If you’re familiar with chess rankings or FiveThirtyEight’s defunct sports section, you’ll know that Elo is an elegant solution that measures teams’ relative strength and is very reactive to recent performance.
To avoid overweighting recent results during the season, we weigh each team’s raw Elo rank using our coinflip playoff odds (specifically, we regress the playoff odds by 50% and weigh those against the raw Elo ranking, increasing in weight as the season progresses to a maximum of 25%). As the best and worst teams sort themselves out throughout the season, they’ll filter to the top and bottom of the rankings, while the exercise will remain reactive to hot streaks or cold snaps.
First up are the full rankings, presented in a sortable table. Below that, I’ve grouped the teams into tiers with comments on a handful of clubs. You’ll notice that the official ordinal rankings don’t always match the tiers — I’ve taken some editorial liberties when grouping teams together — but generally, the ordering is consistent. One thing to note: The playoff odds listed in the tables below are our standard Depth Charts odds, not the coin flip odds that are used in the ranking formula.
All power rankings stats, including team records, are updated through Sunday’s games. The information included in the comments are current as of Tuesday morning.Read the rest of this entry »
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