Worked case study · 7 minute read
How a top-scoring team can miss the playoffs
Over the season, Lanterns score more total points than every other team. They finish second in scoring every week. They still miss our example league’s four-team playoff cutoff. The contradiction disappears when we look at who they faced.
The setup: eight teams, seven weeks, one opponent per week
The Example League has eight fictional teams. Every team plays every other team once over seven completed weeks. There are no ties, no league-median games and no score adjustments. The top four teams make the example playoffs; standings use wins first and total points as the tiebreaker.
Lanterns produce exactly 130 points each week, for 910 points overall. The next-highest total is Ravens’ 892. A repeated score is a teaching simplification: real lineups fluctuate. It lets us isolate opponent timing without changing the team’s own performance.
The three measures answer different questions. Points describe scoring volume. The official record describes seven scheduled contests. All-play compares each weekly score with all seven available opponents, creating 49 comparisons across the season.
Four strong scores meet the one stronger score
In each of the first four weeks, Lanterns run into the highest-scoring team. Their 130 points would beat the six remaining opponents, but the only result that counts in the standings is the scheduled loss. In weeks five through seven, 130 is still the second-highest score; the scheduled opponents now score less.
| Week | Lanterns points | Scheduled opponent | Official result | Other teams beaten | Effective-win contribution |
|---|---|---|---|---|---|
| 1 | 130 | Ravens: 150 | Loss | 6 of 7 | 6 ÷ 7 = 0.857 |
| 2 | 130 | Otters: 151 | Loss | 6 of 7 | 6 ÷ 7 = 0.857 |
| 3 | 130 | Meteors: 152 | Loss | 6 of 7 | 6 ÷ 7 = 0.857 |
| 4 | 130 | Owls: 153 | Loss | 6 of 7 | 6 ÷ 7 = 0.857 |
| 5 | 130 | Foxes: 100 | Win | 6 of 7 | 6 ÷ 7 = 0.857 |
| 6 | 130 | Badgers: 115 | Win | 6 of 7 | 6 ÷ 7 = 0.857 |
| 7 | 130 | Comets: 89 | Win | 6 of 7 | 6 ÷ 7 = 0.857 |
Week three is a useful place to pause. Meteors win 152–130. That is a decisive loss in the actual matchup, yet 130 beats the other six teams. Calling Lanterns weak based on that single loss would discard most of the available evidence. Calling them the week’s best team would also be wrong: Meteors score more.
Normalize all-play before comparing it with a seven-game record
Lanterns beat six of seven possible opponents every week. Across seven weeks, that produces 42 all-play wins and seven all-play losses. Comparing 42 directly with three official wins would be misleading because the number of comparisons is different. Divide by seven available opponents to put the two views on the same scale.
Effective losses = 7 ÷ 7 = 1.00
Matchup gap = official wins − effective wins = 3 − 6 = −3.00
Scale: 0 to 7 wins across seven completed weeks.
Under a uniform choice of one of the seven other teams each week, Lanterns’ score beats six possible opponents. Summing those weekly fractions gives six effective wins. This is a descriptive benchmark for the recorded scores, not a forecast that Lanterns are owed three future wins.
Our effective-record guide explains the full calculation, including ties and leagues with median games. This example avoids those settings so the arithmetic is visible.
The playoff cutoff follows the official results
| Rank | Team | Official record | Points | All-play W–L | Example playoff status |
|---|---|---|---|---|---|
| 1 | Ravens | 6–1 | 892 | 37–12 | In top four |
| 2 | Owls | 4–3 | 858 | 32–17 | In top four |
| 3 | Meteors | 4–3 | 743 | 18–31 | In top four |
| 4 | Foxes | 4–3 | 694 | 15–34 | In top four |
| 5 | Lanterns | 3–4 | 910 | 42–7 | Outside top four |
| 6 | Otters | 3–4 | 718 | 21–28 | Outside top four |
| 7 | Comets | 3–4 | 648 | 13–36 | Outside top four |
| 8 | Badgers | 1–6 | 698 | 18–31 | Outside top four |
Lanterns finish fifth. Three other teams have four wins, so Lanterns’ league-leading points cannot lift them above that group. Total points decide order only between teams tied on official results in this example. With that rule and a four-team cutoff, their season ends.
There is a second lesson in the table: Meteors and Foxes both reach four wins while losing most of their all-play comparisons. Their qualification is valid under the chosen format. The additional view tells us that their scheduled results were more favourable than their league-wide scoring profiles.
That does not establish that head-to-head is a bad format. It measures a consequence of the format. A league may value weekly rivalry and uncertainty more than rewarding the highest all-play total.
What we can—and cannot—conclude
Within these invented scores, the evidence supports saying that Lanterns scored consistently well and their schedule converted that performance into relatively few wins. It does not establish whether their manager drafted well, selected optimal starters or could repeat that performance next season.
We also cannot use this constructed case to estimate the percentage of real teams that suffer the same outcome. The data were selected to make the gap obvious. Measuring frequency would require a defined sample of real leagues, consistent inclusion rules and careful treatment of scoring formats.
The next useful test is a concrete counterfactual: keep the scores and change the schedule. In the companion Lanterns–Comets swap case, Lanterns move from 3–4 to 7–0. That is one possible schedule, not a new official record.
Use the same sequence in your own league
- Choose completed weeks and confirm the regular-season boundary. Avoid comparing an incomplete current matchup with finalized weeks.
- Read official record, total points and all-play together. Identify the disagreement before applying a label such as “unlucky.”
- Check each loss. A strong score meeting the week’s leader is different from repeatedly finishing in the bottom half.
- Confirm tiebreakers, divisions, median games and playoff rules with your commissioner before drawing a qualification conclusion.
- Use Calendar Swap to test a named alternative schedule, while preserving every team’s score.
The public example report includes all eight teams’ weekly points. You can inspect the inputs before trying the calculation on a Sleeper league.
Data and sources
All numbers on this page are calculated from the invented seven-week dataset shown in the example report’s source data. Each team has one score and one matchup per week. No Sleeper account, player lineup or real league was used.
The Sleeper API documentation for weekly matchups describes team points, roster IDs and shared matchup IDs. That is the structure used for live league analysis; the fictional numbers here were created independently. Was It Luck? is independent of Sleeper.
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The example report includes standings, weekly scores and a schedule swap. Open it directly, then use the same questions to investigate your own Sleeper league.