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424,069 observationssnapshot 2026-10-15Registry

Sports · 4d · asked 2026-10-01 · scored 2026-10-05

Will the San Francisco 49ers cover -3 against the Denver Broncos on October 4, 2026?

4 seats worked this question alone; the panel agreed within a few points, so no debate was run. Code ran every test and computed the number. How the desk works

Committee44%PM-stated number (before 2026-10-02) · stated range 38% to 50%
Market at the timenot priced
ResolvedYesBrierBrier score How wrong a probability was, squared. Say 70% and it happens: (0.7 − 1)² = 0.09. Say 70% and it doesn't: 0.49. Lower is better; always saying 50% scores 0.25, so anything above 0.25 is worse than a coin flip. glossary 0.314 · lower is better

Resolves yes if NFL-SF.margin level>= 3.5 before 2026-10-04 (store data, NFL-SF from the desk's own series).

0%50%100%
Sports Analyst44%
Quantitative Researcher46%
Market Positioning Analyst45%
Causal Skeptic42%
Committee44%

Hollow: before the debate. Gold: after. Green rule: what happened. Debate skipped: the seats agreed within a few points. Sat out: Historical Analog Analyst.

The dispute that matteredAll four analysts land in a tight 0.42-0.46 band, so there is no real probability disagreement -- the substantive split is interpretive: A and C treat the -7.5→-3 line move as a strong, information-rich bearish signal for SF that should pull probability meaningfully below 50%, while D explicitly argues the historical series show no stable causal pathway (leave-one-out corr=0.084) and that the line move alone shouldn't be over-weighted beyond a small nudge off the no-edge base rate. I resolve this by treating the line move as ONE piece of evidence (not four), crediting it primarily to D's more disciplined, skepticism-adjusted interpretation, and supplementing with B's independent empirical base rate (historical margin distribution, P≈0.43) as a second, genuinely separate corroborating line. This converges the committee's four restatements of the same market signal into two real evidence lines, both landing near 0.43-0.44, which is why the consensus sits at the low end of the stated range rather than at the simple cross-analyst midpoint.

