@buzzr/dfs-engine

Pure-functional DFS prop grading, payout math, stat normalization, and policy-aware settlement for DFS pick'em apps. PrizePicks is an experimental, partially verified compatibility profile; Underdog is experimental and unverified. These independent profiles are not official operator rules engines. The package also supports strict settlement inputs, structured validation, and custom book policies without forking. Drop-in TypeScript, zero runtime dependencies, ESM + CJS + .d.ts shipped.

Sports covered: NBA, WNBA, NCAAM/W, NFL, MLB, NHL, EPL, MLS, La Liga, NWSL, UEFA Champions League. ~70 props.

Install

npm install @buzzr/dfs-engine
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Why this exists

If you're building a DFS-adjacent tool — a bet tracker, parlay analyzer, EV calculator, social betting app, fantasy coaching tool — you eventually need code that answers:

• Did this leg hit? Given a player's actual stat and a slip line, decide won / lost / push.
• What does the slip pay out? Given the play type (Power / Flex / Standard), the pick count, the hits, and any boost, compute the multiplier and the withdrawable-vs-bonus split.
• What happens when a player doesn't play? Apply a selected compatibility or custom policy, preserve the decision in the audit trail, and surface uncertainty instead of inventing an operator ruling.
• What stat goes into a Pts + Rebs + Asts leg? Or Pass + Rush + Rec Yds? Or Hitter FS?

There's no good open-source TypeScript package for any of this. Everyone reinvents it from scratch, usually wrong. This package was extracted from Buzzr and is maintained as an independent, testable engine. Pure functions, strict runtime validation, and a release suite covering 300+ settlement tests keep code behavior auditable without claiming that an operator will issue the same ruling.

Quickstart

import { gradeLegFromActual } from '@buzzr/dfs-engine';

// Player scored 28 against a line of 24.5 over → leg won.
gradeLegFromActual(24.5, 'over', 28);  // 'won'

// Same line, only 20 → leg lost.
gradeLegFromActual(24.5, 'over', 20);  // 'lost'

// Game hasn't ended yet (no stat available) → leg pending.
gradeLegFromActual(24.5, 'over', null); // 'pending'
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v4 Settlement OS

For full-entry settlement, create an isolated engine. Each engine owns its own book policies, payout overrides, league adapters, providers, clock, and audit metadata, so tests, apps, and plugins do not mutate a global registry.

import { createDfsEngine, defineBookPolicy, definePayoutTable } from '@buzzr/dfs-engine';

const myBook = defineBookPolicy({
  id: 'my-book',
  displayName: 'My Book',
  version: '2026-05',
  effectiveFrom: '2026-05-01',
  status: 'stable',
  sources: [{ label: 'Internal rules memo' }],
  playTypes: [
    {
      id: 'all-in',
      displayName: 'All-In',
      payoutModel: 'fixed-table',
      pickCount: { min: 2, max: 4 },
      allOrNothing: true,
    },
  ],
  tiePolicy: { type: 'push' },
  dnpPolicy: { type: 'remove_leg', voidIfNoSurvivors: true },
  pushPolicy: { type: 'remove_leg', refundIfNoSurvivors: true },
  payoutSplit: { type: 'all_withdrawable' },
  validation: { duplicatePlayers: 'error' },
});

const engine = createDfsEngine({
  bookPolicies: [myBook],
  payoutTables: [
    definePayoutTable({
      bookId: 'my-book',
      playTypeId: 'all-in',
      effectiveFrom: '2026-05-01',
      entries: [{ pickCount: 2, hits: 2, multiplier: 4 }],
    }),
  ],
});

const result = await engine.settleEntry(
  {
    entryId: 'slip-1',
    bookId: 'my-book',
    playTypeId: 'all-in',
    stake: 10,
    displayedMultiplier: 4,
    legs: [
      {
        legId: 'a',
        playerName: 'A. Example',
        playerId: 'athlete-1',
        league: 'NBA',
        propType: 'Points',
        line: 24.5,
        direction: 'over',
        actual: null,
        status: 'pending',
        gameDate: '2026-05-07',
      },
      {
        legId: 'b',
        playerName: 'B. Example',
        league: 'NBA',
        propType: 'Rebounds',
        line: 7.5,
        direction: 'over',
        actual: null,
        status: 'pending',
      },
    ],
  },
  { actualsByLegId: { a: 28, b: 9 } },
);

