Follow the evidence
Open a pick to see its reasoning and sources. Forecasts and reporting each keep their own dates.
COLLEGE FOOTBALL RESEARCH & PICKS
Duck Force One · College football research & ESPN College Pick’em.
INDEPENDENT COLLEGE FOOTBALL RESEARCH
The picks. The case behind them. The results that keep us honest.
Duck Force One brings college football research and ESPN College Pick’em together. Follow our weekly picks, get to know a matchup, then follow the results after the final whistle.
Made by a fan who likes to show the work. Independent of ESPN.
MAKE YOUR NEXT PICK AN INFORMED ONE
Ten picks, ranked from 10 points to 1. Read the reasoning, the risks and what changed.
See this week’s picks →02 / GAME RESEARCHExplore the wider slate, team statistics, player profiles and dated reporting.
Find a game →03 / THE RESULTSThe original pick, the final score and the confidence points earned, with postgame reporting.
Read the week’s results →AN OPINION YOU CAN EXAMINE
We review the football case, then compare it with the market and our experimental research model. Every card keeps its original choices, so the results can be judged honestly.
When those views disagree, you can see it. When a source is missing or a game goes the other way, that stays visible too.
How Duck Force One works →Open a pick to see its reasoning and sources. Forecasts and reporting each keep their own dates.
A favorite can lose. Compare estimates and explore possible outcomes before assigning your points.
Compare final scores with forecasts saved before kickoff. Earlier versions remain available.
THE WORK DOESN’T END AT KICKOFF
Submitted cards, actual game results and forecast accuracy—all in the open.
EXPERIMENTAL MODEL COMPARISON
66.5% experimental model comparison.
Week 8 game analysis, saved win chances, player leaders, analyst views and evidence.
Saved market benchmark: Southern California at 56.2%.
Forecast saved 2026-10-23T21:30:37.752828+00:00. Dated reporting and final scores load separately.
All Week 8 games →Sign in to save your private weekly card
Opening this week’s card builder…
DUCK FORCE ONE · ESPN COLLEGE PICK’EM
Confidence-point comparisons will show both save dates when the records load.
| Pts | Pick / opponent | Win chance | Confidence points since previous save |
|---|---|---|---|
| Loading Weekly Picks… | |||
SAVED OUTCOMES
The same ten picks, played out 100 different ways.
Fixed probabilities and independent outcomes. These are simulated outcomes, not 100 forecasting models or estimates of the chance of winning a pool.
A new forecast never changes a recorded submission.
Market quotes for the selected run. Historical workbook content is available in Source archive.
Loading saved records…
Loading saved records…
Loading saved records…
Loading saved records…
Loading saved records…
ABOUT DUCK FORCE ONE
Duck Force One is Justin Hanes’s independent college football project and ESPN College Pick’em entry. It brings the weekly picks, the case for each game, and the actual results together. Built by a fan in Seattle, with Oregon always on the watchlist.
You can follow the published picks or build your own card. The goal is to make each choice understandable: why that team, why that many points, and what could go wrong. Duck Force One is not affiliated with ESPN.
THREE THINGS YOU’LL SEE
Starting in Week 7, we save an independent football assessment before retrieving new market prices. We compare the evidence and document the final selection; the no-vig market remains our benchmark.
How we get that numberAn experimental estimate built from team performance and preseason information. It can agree or disagree with the published pick.
What goes into the modelESPN’s matchup probability is a statistical estimate. A writer’s prediction is an opinion. We identify the source and the type of prediction.
How to read those comparisonsEvery Week 7 forecast requires a saved research checkpoint, market benchmark and ten documented decisions. Judgment estimates are labeled unvalidated. A run receipt in its briefing shows the sequence, evidence and limitations.
HOW THE PICKS ARE MADE
The market benchmark uses this process for the ten games selected by ESPN College Pick’em. The final card may differ when its documented review supports a different estimate. The same market method covers other games on the research page when the required odds are available.