Synthesis

Base rate: using SF's own 48-game historical margin distribution (mean=1.06, sd=13.99), a normal approximation puts P(SF margin >= 3.5) at ~0.43 -- this is the starting point before any game-specific adjustment. All four analysts update only modestly off this base rate (range 0.42-0.46), driven almost entirely by one shared observation: the spread moved sharply from SF -7.5 to SF -3 over the week, which the committee interprets as the market absorbing adverse information about SF (injury/lineup) faster than any stale favorable signal. Because this line-move evidence is cited by all four analysts off what is effectively the same market data feed, I collapsed it to one evidence line rather than four, and weighted analysts by (a) calibration quality in this segment, (b) sports-domain relevance, and (c) whether they added anything beyond restating the line move. Analyst D's leave-one-out robustness check and Analyst B's independent historical-margin base rate are the only two evidence lines that are genuinely separate from the shared market signal, so I weighted D and B's interpretive framing (modest, disciplined downward adjustment) more heavily than C's (whose calibration is worst in the group and whose evidence is fully duplicated). Final consensus: P(SF covers -3) = 0.44, CI [0.38, 0.50]. Top disagreement -- how hard to lean on the line move as a bearish signal -- was resolved by crediting D's more skeptical treatment (nudge off base rate, not a large repricing) over A/C's stronger bearish framing, while still letting the shared signal pull the estimate from a 0.43 base rate down only slightly to 0.44 (effectively near-neutral). TRADEABILITY: This is marginally tradeable. At standard -110 pricing (52.4% breakeven), a true P(SF cover)=0.44 implies betting Denver +3 has ~+6% expected value per unit staked. However, this edge is thin, rests on only two quasi-independent evidence lines, and the committee's own calibration history in this segment is mediocre (3 of 4 analysts <=55% historical accuracy). Recommended expression, if trading: a small, size-constrained position on Denver +3 (or equivalently fading SF -3), sized to reflect low conviction (e.g., 0.5-1x normal unit size), not a full-conviction position. Do not treat the four analysts' agreement as four independent confirmations -- it is closer to one strong signal (the line move) corroborated by one weaker independent base-rate check.
Observed · in the data
  • Spread opened/moved from SF -7.5 on 2026-09-27 to SF -3 by 2026-10-04 (as of as_of date, game is scheduled, line not yet final-closing)
  • Moneyline-implied win probability for SF trended down from a stated high (~0.66) to recent values clustered around 0.575
  • Historical SF margin series (n=48 games) has mean=1.062, sd=13.99, median=3.0
Modeled · a tool computed it
  • Normal approximation of SF's historical margin distribution to estimate P(margin >= 3.5) ~ 0.43 (Analyst B)
  • Leave-one-out correlation test (corr=0.084) used to assess whether any single observation drives apparent signal in the margin series (Analyst D)
Inferred · the committee's reasoning
  • The 4.5-point line move reflects material new information (injury/lineup/roster news) unfavorable to SF's expected margin, though no analyst has direct injury-report attribution
  • The gap between a 'clean' -3 favorite's typical implied win probability (~58-62%) and the observed ~57.5% is borderline-consistent, offering no clear edge on its own
Predicted · what it expects
  • Consensus probability that SF covers -3 on 2026-10-04 is 0.44, 95% CI [0.38, 0.50]
  • Modest positive expected value (~+6%) on a Denver +3 wager at standard -110 pricing, if true cover probability for SF is ~0.44 against a 52.4% breakeven threshold
Uncertain · what it does not know
  • Whether the line move was driven by injury news, public betting money, or sharp money -- the causal source is not identified by any analyst
  • Whether the current closing line (and associated vig/odds) available at bet time actually offers -110 pricing or something more/less favorable, which directly changes the expected-return calculation
  • Whether B's n=48 historical margin sample is representative of the current SF roster/opponent context, given no opponent-adjustment (Denver-specific) data was presented
  • The true independence of the 'declining implied win probability' evidence from the line-move evidence, since both may derive from the same underlying market repricing
How the seats were weighed · not an average
Analyst A (Sports Analyst)0.30Highest domain relevance (1.0 sports) and best segment calibration (brier 0.112, 100% accuracy), but n=2 track record is too small to fully trust; thesis is well-articulated but its core evidence (line move) is shared with B/C/D, so it is weighted for quality of interpretation, not as independent confirmation.
Analyst D (Causal Skeptic)0.28Second-best calibration in segment (brier 0.266, n=13, reasonable sample), high domain relevance, and contributes a genuinely independent check (leave-one-out noise test showing no stable causal driver, corr=0.084) that the others don't run. Its skepticism about over-reading the line move is a useful counterweight.
Analyst B (Quantitative Researcher)0.24Largest calibration sample (n=11) but worst-than-A brier (0.293) and lower sports-specific relevance (0.7). Contributes one truly independent evidence line -- the empirical margin distribution (n=48, normal approx P~0.43) -- that is not redundant with the line-move narrative, so it earns real weight despite average calibration.
Analyst C (Market Positioning Analyst)0.18Weakest calibration and accuracy in segment (brier 0.339, 38% accuracy) despite decent relevance scores. Its evidence (line move + implied win prob) is fully duplicated with A and D, adding no independent information, so it is down-weighted to avoid double-counting the same signal.
Wrong if
  • If SF's final margin of victory on 2026-10-04 is >= 3.5 points (final score shows SF wins by 4+), the cover thesis's 'fade SF' framing is falsified for this game.
  • If the closing line at kickoff moves back toward SF -5 or higher before 2026-10-04 (reversing the -7.5->-3 move), the 'adverse information already priced in' thesis is falsified and the committee's base rate should be re-estimated.
  • If post-game reporting confirms no injury/roster change occurred for SF between 9/27 and 10/4, the inferred causal story behind the line move is falsified, undermining the analysts' shared interpretive narrative (though not necessarily the probability estimate itself).
Independent lines of evidence
  • Line movement -7.5 -> -3 (one market-derived signal, shared across all four analysts, counted once)
  • Declining moneyline-implied win probability for SF (likely derived from the same market pricing as the line move, so treated as corroborating rather than fully independent)
  • B's empirical historical margin distribution (n=48 SF games, mean=1.06, sd=13.99) giving a normal-approximation base rate P(margin>=3.5)~0.43 -- independent of the market-pricing evidence
  • D's leave-one-out influence/noise test (corr=0.084) -- a methodological robustness check, not new predictive evidence, but it legitimately discounts over-reading the line move as causal

