brackt/app/routes/admin.sports-seasons.$id.golf-skills.tsx

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Add golf qualifying points simulator (Plackett-Luce Monte Carlo) (#223) * Add golf QP simulator with Plackett-Luce model, fixes #120 - New `participant_golf_skills` table (migration 0061) for SG: Total and per-major American odds per player/season - New `app/models/golf-skills.ts` with getGolfSkillsMap, getGolfSkillsForSeason, batchUpsertGolfSkills - Full `GolfSimulator` implementation replacing the TODO stub: Plackett-Luce ranking model (PL_BETA=1.5, FIELD_SIZE=156), 10k Monte Carlo iterations, awards QP by finishing position, ranks by total QP across all 4 majors - New admin route `sports-seasons/:id/golf-skills` with bulk CSV import, fuzzy name matching, per-player SG + per-major odds inputs; saves skills and auto-runs simulation on submit - Simulator dropdown on sport admin sorted alphabetically; renamed to "Golf Qualifying Points Monte Carlo" - Golf Skills button shown on sports season admin when simulator type is golf_qualifying_points - Extract normalizeName/diceCoefficient to shared `app/lib/fuzzy-match.ts`, removing duplication from surface-elo and golf-skills routes - Parallelize 4 DB queries in GolfSimulator.simulate() with Promise.all - O(1) field array removal via swap-to-end + pop (was O(N) splice) - Fix source tag: performance_model (not elo_simulation) for SG-based model - 23 unit tests covering americanToImplied, getMajorOddsKey, resolveSkill, simulateMajor, and Monte Carlo calibration properties Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix oxlint errors: no-non-null-assertion and eqeqeq Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-24 21:46:02 -07:00
import { Form, redirect, useLoaderData, useActionData, useNavigation, useFetcher } from 'react-router';
import type { Route } from './+types/admin.sports-seasons.$id.golf-skills';
import { logger } from '~/lib/logger';
import { findSportsSeasonById, updateSportsSeason } from '~/models/sports-season';
import { findParticipantsBySportsSeasonId, findParticipantByName, createParticipant } from '~/models/season-participant';
Add golf qualifying points simulator (Plackett-Luce Monte Carlo) (#223) * Add golf QP simulator with Plackett-Luce model, fixes #120 - New `participant_golf_skills` table (migration 0061) for SG: Total and per-major American odds per player/season - New `app/models/golf-skills.ts` with getGolfSkillsMap, getGolfSkillsForSeason, batchUpsertGolfSkills - Full `GolfSimulator` implementation replacing the TODO stub: Plackett-Luce ranking model (PL_BETA=1.5, FIELD_SIZE=156), 10k Monte Carlo iterations, awards QP by finishing position, ranks by total QP across all 4 majors - New admin route `sports-seasons/:id/golf-skills` with bulk CSV import, fuzzy name matching, per-player SG + per-major odds inputs; saves skills and auto-runs simulation on submit - Simulator dropdown on sport admin sorted alphabetically; renamed to "Golf Qualifying Points Monte Carlo" - Golf Skills button shown on sports season admin when simulator type is golf_qualifying_points - Extract normalizeName/diceCoefficient to shared `app/lib/fuzzy-match.ts`, removing duplication from surface-elo and golf-skills routes - Parallelize 4 DB queries in GolfSimulator.simulate() with Promise.all - O(1) field array removal via swap-to-end + pop (was O(N) splice) - Fix source tag: performance_model (not elo_simulation) for SG-based model - 23 unit tests covering americanToImplied, getMajorOddsKey, resolveSkill, simulateMajor, and Monte Carlo calibration properties Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix oxlint errors: no-non-null-assertion and eqeqeq Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-24 21:46:02 -07:00
import { batchUpsertParticipantEVs } from '~/models/participant-expected-value';
import { batchUpsertParticipantEvSnapshots } from '~/models/ev-snapshot';
import { getGolfSkillsForSeason, batchUpsertGolfSkills } from '~/models/golf-skills';
import { getSimulator, type SimulatorType } from '~/services/simulations/registry';
import { calculateEV, type ScoringRules } from '~/services/ev-calculator';
import { recalculateStandings } from '~/models/scoring-calculator';
import { database } from '~/database/context';
import * as schema from '~/database/schema';
import { eq } from 'drizzle-orm';
import { Button } from '~/components/ui/button';
import { Input } from '~/components/ui/input';
import { Label } from '~/components/ui/label';
import { Textarea } from '~/components/ui/textarea';
import {
Card,
CardContent,
CardDescription,
CardHeader,
CardTitle,
} from '~/components/ui/card';
import { useEffect, useRef, useState } from 'react';
import { Loader2, CheckCircle2, AlertCircle, UserPlus } from 'lucide-react';
