Lakewood Rod & Gun 2023-2025

Schedule Fairness Analysis

This report tests whether strong weekly point totals were more likely to come against lower-finishing teams, and whether the current unbalanced schedule leaves enough variation in opponent strength to affect the standings. It also includes an exploratory division simulation section to show how structure can help or hurt depending on how divisions are built.

For a tighter 2025 case study, open the top 4 schedule breakdown.

Main Takeaways

2023 Correlation
0.198

Weaker opponent, better-than-usual team points.

2024 Correlation
0.319

The strongest week-level scoring signal in the three-year sample.

2025 Correlation
-0.003

No real week-level signal league-wide.

2025 Top Finishers
3 Of Easiest 4

Three of the four easiest schedules belonged to the eventual top three finishers.

Top 4 Breakdown

The separate 2025 page drills into the top four finishers team by team. It shows the weakest opponents each one actually played, the points they scored in those weeks, the stronger teams they did not have to face, and how they performed against other top finishers.

Open it here: top-4-schedule-analysis-2025.html

Week-Level Scoring Signal

Against bottom five: +0.667 points versus each team’s own season average.

Against top five: -0.501 points versus each team’s own season average.

Top 3 only vs bottom five: +0.515.

Top 3 only vs top five: +0.167.

Correlation: 0.198

Week-Level Scoring Signal

Against bottom five: +0.969 points versus each team’s own season average.

Against top five: -1.072 points versus each team’s own season average.

Top 3 only vs bottom five: +0.855.

Top 3 only vs top five: -0.893.

Correlation: 0.319

Week-Level Scoring Signal

Against bottom five: -0.140 points versus each team’s own season average.

Against top five: +0.000 points versus each team’s own season average.

Top 3 only vs bottom five: -0.639.

Top 3 only vs top five: +0.371.

Correlation: -0.003

What That Means

The 2023 and 2024 seasons both show the same directional pattern: teams tended to post stronger-than-normal point weeks against lower-finishing opponents. That means opponent quality mattered in the weekly points race. In 2025 that relationship was not visible at the week level, but the final top three teams still benefited from easier overall schedules.

Said differently: even when a single missed matchup does not explain the standings, schedule imbalance can still matter across the whole season by shifting the average difficulty of the opponents a team actually faced.

Avoiding The Top 4

Using each season's actual top 4 as the stronger teams, and only counting opponents from weeks that were actually played, the pattern across 2023-2025 is that teams that missed more top-4 opponents tended to finish higher.

Top-4 Opponents Missed Average Finish Median Finish Teams Read
0 10.88 11.5 26 Teams that faced every top-4 opponent finished lowest on average.
1 10.19 10.5 26 Missing one top team helped a little.
2 10.25 9.0 8 This bucket still trends better than facing every top-4 opponent, but not by a huge margin.

Year by year, the effect gets stronger. In 2023, teams that missed a top-4 opponent finished 0.53 places better on average. In 2024, that gap grew to 2.15 places. In 2025, the gap was much smaller at 0.55 places.

So the cleanest statement is not that 2025 proved the point by itself. It is that across the full 2023-2025 sample, teams that avoided more top-4 opponents generally finished a little better, with 2024 providing the strongest single-year example.

Biggest Beatings And Top-Finisher Correlation

To test whether dominant weekly wins were connected to the teams that finished at the top, I flagged each season's top 10 percent of scoring margins as "major beatings." That cutoff was 7.0 points in 2023, 10.0 in 2024, and 9.0 in 2025.

2025 Group Major Wins Major Losses Average Per Team Read
Top 4 finishers 4 0 1.00 major wins, 0.00 major losses The eventual top 4 were never on the receiving end of a 2025 major beating.
All other teams 11 15 0.69 major wins, 0.94 major losses The rest of the league both delivered and absorbed more blowout volatility.

The strongest 2025 correlation is not that every top finisher piled up huge wins. It is that the top teams almost never got buried. John Angeletti Jr. / Jeff Angeletti and PJ Degnan / Casey Digirolamo each posted two major beatings, while Bill Johnson / Bryce Ireland and Jody Gwin / Kane Desmond reached the top four without any major beatings either for or against them.

That makes blowouts more of a stability signal than a full explanation. The top teams did not all dominate the weakest opponents, but they also avoided the large negative swings that show up more often in the middle and bottom of the standings.

Were The Same Teams Taking The Major Beatings?

Team Major Losses Seasons Hit Note
Randy Gray / Mike Peterson 6 2 The most repeated blowout recipient in the sample, with major losses concentrated in 2023 and 2025.
John Angeletti Jr. / Jeff Angeletti 6 2 Took several big losses in 2023 and 2024, then flipped to a top-2 finish in 2025.
Mike Brandow / Chris Allenson 6 2 Frequently on the wrong end of the largest weekly margins in 2024 and 2025.
Aaron Widrig / Evan Acklin 4 3 The clearest three-year repeat case: not the highest total, but spread across every season in the sample.