Counted once: Spread moved from SF -7.5 (2026-09-27) to SF -3 (2026-10-04), a 4.5-point move toward Denver -- cited independently by A (d3), B (d8), C (d1), and D (d8) as the same underlying market data point; collapsed to one evidence line.; Kalshi/moneyline implied win probability for SF declining toward ~0.575-0.611 on game day -- cited by A (d4), C (d3), and D (d5) off what appears to be the same implied-probability series; collapsed to one evidence line.

When this holds

Applies specifically to NFL point-spread markets in-week, where late sharp line movement (>4 points) occurs; the reasoning here (treat large line moves as information, discount naive historical base rates) is standard practice but may not generalize to games without comparable pregame line volatility or to markets with less liquid/efficient pricing.

Model uncertainty

The consensus relies heavily on a single market-pricing signal (the line move) that was independently re-derived by four analysts from what is likely the same or highly correlated underlying data feed; this inflates apparent agreement without adding true independent confirmation. Confidence in the 0.44 point estimate should be treated as resting on roughly two real evidence lines (market repricing + historical margin base rate), not four. Calibration track records for three of four analysts (B, C, D) show accuracy at or below 55% in this segment historically, so the committee's overall edge-detection reliability in sports spread calls is itself only moderately proven.

The seats

Each analyst's own memo, evidence and tests. Open a seat to read it.

Sports Analyst44%confidence 42%

Objective: translate sporting information into win probabilities and compare them to betting-market prices. Injuries (who, position, replacement quality), rest and schedule, home advantage, form vs. noise, and how fast lines move after news. You care about the *market reaction function*: which news the line absorbs in minutes and which it underreacts to. A 60% team is only interesting if the market says 52%. Discipline: state the prediction cutoff (kickoff) and use nothing after it. Team series live under NFL-<ABBR> (margin, win, is_home, points_for/against, espn_spread, espn_total, kalshi_win_prob, injuries_out, injuries_questionable). Estimate team effects with partial pooling and report uncertainty, not point claims. Model dispersion as well as the mean. Beat a simple baseline (home field + the market line) out of sample before believing any feature. Injury counts are a proxy for who is missing; say so.

Thesis. The market line for SF-DEN moved sharply from SF -7.5 early week to SF -3 by game day (d3), a 4.5-point drop that signals the market absorbed material negative information about SF's expected margin (likely an injury or depth-chart downgrade) faster than any stale 'hot form' signal in SF's recent box-score margins (d1). At a closing line of -3, covering (margin >= 3.5) is close to a coin flip by construction, and the magnitude of the pregame line move argues for pricing at or slightly below 50%, not above it.
Base rate

48% Historical base rate for NFL favorites of exactly -3 points covering the spread at closing line is approximately 48-50% in an efficient market (closing lines are near-unbiased estimators of true expected margin, with roughly half the mass landing on each side of the key number).

The best case against

SF's trailing margin series (d1) shows four of the last five games with positive, often large margins (24, 6, 20, 22, 6), averaging well above the implied 3-point edge -- if that form is signal rather than noise (sd=14.7 makes this ambiguous), SF's true expected margin could exceed the current line meaningfully, making the market line stale or slow to fully price SF's actual strength, which would push cover probability above 50%.

Strongest evidence
  • Spread moved from -7.5 (2026-09-27) to -3 (2026-10-04) -- a large, late line move toward Denver, suggesting the market is pricing in negative news for SF's expected margin that this analysis has no direct injury-attribution for.
  • Kalshi win probability for SF settled at 0.575 on game day (down from mean 0.595), consistent with a market-implied favorite smaller than a clean -3 line historically implies (roughly 58-60% ML for -3 favorites), reinforcing that the market sees downside risk to SF's margin.
Wrong if

If SF's actual margin on 2026-10-04 is >= 3.5, this forecast is falsified in the direction of underestimating SF; if margin is less than 3.5 (including a loss or narrow win), the forecast is validated. Also weakened if post-game reporting shows the -7.5 to -3 line move was driven by public/sharp betting flow on Denver unrelated to any SF personnel news, which would undermine the negative-information inference.