import { normalizeName, diceCoefficient } from '~/lib/fuzzy-match';
const DEFAULT_SCORING_RULES: ScoringRules = {
pointsFor1st: 100,
pointsFor2nd: 70,
pointsFor3rd: 45,
pointsFor4th: 45,
pointsFor5th: 20,
pointsFor6th: 20,
pointsFor7th: 20,
pointsFor8th: 20,
};
export function meta({ data }: Route.MetaArgs): Route.MetaDescriptors {
return [{ title: `Golf Skills — ${data?.sportsSeason?.name ?? 'Sports Season'} - Brackt Admin` }];
}
export async function loader({ params }: Route.LoaderArgs) {
const sportsSeasonId = params.id;
const sportsSeason = await findSportsSeasonById(sportsSeasonId);
if (!sportsSeason) {
throw new Response('Sports season not found', { status: 404 });
}
const [participants, existingSkills] = await Promise.all([
findParticipantsBySportsSeasonId(sportsSeasonId),
getGolfSkillsForSeason(sportsSeasonId),
]);
const skillsMap: Record<
string,
{ sgTotal: string; datagolfRank: string; mastersOdds: string; usOpenOdds: string; openChampionshipOdds: string; pgaChampionshipOdds: string }
> = {};
for (const r of existingSkills) {
skillsMap[r.participantId] = {
sgTotal: r.sgTotal !== null ? String(r.sgTotal) : '',
datagolfRank: r.datagolfRank !== null ? String(r.datagolfRank) : '',
mastersOdds: r.mastersOdds !== null ? String(r.mastersOdds) : '',
usOpenOdds: r.usOpenOdds !== null ? String(r.usOpenOdds) : '',
openChampionshipOdds: r.openChampionshipOdds !== null ? String(r.openChampionshipOdds) : '',
pgaChampionshipOdds: r.pgaChampionshipOdds !== null ? String(r.pgaChampionshipOdds) : '',
};
}
return { sportsSeason, participants, skillsMap };
}
type ActionData =
| { intent: 'create-participant'; success: true; participant: { id: string; name: string } }
| { intent: 'create-participant'; success: false; message: string }
| { success?: boolean; message?: string };
export async function action({ request, params }: Route.ActionArgs) {
const sportsSeasonId = params.id;
const formData = await request.formData();
const intent = formData.get('intent');
if (intent === 'create-participant') {
const name = (formData.get('name') as string)?.trim();
if (!name) {
return { intent: 'create-participant', success: false, message: 'Name is required' } satisfies ActionData;
}
const existing = await findParticipantByName(sportsSeasonId, name);
if (existing) {
return { intent: 'create-participant', success: false, message: `"${name}" already exists in this season.` } satisfies ActionData;
}
Add golf qualifying points simulator (Plackett-Luce Monte Carlo) (#223) * Add golf QP simulator with Plackett-Luce model, fixes #120 - New `participant_golf_skills` table (migration 0061) for SG: Total and per-major American odds per player/season - New `app/models/golf-skills.ts` with getGolfSkillsMap, getGolfSkillsForSeason, batchUpsertGolfSkills - Full `GolfSimulator` implementation replacing the TODO stub: Plackett-Luce ranking model (PL_BETA=1.5, FIELD_SIZE=156), 10k Monte Carlo iterations, awards QP by finishing position, ranks by total QP across all 4 majors - New admin route `sports-seasons/:id/golf-skills` with bulk CSV import, fuzzy name matching, per-player SG + per-major odds inputs; saves skills and auto-runs simulation on submit - Simulator dropdown on sport admin sorted alphabetically; renamed to "Golf Qualifying Points Monte Carlo" - Golf Skills button shown on sports season admin when simulator type is golf_qualifying_points - Extract normalizeName/diceCoefficient to shared `app/lib/fuzzy-match.ts`, removing duplication from surface-elo and golf-skills routes - Parallelize 4 DB queries in GolfSimulator.simulate() with Promise.all - O(1) field array removal via swap-to-end + pop (was O(N) splice) - Fix source tag: performance_model (not elo_simulation) for SG-based model - 23 unit tests covering americanToImplied, getMajorOddsKey, resolveSkill, simulateMajor, and Monte Carlo calibration properties Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Fix oxlint errors: no-non-null-assertion and eqeqeq Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-24 21:46:02 -07:00
const participant = await createParticipant({ sportsSeasonId, name });
return {
intent: 'create-participant',
success: true,
participant: { id: participant.id, name: participant.name },
} satisfies ActionData;
}
const sportsSeason = await findSportsSeasonById(sportsSeasonId);
if (!sportsSeason) {
return { success: false, message: 'Sports season not found' };
}
if (!sportsSeason.sport?.simulatorType) {
return { success: false, message: 'This sport has no simulator type configured.' };
}
if (sportsSeason.simulationStatus === 'running') {
return { success: false, message: 'A simulation is already running. Please wait.' };
}
const participants = await findParticipantsBySportsSeasonId(sportsSeasonId);
// Parse golf skill fields: sgTotal_{id}, datagolfRank_{id}, mastersOdds_{id}, etc.