console.log(result.status, result.payout, result.policyVersion, result.explanationCodes);
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Legacy app / playType inputs are intentionally not the main v4 model. Use adaptV2EntryInput(...) during migration:

import { adaptV2EntryInput } from '@buzzr/dfs-engine';

const v4Input = adaptV2EntryInput({
  entryId: 'legacy-slip',
  app: 'underdog',
  playType: 'underdog_flex',
  stake: 10,
  displayedMultiplier: 11.5,
  legs: [],
});
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Optional SDK packages:

• @buzzr/dfs-provider-espn wraps your ESPN-shaped loader as a stat provider.
• @buzzr/dfs-testkit ships fixture builders and mock providers for settlement tests.

Operator compatibility contract

The operator-named built-ins are versioned compatibility profiles, not affiliated or endorsed implementations:

• PrizePicks: status: "experimental" with verification.status: "partial". Standard Player Pick references were reviewed on 2026-07-16 from PrizePicks Payouts, PrizePicks Potential Outcomes, and DNPs, Reboots, and Ties. For a 2-pick Power entry, one correct pick plus one tie pays 1.5x, one incorrect pick plus one tie loses, and a DNP below the two-pick minimum receives a refund. Other settlement behavior and variable lineup-specific payouts remain incomplete.
• Underdog: status: "experimental" with verification.status: "unverified". The Underdog Sports Legal Center is recorded as the rules entrypoint; current payout and settlement values in the compatibility snapshot have not been verified.

The displayed lineup terms are authoritative. Record placedAt so the engine can select an effective-dated payout table, inspect policyStatus, policyVerification, payoutTable, confidence, sourceRefs, and explanationCodes on every engine-produced result, and obtain explicit operator rulings for DNPs, reboots, ties, rescues, voids, and corrections. The three policy metadata properties are optional in the public DfsSettlementResult type so legacy external result objects remain source-compatible, but createDfsEngine() always populates them at runtime.

const policies = createDfsEngine().getBookPolicies();
// Immutable snapshots with status, verification, sources, and play types.
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createDfsEngine() returns DfsEngineWithPolicySnapshots, which extends the legacy DfsEngine interface with getBookPolicies(). Existing external DfsEngine implementations do not need to add the discovery method.

Draft fixtures are source metadata for future work. They are not registered by createDfsEngine() and cannot settle entries unless a caller deliberately supplies a complete custom implementation.

Examples

1. Look up the payout for a pick count + hit count

import { lookupStandardMultiplier } from '@buzzr/dfs-engine';

// PrizePicks compatibility table effective 2026-07-02: 5-pick Power, 5/5 → 20×.
lookupStandardMultiplier({ app: 'prizepicks', playType: 'power', pickCount: 5, hits: 5 });
// → 20

// PrizePicks compatibility table effective 2026-07-02: 6-pick Flex, 5/6 → 2×.
lookupStandardMultiplier({ app: 'prizepicks', playType: 'flex', pickCount: 6, hits: 5 });
// → 2

// Unverified Underdog compatibility snapshot: 8-pick Standard, 8/8 → 100×.
lookupStandardMultiplier({ app: 'underdog', playType: 'underdog_standard', pickCount: 8, hits: 8 });
// → 100
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2. Recompute the multiplier after a DNP

import { recalcMultiplierAfterDnp } from '@buzzr/dfs-engine';

// Under the selected compatibility profile, remove one leg from a 6-pick
// Power entry and scale the slip's displayed multiplier proportionally.
const { newMultiplier } = recalcMultiplierAfterDnp({
  app: 'prizepicks',
  playType: 'power',
  originalPickCount: 6,
  survivingPickCount: 5,
  survivingHits: 5,
  originalMultiplier: 37.5,   // slip-displayed multiplier (post-boost)
});
// newMultiplier ≈ 20 (37.5 × 20/37.5)
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recalcMultiplierAfterDnp returns { newMultiplier, usedFallback }. usedFallback is true when the payout table doesn't cover the (app, playType, pickCount, hits) tuple — caller should warn the user that the recompute couldn't be verified.