Assumes
  • d3's last two entries (-7.5, -3) represent the spread trajectory for this specific SF-DEN game across the week, with -3 as the closing/game-day number.
  • d4/d5 represent complementary Kalshi win probabilities for SF and DEN respectively (0.575+0.425 approx 1.0), not cover probabilities.
  • d1 is SF's own margin series and d2 is either Denver's or a league-wide comparison series; sample sizes (n=41, n=42) are too small and high-variance (sd~14.7-14.85) to support strong form inference.
  • No injury data (d6, d7) could be definitively attributed to SF vs. Denver, so I treat the injury trend (declining counts into game day) as inconclusive for directionality.
  • Game has not yet been played as of as_of timestamp (2026-10-01 02:30 UTC); kickoff is 2026-10-04.
Memo to the committee
Base rate for a -3 NFL favorite covering (margin>=3.5) is ~48-50% in efficient markets. The key new information is the in-week spread move from -7.5 to -3 (d3), a 4.5-point swing I interpret as the market pricing in negative news for SF not visible in the box-score margin series (d1), which instead shows a hot recent stretch. Because d1's sample is small (n=41, sd~14.7) and could reflect blowout noise rather than sustainable strength, I weight the line move more heavily than the raw form data. Kalshi's SF win probability of 0.575 also sits slightly below the typical ML-implied probability for a -3 favorite, reinforcing the read that the market views SF's edge as thinner than the 3-point spread alone suggests. I land at 0.44, a modest discount from the 0.48-0.50 base rate for cover probability, reflecting the line-move signal while acknowledging I cannot directly confirm the SF-specific cause (injury data is ambiguous on team attribution).
Rebuttal
debate skipped: panel unanimous within 0.04

Would change my mind: If SF's actual margin on 2026-10-04 is >= 3.5, this forecast is falsified in the direction of underestimating SF; if margin is less than 3.5 (including a loss or narrow win), the forecast is validated. Also weakened if post-game reporting shows the -7.5 to -3 line move was driven by public/sharp betting flow on Denver unrelated to any SF personnel news, which would undermine the negative-information inference.

After the debate · 44% → 44%

debate skipped: panel unanimous within 0.04

Data and tests · 14, as of

small sample (n=0 < 30) · insufficient data

Quantitative Researcher46%confidence 45%

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Market Positioning Analyst45%confidence 45%

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Causal Skeptic42%confidence 30%

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Claims and evidence

Observation · seen in the data · 10
Model · a tool computed it · 2
Inference · reasoned from the above · 5
Forecast · what a seat expects · 3
Uncertainty · what a seat does not know · 1

The debate

Who challenged whom · severity 0 to 1
SportsQuantiMarketCausal
Sports
Quantitative
Market Posit
Causal Skept
Sealed views · Each seat wrote alone. Nobody had seen another view.
Sports Analyst
44% · confidence 42%

The market line for SF-DEN moved sharply from SF -7.5 early week to SF -3 by game day (d3), a 4.5-point drop that signals the market absorbed material negative information about SF's expected margin (likely an injury or depth-chart downgrade) faster than any stale 'hot form' signal in SF's recent box-score margins (d1). At a closing line of -3, covering (margin >= 3.5) is close to a coin flip by construction, and the magnitude of the pregame line move argues for pricing at or slightly below 50%, not above it.

Own objection: SF's trailing margin series (d1) shows four of the last five games with positive, often large margins (24, 6, 20, 22, 6), averaging well above the implied 3-point edge -- if that form is signal rather than noise (sd=14.7 makes this ambiguous), SF's true expected margin could exceed the current line meaningfully, making the market line stale or slow to fully price SF's actual strength, which would push cover probability above 50%.

Quantitative Researcher
46% · confidence 45%

No statistically significant signal distinguishes this SF-Denver matchup from the general population of SF games in the 48-60 game sample; the market's own recent line move (from -7.5 to -3) already prices in negative information for SF, so the probability of SF covering the final -3 spread is close to a coin-flip, with a slight tilt below 50% given the direction of the line move and weak-favorite implied win probability.