We use paired moneyline prices from at least two named sportsbooks. A moneyline is the price for a team to win outright, rather than cover a point spread. Each quote keeps its source and update time.
Odds usually imply a combined probability above 100%. We convert both prices into probabilities and divide each by their combined total. The two adjusted win chances then add up to 100% for that book.
Each qualifying book contributes an estimate. The benchmark takes the simple average and picks the team above 50%. If the required odds are missing, we show the gap instead of inventing a market forecast.
The published update retains its probabilities, confidence order, source times and notes. A later update gets its own record. Earlier picks remain available.
Illustration: suppose the two prices imply 60% and 45%. Together, that is 105%. Divide each by 105%: the adjusted chances are about 57.1% and 42.9%. This removes the margin mathematically; it does not turn the market into a certainty or correct every pricing bias.
This describes the current method. Some earlier saved updates used different source blends or a stated confidence override. Their original methods and numbers stay with those records.
WHY ONE PICK GETS MORE POINTS
The benchmark ranks selected winners by their unrounded win chances. The reviewed card may use a different confidence order when the football evidence supports it. Each change requires a saved explanation and an explicit comparison of expected points under the same market probabilities. Every number is used once: 55 points are available.
Expected points describe an average over many comparable outcomes. This game will earn either 10 or 0. A 70% estimate still leaves a 30% chance of losing.
Assigning larger point values to stronger win chances maximizes expected confidence points under those estimates. A football review that changes this order gives up some of that benchmark expectation; we disclose the cost and do not claim an unproven payout advantage. It does not guarantee a weekly prize or maximize the chance of beating every particular opponent. Close probabilities can also make adjacent ranks nearly interchangeable.
The tiebreaker is a separate predicted combined score for ESPN’s designated game. It is saved with the update and does not change the confidence order. See the current Weekly Picks.
THE RESEARCH MODEL
This is a separate, experimental statistical model. It estimates the chance of winning from team information rather than using the current sportsbook prices to choose a side.
How effectively a team advances the ball, how consistently its plays succeed, and its scoring margin—with opponent strength taken into account.
Talent and recruiting measures, plus returning production in passing, rushing and receiving. These provide context when the current season has only a small sample.
Home-field setting and explicit handling of missing data. Coverage gaps remain visible; a missing estimate is not a 50% forecast.
The formula was fitted on 2015–2024 games and frozen. New eligible team data can change a forecast; we do not refit the formula every time someone refreshes the website. The current game’s final result is not an input to its pregame forecast.
When it disagrees with Duck Force One’s pick, that is useful context to investigate—not an automatic reason to switch sides. Agreement is not independent proof that a pick is right. We compare both estimates with the actual results.
The displayed Research model is a regularized logistic model: it learns a restrained relationship between those inputs and a win probability. It uses opponent-adjusted efficiency, success rate and margin, home venue, talent, recruiting and returning-production differences. Missing values use saved training-data replacements and missing-data indicators.
Historical training data can reflect later revisions. Good historical fit alone does not establish performance on newly published forecasts. The dated, pregame record is the more useful test. The model does not directly read breaking injury reports, weather or analyst articles into its probability.
THE CASE BEHIND EACH GAME
Game analysis brings together team statistics, official availability reports, weather, local coverage and attributed analyst views. The game recap and preview connect the pick to its evidence, gives the other team’s route to a win and identifies unresolved questions.
We do not add an arbitrary injury or weather adjustment to a win chance. A reporting note can flag a risk or a need to recheck the odds without silently changing the saved number.
Player statuses keep their original report and check dates. An initial report can change. “Not listed” or “not checked” does not mean cleared to play.
Team reports, local journalism and national analysis keep their attribution. A quoted opinion is separate from our interpretation. Missing or conflicting evidence stays visible.
An AP or other poll ranking is labeled with its poll and week. It is a ranking, not a win probability, and does not by itself determine the confidence order.
An ESPN matchup win probability comes from its statistical forecast. A Football Power Index (FPI) rating is a measure of team strength, not itself a matchup percentage. A writer may predict an outright winner, a point-spread result or a total; those are different questions and are labeled accordingly.