3. Extract a stat from a gamelog entry

The grader needs a numeric value to compare against the line. extractStatForProp handles the prop-string → stat-value mapping across leagues:

import { extractStatForProp } from '@buzzr/dfs-engine';

const entry = {
  date: '2026-05-04',
  minutes: '38:21',
  points: '28',
  rebounds: '4',
  assists: '7',
  steals: '1',
  blocks: '0',
  turnovers: '2',
  threeP: '3',
};

extractStatForProp('Points', 'NBA', entry, 'prizepicks');          // 28
extractStatForProp('Pts+Rebs+Asts', 'NBA', entry, 'prizepicks');   // 39
extractStatForProp('3-Pointers Made', 'NBA', entry, 'prizepicks'); // 3
extractStatForProp('Rebounds', 'NBA', entry, 'prizepicks');        // 4
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Slip-text aliases are normalized — "3PT Made", "3-pt made", "3ptm", "3pm", "threes" all resolve to '3-Pointers Made'. v0.3 adds 14 new props (Double-Double, Triple-Double, Pts+Stls, Longest Reception/Rush/Pass, MLB Singles/Doubles/Triples/Runs, Pitching Outs, NHL Plus/Minus). See DFS_PROP_TYPE_KEYS for the full canonical list (60+ props across NBA / WNBA / NCAAM/W / NFL / MLB / NHL).

4. Grade a full entry end-to-end

gradeDfsBetFromGraded rolls per-leg statuses into a bet-level result with the boost split:

import { gradeDfsBetFromGraded } from '@buzzr/dfs-engine';

const result = gradeDfsBetFromGraded({
  app: 'underdog',
  playType: 'underdog_flex',
  legs: [
    { legId: 'a', legStatus: 'won',  /* ...DfsBetLeg fields */ },
    { legId: 'b', legStatus: 'won',  /* ... */ },
    { legId: 'c', legStatus: 'lost', /* ... */ },
    { legId: 'd', legStatus: 'won',  /* ... */ },
    { legId: 'e', legStatus: 'won',  /* ... */ },
  ],
  stake: 10,
  displayedMultiplier: 11.5,      // boosted from base 10×
  baseMultiplier: 10,
  profitBoostPct: null,
});
// Unverified Underdog compatibility snapshot: 4-of-5 Flex → 2×,
// scaled by displayed/base ratio.
// → { status: 'won', effectiveMultiplier: 2.3, totalPayout: 23,
//     withdrawablePayout: 20, bonusPayout: 3 }
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Pending semantics: if any surviving leg is legStatus: 'pending', the whole bet returns status: 'pending' — you can call this every time a leg's actualValue updates without risk of premature settlement.

Add your own sport

Built-in coverage is NBA, WNBA, NCAAM/W, NFL, MLB, NHL. The plugin registry lets you add a sport without forking:

import {
  registerLeague,
  extractStatForProp,
  type AdapterTable,
} from '@buzzr/dfs-engine';

const SOCCER_ADAPTERS: AdapterTable = {
  Goals: (entry) => parseInt(entry.points, 10) || null,
  Assists: (entry) => parseInt(entry.rebounds, 10) || null,
};

registerLeague('EPL', SOCCER_ADAPTERS);
registerLeague('MLS', SOCCER_ADAPTERS);

extractStatForProp('Goals', 'EPL', someEntry, 'prizepicks'); // your value
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getRegisteredLeagues() returns the current list; unregisterLeague(name) removes one (useful in tests).