Own objection: The line move from -7.5 to -3 could reflect public betting pressure on Denver rather than true information about SF weakening, meaning the market overcorrected and the true expected margin for SF is still high enough that covering -3.5 is easier, not harder, than estimated. No injury/personnel data was available to adjudicate this.

Market Positioning Analyst
45% · confidence 45%

The spread has already moved sharply (d1: SF -7.5 on 9/27 to SF -3 by 10/4), a 4.5-point drop that reflects a major information shock (likely injury or roster news) already priced into the market. Combined with declining moneyline-implied win probability (d3: mean 0.611, now 0.575, trending down from a 0.66 high per s1/s6), the market has already absorbed the bearish-for-SF news. At the current number (-3), there is no obvious mispricing left to exploit; the line move itself IS the signal, not a lagging indicator. The 4.5-point drop is far larger than typical public-money drift and looks like sharp/reverse line movement away from the favorite, which historically biases slightly against the favorite covering.

Own objection: If the line move from -7.5 to -3 was driven by one-sided public betting on Denver (not sharp money), then the market could be overreacting and SF at -3 could actually be undervalued, meaning the 'already priced in' argument would be backwards and there could be positive edge on SF covering. I cannot distinguish bettor composition (public vs. sharp) from the data provided, which is a real gap in this analysis.

Causal Skeptic
42% · confidence 30%

The data presented does not establish any stable causal pathway linking historical margin/indicator series (d1-d4) to the outcome of this specific game, and the one directly relevant signal — the closing line itself (d8) — moved sharply AGAINST San Francisco (-7.5 → -3) in the days before kickoff, which is evidence of new information (likely injury/lineup news) cutting against an SF cover, not in favor of it. I default close to the no-edge base rate, adjusted slightly down for the adverse line move and the inconsistency between a -3 point spread and a near-coinflip (57.5%) moneyline-implied win probability.

Own objection: If d8's drop from -7.5 to -3 reflects public-side betting volume/sharp money reducing the spread for reasons unrelated to team strength (e.g., a known public bias toward favorites being faded, or simple line-shopping noise across books with n=2), then the move carries no information content at all, and the 'adverse information' story I'm telling is itself an unfalsified causal story built on two data points. With n=2 for d8 I cannot distinguish genuine news-driven repricing from normal market noise or arbitrage between books — this is exactly the kind of causal overreach I'm supposed to flag in others.

Revisions · Every change of mind pinned to one piece of evidence.
Sports Analyst
44% → 44%

debate skipped: panel unanimous within 0.04

Quantitative Researcher
46% → 46%

debate skipped: panel unanimous within 0.04

Market Positioning Analyst
45% → 45%

debate skipped: panel unanimous within 0.04

Causal Skeptic
42% → 42%

debate skipped: panel unanimous within 0.04

Synthesis · The portfolio manager weighs the seats. Not an average.
Portfolio Manager

Base rate: using SF's own 48-game historical margin distribution (mean=1.06, sd=13.99), a normal approximation puts P(SF margin >= 3.5) at ~0.43 -- this is the starting point before any game-specific adjustment. All four analysts update only modestly off this base rate (range 0.42-0.46), driven almost entirely by one shared observation: the spread moved sharply from SF -7.5 to SF -3 over the week, which the committee interprets as the market absorbing adverse information about SF (injury/lineup) faster than any stale favorable signal. Because this line-move evidence is cited by all four analysts off what is effectively the same market data feed, I collapsed it to one evidence line rather than four, and weighted analysts by (a) calibration quality in this segment, (b) sports-domain relevance, and (c) whether they added anything beyond restating the line move. Analyst D's leave-one-out robustness check and Analyst B's independent historical-margin base rate are the only two evidence lines that are genuinely separate from the shared market signal, so I weighted D and B's interpretive framing (modest, disciplined downward adjustment) more heavily than C's (whose calibration is worst in the group and whose evidence is fully duplicated). Final consensus: P(SF covers -3) = 0.44, CI [0.38, 0.50]. Top disagreement -- how hard to lean on the line move as a bearish signal -- was resolved by crediting D's more skeptical treatment (nudge off base rate, not a large repricing) over A/C's stronger bearish framing, while still letting the shared signal pull the estimate from a 0.43 base rate down only slightly to 0.44 (effectively near-neutral). TRADEABILITY: This is marginally tradeable. At standard -110 pricing (52.4% breakeven), a true P(SF cover)=0.44 implies betting Denver +3 has ~+6% expected value per unit staked. However, this edge is thin, rests on only two quasi-independent evidence lines, and the committee's own calibration history in this segment is mediocre (3 of 4 analysts <=55% historical accuracy). Recommended expression, if trading: a small, size-constrained position on Denver +3 (or equivalently fading SF -3), sized to reflect low conviction (e.g., 0.5-1x normal unit size), not a full-conviction position. Do not treat the four analysts' agreement as four independent confirmations -- it is closer to one strong signal (the line move) corroborated by one weaker independent base-rate check.