AI tools help collect and organize evidence, build the site and draft explanations. They are not a news source or a substitute for the linked reports. The numerical estimates follow the saved methods above; generated prose is not another forecasting model.
100 POSSIBLE SATURDAYS
Each simulation draws a winner for every game using the saved win probabilities, then scores the card. The process repeats 100 times. Games are drawn independently and probabilities stay fixed within that saved run.
A team with a 60% win chance will not necessarily win exactly 60 of those 100 draws. The sample illustrates uncertainty; it does not improve the original forecast, simulate an exact football score, or prove that the picks work.
Play out your week lets you set particular results and see what they would mean for the card. Those scenarios do not change the published picks.
THE RESULTS THAT MATTER
Ten submitted picks, the confidence points actually assigned, and points earned from the outcomes. A draft recommendation and an ESPN submission are different records.
The market benchmark and research model are evaluated on eligible forecasts saved before kickoff. The direct comparison uses games covered by both, so different coverage does not skew the comparison.
The season record uses each week’s registered original forecast. You can also grade another saved update, but it does not rewrite that original benchmark. A score refresh updates the outcomes; it does not replace the predictions being evaluated.
We show correct picks and probability error. The error measure checks how close the estimated chances were to what happened; lower is better, and confident misses are penalized more. Missing, unfinished or unverified results are excluded, never counted as losses.
Explore the track record →DATES & LIVE UPDATES
A cloud collector runs on Supabase, independently of this website and your computer. It checks CollegeFootballData for scores and game status across the saved research slate every 30 minutes. Around active games, it checks about every two minutes. Oregon is included whenever its game is in the saved slate.
Verified scores are saved once and shared by Game day, game pages, team schedules and full-slate Results. Open pages check that shared record once a minute while visible. The collector keeps running when you close the page. This is periodic score checking, so changes can appear a few minutes after the play and depend on the provider’s timing.
The site keeps the last verified score and its original check time. An update panel shows the last successful check, the next planned check and any delay. The collector retries automatically; an unavailable score is never counted as a loss. Confirmed finals earn points, and score changes are retained for review.
There is currently no dedicated midweek news-discovery collector. The hourly availability task focuses on games within two hours of kickoff; it does not continuously search for Dante Moore or other unresolved players. New reporting appears when a source review is completed. A separate news-monitoring service is being planned; it is not active yet.
A separate daily collector refreshes the season statistics used in matchup comparisons after 6 a.m. Pacific. It checks every game in the active published slate, using CollegeFootballData totals through the preceding week. A failed check keeps the last verified edition.
Team schedules, polls, rosters and player totals refresh daily at 6:30 a.m. Pacific. A full-slate research task is scheduled for 7 a.m.; postgame reviews are scheduled for 8 a.m. A scheduled task is not proof that its review finished. An hourly check from 9 a.m. to 11 p.m. looks for final availability and weather updates for games approaching kickoff. A separate 6 a.m. task prepares fresh odds, the upcoming slate and a new draft card once ESPN’s lineup and required evidence are available. These cloud tasks keep the last valid edition if a source fails. The update-status panel reports a failed or incomplete review.
Odds, availability reports, news, polls and detailed player statistics retain their own dates. The score collector does not review those sources, create a new forecast, change the confidence order or submit a card to ESPN. Submitted league totals remain the recorded ESPN results; Game day can separately calculate a card’s points from verified finals.
A pregame percentage remains a pregame percentage during the game. It is not a live win probability calculated from the score and clock.
MAKE IT YOUR OWN
Build my card lets you choose winners and rank all ten picks. Your browser draft and shared link do not alter Duck Force One’s published picks or submit anything to ESPN. A draft can be edited, including after kickoff; an explicitly saved pregame record preserves the version and server timestamp.
Compare the choices, read the evidence, and make the call yourself.
Loading saved records…
Loading saved records…
Opening the Operations Center…