Explained variants for richer error handling

When null isn't specific enough, use the *Explained variants — they return a discriminated union with a reason code so you can show the user why a leg can't be graded yet:

import {
  extractStatForPropExplained,
  gradeLegFromActualExplained,
} from '@buzzr/dfs-engine';

const stat = extractStatForPropExplained('Yellow Cards', 'EPL', entry, 'prizepicks');
if (!stat.ok) {
  console.log(stat.reason); // 'unknown_prop' | 'unsupported_league' | 'prop_not_supported_for_league' | 'adapter_returned_null'
  console.log(stat.detail); // human-readable context
}

const grade = gradeLegFromActualExplained(24.5, 'over', NaN);
if (!grade.ok) {
  console.log(grade.reason); // 'pending' | 'unparseable_actual'
}
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What's in here

The PlayerGameLogEntryShape the adapters consume is intentionally minimal — define your own gamelog rows that satisfy the shape ({ date, minutes, points, ... }) and pipe them in.

See CHANGELOG.md for what's new in each release. Looking to contribute? Start at CONTRIBUTING.md. Copy-paste-runnable demos live in examples/README.md. Generated API docs: buzzr-app.github.io/dfs-engine.

Performance

Pure functions, zero deps, sub-microsecond on a Mac M-series (from npm run bench):

Floor numbers — every operation completes in microseconds. You will not be CPU-bound by this library.

Stability

Starting at 1.0, the public API is frozen. Breaking changes only at major versions. New sports, props, and *Explained failure reasons can ship in minor releases without breaking consumers. See CHANGELOG.md for the full stability contract.

Validating untrusted inputs

When an LLM, webhook, or cross-process source hands you a slip leg or gamelog entry, run it through the validator before grading:

import {
  assertValidDfsEntryInput,
  validateDfsEntryInput,
  validatePlayerGameLogEntryShape,
} from '@buzzr/dfs-engine';

const v = validatePlayerGameLogEntryShape(maybeEntry);
if (!v.ok) {
  console.error('Bad gamelog entry:', v.errors);
  return;
}
// v.value is now typed as PlayerGameLogEntryShape

const entry = validateDfsEntryInput(maybeSettlementEntry);
if (!entry.ok) {
  console.error(entry.errors.map((issue) => [issue.path, issue.code]));
  return;
}

assertValidDfsEntryInput(maybeSettlementEntry);
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v4 settlement inputs are canonical: use actual on DfsLegInput, status for leg state, actualsByLegId for settlement context actuals, and legStatusesByLegId for status overrides. Legacy stat, legStatus, statsByLegId, and legStatusByLegId are rejected by the strict validators.

Status & caveats

• Compatibility status is part of the result. PrizePicks is experimental and partially verified; Underdog is experimental and unverified. Neither profile certifies a current operator ruling.
• PrizePicks standard references were reviewed 2026-07-16. The current standard table is effective 2026-07-02, and older effective-dated tables remain for historical entries. Recheck the linked first-party sources before relying on a later entry.
• Displayed slip terms are authoritative. Tables are compatibility inputs and demotion-ratio baselines; variable, promotional, state-specific, and entry-specific terms may differ.
• Gamelog parsing is your problem. This package grades stats; it doesn't fetch them. Adapt ESPN, your own scraper, or a paid data feed to PlayerGameLogEntryShape upstream.
• Sport coverage: NBA / WNBA / NCAAM (basketball), NFL, MLB (batters + pitchers), NHL (skaters + goalies). Adding a sport means a new AdapterTable plus extending DfsPropTypeKey.

Origin

Extracted from Buzzr and maintained in this public monorepo. The mobile app currently vendors the 5.0.0 engine tarball; later public-repository changes require a deliberate app upgrade. Operator-named policy outputs remain compatibility estimates subject to the displayed entry terms and current operator ruling.

Compatibility and support

Node.js >= 22 is supported. Import the supported API from @buzzr/dfs-engine. Deep src/* and dist/* imports are unsupported. See the all-package API index and the generated root-export reference.

Report reproducible defects in GitHub Issues. Report vulnerabilities privately through SECURITY.md. The versioning and support policy defines the supported runtime and SemVer contract.

License

MIT © Sarvesh Chidambaram