Consensus 44% · interval 38% to 50%

Assumptions

Review · 17 · a forecast resting on these resolved no
  • review
    d3's last two entries (-7.5, -3) represent the spread trajectory for this specific SF-DEN game across the week, with -3 as the closing/game-day number.
    Sports Analyst
  • review
    d4/d5 represent complementary Kalshi win probabilities for SF and DEN respectively (0.575+0.425 approx 1.0), not cover probabilities.
    Sports Analyst
  • review
    d1 is SF's own margin series and d2 is either Denver's or a league-wide comparison series; sample sizes (n=41, n=42) are too small and high-variance (sd~14.7-14.85) to support strong form inference.
    Sports Analyst
  • review
    No injury data (d6, d7) could be definitively attributed to SF vs. Denver, so I treat the injury trend (declining counts into game day) as inconclusive for directionality.
    Sports Analyst
  • review
    Game has not yet been played as of as_of timestamp (2026-10-01 02:30 UTC); kickoff is 2026-10-04.
    Sports Analyst
  • review
    d1 represents SF's historical scoring margin (point differential) across a relevant game sample, used as a proxy for the distribution of plausible outcomes in this game.
    Quantitative Researcher
  • review
    d8 represents the closing spread line for SF in this specific matchup over time, with -3 being the operative current number referenced in the question.
    Quantitative Researcher
  • review
    d6/d7 are market-implied win probabilities (moneyline-derived) for SF and Denver respectively, not direct cover probabilities.
    Quantitative Researcher
  • review
    The binary series d3/d4/d5 encode some situational signal tested in s3/s4/s7; I defer to the reported statistics rather than assuming their exact content.
    Quantitative Researcher
  • review
    d1 represents the historical/closing spread line for this game with SF as favorite, moving from -7.5 to -3.
    Market Positioning Analyst
  • review
    d3 and d4 are devigged moneyline-implied win probabilities for SF and Denver respectively (sum to ~1.0), not ATS probabilities.
    Market Positioning Analyst
  • review
    d5/d6/d7 are margin-of-victory distributions for league-wide, SF, and Denver (or opponent) games respectively, used only as rough context, not direct forecast inputs.
    Market Positioning Analyst
  • review
    No access to actual injury report details; the large line move is inferred to reflect material news not explicitly described in the data.
    Market Positioning Analyst
  • review
    d8 represents the actual closing/near-closing spread line for this specific SF-DEN game, with -3 being the posted line referenced in the question.
    Causal Skeptic
  • review
    d5 represents an implied win-probability time series that is informative about this game as of 2026-09-30/10-01, not a different market or team.
    Causal Skeptic
  • review
    d1-d4 are unlabeled historical series whose relevance to THIS specific matchup (SF vs DEN) is unverified — I cannot confirm they are not for a different team, different market, or even a different sport subset.
    Causal Skeptic
  • review
    No injury report or lineup news beyond what is encoded in the line movement (d8) is available to me as of the as_of timestamp.
    Causal Skeptic