On the delivery side, PJ Degnan / Casey Digirolamo recorded the most major wins across the three-year sample with six, and did it in all three seasons.

Who The Top Teams Missed

Year Finish Team Average Rank Of Missed Teams Missed Opponents
2023 1 Randy Lobb / Randy Fosberg 13.00 Cole Robbins / Reid Sturzenbecker (final rank 12)
Jimmy Shultz / Steve Briggs (final rank 15)
Randy Gray / Mike Peterson (final rank 16)
Al Johnson / Jim Gustafson (final rank 9)
2023 2 Bill Johnson / Bryce Ireland 9.25 Mike Sard / Tim Loomis (final rank 3)
John Angeletti Jr. / Jeff Angeletti (final rank 18)
Bernie Anderson / Dave Warren (final rank 7)
Al Johnson / Jim Gustafson (final rank 9)
2023 3 Mike Sard / Tim Loomis 10.25 Mike Brandow / Chris Allenson (final rank 5)
Bill Johnson / Bryce Ireland (final rank 2)
John Angeletti Jr. / Jeff Angeletti (final rank 18)
Randy Gray / Mike Peterson (final rank 16)
2024 1 Brian Devine / Craig Acklin 5.50 Mike Sard / Tim Loomis (final rank 4)
Chuck Shick / Dave Rowe (final rank 7)
2024 2 Cole Robbins / Reid Sturzenbecker 12.00 Bill Johnson / Bryce Ireland (final rank 8)
Randy Lobb / Randy Fosberg (final rank 16)
2024 3 Al Johnson / Jim Gustafson 11.50 Doug Hosier / Chris Payne (final rank 9)
Chris Henderson / Jeremy Gruber (final rank 14)
2025 1 Bill Johnson / Bryce Ireland 11.20 Mike Brandow / Chris Allenson (final rank 17)
Butch Camarata / Zach Camarata (final rank 7)
Chuck Shick / Dave Rowe (final rank 5)
Chris Henderson / Jeremy Gruber (final rank 11)
Bernie Anderson / Dave Warren (final rank 16)
2025 2 John Angeletti Jr. / Jeff Angeletti 10.80 Mike Sard / Tim Loomis (final rank 9)
PJ Degnan / Casey Digirolamo (final rank 4)
Butch Camarata / Zach Camarata (final rank 7)
Dave Ruby / Roger Kent (final rank 20)
Randy Lobb / Randy Fosberg (final rank 14)
2025 3 Jody Gwin / Kane Desmond 10.00 Mike Sard / Tim Loomis (final rank 9)
Aaron Widrig / Evan Acklin (final rank 10)
Todd Conklin / Bruce Myers (final rank 6)
Brian Devine / Craig Acklin (final rank 15)

Higher missed-opponent average means the team skipped weaker finishers. Lower means it skipped stronger finishers.

How Uneven Was The Actual Schedule?

Year Schedule Spread Schedule SD Average Missed Opponents Average Repeat Opponents Top 3 Played-Schedule Average
2023 2.25 0.640 3.8 0.8 10.44
2024 1.61 0.449 1.9 0.9 10.61
2025 2.67 0.751 4.0 0.0 11.44

Schedule spread is the gap between the easiest and hardest played schedules, measured by opponents’ final standings ranks. Bigger spread means a wider fairness gap across the field.

What About A Division Structure?

The table below is exploratory only. It is not a proposed final schedule. It uses standings-seeded divisions and then forces a full in-division round robin before filling the remaining weeks. This is useful because it shows an important truth: structure alone is not enough. If divisions are seeded or built poorly, a division system can actually make schedule inequality worse.

Year Format Schedule Spread Schedule SD Avg Missed Avg Repeats Top 3 Schedule Avg
2023 2 divisions of 10 4.75 1.480 4.2 1.2 8.96
2023 4 divisions of 5 6.88 2.272 4.7 1.6 7.30
2024 2 divisions of 10 2.11 0.489 1.8 0.8 9.87
2024 4 divisions of 5 4.23 0.769 1.8 0.3 9.50
2025 2 divisions of 10 4.00 1.383 4.9 0.9 9.31
2025 4 divisions of 5 7.13 2.456 5.7 1.6 7.41

The takeaway is not that divisions are bad. The takeaway is that divisions need a fairness rule behind them. If the goal is fair qualification, the best argument is this: make teams compete primarily against a smaller group where everyone shares the same core opponents. That removes a lot of the current “you happened to miss these two teams” noise inside the race that actually matters.

Best Case For A Structured Division Layout

Based on these three years, the strongest defensible statement is: the current unbalanced format creates real schedule-strength variance, and a structured division schedule would make the qualification race fairer if the division schedule itself is shared evenly.