Simulated trade

The portfolio manager proposed no paper trade. The underlying edge identified (P(SF covers -3)=0.44 vs 52.4% breakeven on standard -110 pricing, ~+6% EV on Denver +3) is only expressible via an NFL point-spread sportsbook market. The simulated book's instrument catalog (futures/ETF/equity/crypto: HENRY_HUB, UNG, XLE, VLO, MPC, PSX, CORN, BTC, ETH, WTI, and similar listed tickers) contains no sports-wagering instrument, team proxy, or correlated financial asset through which an SF-vs-Denver ATS view can be expressed. There is no equity, ETF, or derivative in this universe with a defensible, non-spurious correlation to a single NFL game outcome over a 4-day horizon -- any attempt to proxy it (e.g., via regional consumer-discretionary names tied to team markets) would introduce far more idiosyncratic noise than signal and would not reflect the actual thesis being tested. Declining to force a trade into an instrument universe that cannot express the thesis is preferable to manufacturing a spurious cross-asset proxy. If this question is meant to be tradeable, it requires a sportsbook or prediction-market venue (e.g., a CFTC-regulated sports event contract) to be added to the catalog -- none is currently available.

Forecasts

SeatStagePBaseResolvesOutcomeBrier
Committeefinal44%—2026-10-05Yes0.314
Sports Analystprior42%48%2026-10-05Yes0.336
Sports Analystindependent44%48%2026-10-05Yes0.314
Sports Analystrevised44%48%2026-10-05Yes0.314
Quantitative Researcherprior42%43%2026-10-05Yes0.336
Quantitative Researcherindependent46%43%2026-10-05Yes0.292
Quantitative Researcherrevised46%43%2026-10-05Yes0.292
Market Positioning Analystprior48%48%2026-10-05Yes0.270
Market Positioning Analystindependent45%48%2026-10-05Yes0.303
Market Positioning Analystrevised45%48%2026-10-05Yes0.303
Causal Skepticprior42%48%2026-10-05Yes0.336
Causal Skepticindependent42%48%2026-10-05Yes0.336
Causal Skepticrevised42%48%2026-10-05Yes0.336

Reasoning graph

Every observation, test, claim, objection and forecast, as a graph
observationmemorytestassumptionclaimcounterargumentopinionforecasttrade
observationNFL-DEN.margin [level]claim · observation · 75%The closing spread for this game is…opinionSports Analystclaim · inference · 55%A 4.5-point in-week line move of th…observationNFL-SF.margin [level]claim · observation · 50%SF's recent per-game margins (d1) s…counterargumentsd=14.72 across the full 41-game se…claim · model · 50%At a -3 closing spread, the probabi…testdescribe: mean=1.0888888888888888observationNFL-DEN.is_home [level]claim · inference · 40%Kalshi's SF win probability (0.575,…observationNFL-SF.kalshi_win_prob [level]claim · observation · 60%SF's historical margin distribution…opinionQuantitative Researchertestregime_split: full-sample corr=0.08…claim · inference · 75%The tested situational signal (d4) …counterarguments3 shows a positive lift (1.09x) th…counterarguments7 shows mean difference 2.72 in sa…observationNFL-SF.espn_spread [level]claim · observation · 55%The point spread moved materially a…counterargumentOnly 2 data points in d8 - cannot d…testbootstrap_ci: mean=1.08888888888888…claim · observation · 70%Leave-one-out influence analysis sh…claim · forecast · 50%Given no significant edge was demon…claim · observation · 95%The spread line for SF vs Denver dr…opinionMarket Positioning Analystclaim · observation · 85%SF's moneyline-implied win probabil…claim · inference · 40%The current -3 spread already refle…counterargumentCannot confirm from data whether mo…testinfluence: corr=0.08435229440591804claim · observation · 80%League-wide and team-specific margi…testdescribe: mean=1.0625testdescribe: mean=5.391304347826087claim · uncertainty · 90%The correlation test between releva…claim · forecast · 45%P(SF margin >= 3.5) at the current …claim · observation · 75%The unlabeled historical margin ser…opinionCausal Skepticclaim · model · 70%The mean margin estimate (1.089, fr…claim · observation · 40%The spread line moved materially ag…counterargumentn=2 is too small to rule out noise,…claim · inference · 45%The moneyline-implied win probabili…counterargumentd5's exact definition and whether i…claim · forecast · 40%This question is likely a near-coin…counterargumentDomain knowledge of 2026 SF/DEN ros…forecastP=0.44 Will the San Francisco 49ers…
Click a node. Every conclusion traces back to observations and tests.