const skillInputs = participants
.map((p) => ({
participantId: p.id,
sportsSeasonId,
sgTotal: parseDecimalOrNull(formData.get(`sgTotal_${p.id}`) as string),
datagolfRank: parseIntOrNull(formData.get(`datagolfRank_${p.id}`) as string),
mastersOdds: parseIntOrNull(formData.get(`mastersOdds_${p.id}`) as string),
usOpenOdds: parseIntOrNull(formData.get(`usOpenOdds_${p.id}`) as string),
openChampionshipOdds: parseIntOrNull(formData.get(`openChampionshipOdds_${p.id}`) as string),
pgaChampionshipOdds: parseIntOrNull(formData.get(`pgaChampionshipOdds_${p.id}`) as string),
}))
.filter((r) =>
r.sgTotal !== null ||
r.datagolfRank !== null ||
r.mastersOdds !== null ||
r.usOpenOdds !== null ||
r.openChampionshipOdds !== null ||
r.pgaChampionshipOdds !== null
);
if (skillInputs.length === 0) {
return { success: false, message: 'Please enter at least one skill rating.' };
}
await batchUpsertGolfSkills(skillInputs);
// Auto-run simulation after saving
await updateSportsSeason(sportsSeasonId, { simulationStatus: 'running' });
try {
const simulator = getSimulator(sportsSeason.sport.simulatorType as SimulatorType);
const results = await simulator.simulate(sportsSeasonId);
if (results.length === 0) {
throw new Error('Simulation returned no results.');
}
const simulatedIds = new Set(results.map((r) => r.participantId));
const ZERO_PROBS = {
probFirst: 0, probSecond: 0, probThird: 0, probFourth: 0,
probFifth: 0, probSixth: 0, probSeventh: 0, probEighth: 0,
};
const evInputs = [
...results.map((r) => ({
participantId: r.participantId,
sportsSeasonId,
probabilities: r.probabilities,
scoringRules: DEFAULT_SCORING_RULES,
source: 'performance_model' as const,
})),
...participants
.filter((p) => !simulatedIds.has(p.id))
.map((p) => ({
participantId: p.id,
sportsSeasonId,
probabilities: ZERO_PROBS,
scoringRules: DEFAULT_SCORING_RULES,
source: 'performance_model' as const,
})),
];
await batchUpsertParticipantEVs(evInputs);
// Refresh projected points in team standings
const seasonSports = await database().query.seasonSports.findMany({
where: eq(schema.seasonSports.sportsSeasonId, sportsSeasonId),
});
await Promise.all(seasonSports.map(({ seasonId }) => recalculateStandings(seasonId)));
// EV snapshot
const today = new Date().toISOString().slice(0, 10);
await batchUpsertParticipantEvSnapshots(
results.map((r) => ({
participantId: r.participantId,
sportsSeasonId,
snapshotDate: today,
probFirst: r.probabilities.probFirst,
probSecond: r.probabilities.probSecond,
probThird: r.probabilities.probThird,
probFourth: r.probabilities.probFourth,
probFifth: r.probabilities.probFifth,
probSixth: r.probabilities.probSixth,
probSeventh: r.probabilities.probSeventh,
probEighth: r.probabilities.probEighth,
calculatedEV: calculateEV(r.probabilities, DEFAULT_SCORING_RULES),
source: r.source,
}))
);
await updateSportsSeason(sportsSeasonId, { simulationStatus: 'idle' });
} catch (error) {
await updateSportsSeason(sportsSeasonId, { simulationStatus: 'failed' });
logger.error('Error running golf simulation:', error);
return {
success: false,
message: error instanceof Error ? error.message : 'Simulation failed',
};
}
return redirect(`/admin/sports-seasons/${sportsSeasonId}/expected-values`);
}
function parseIntOrNull(val: string | null | undefined): number | null {
if (!val || val.trim() === '') return null;
const n = parseInt(val.trim(), 10);
return isNaN(n) ? null : n;
}
function parseDecimalOrNull(val: string | null | undefined): number | null {
if (!val || val.trim() === '') return null;
const n = parseFloat(val.trim());
return isNaN(n) ? null : n;
}
type SkillValues = Record<
string,
{ sgTotal: string; datagolfRank: string; mastersOdds: string; usOpenOdds: string; openChampionshipOdds: string; pgaChampionshipOdds: string }
>;
interface ParsedSkill {
sgTotal: number | null;
datagolfRank: number | null;
mastersOdds: number | null;
usOpenOdds: number | null;
openChampionshipOdds: number | null;
pgaChampionshipOdds: number | null;
}
interface MatchedItem extends ParsedSkill {
participantId: string;
name: string;
inputName: string;
}
interface Suggestion {
participantId: string;
name: string;
score: number;
}
interface UnmatchedItem extends ParsedSkill {
inputName: string;
suggestions: Suggestion[];
}
interface ParseResults {
matched: MatchedItem[];
unmatched: UnmatchedItem[];
}
type LocalParticipant = { id: string; name: string };
export default function AdminSportsSeasonGolfSkills() {
const { sportsSeason, participants: loaderParticipants, skillsMap } = useLoaderData<typeof loader>();
const actionData = useActionData<ActionData>();
const navigation = useNavigation();
const createFetcher = useFetcher<ActionData>();
const [localParticipants, setLocalParticipants] = useState<LocalParticipant[]>(loaderParticipants);
const [skillValues, setSkillValues] = useState<SkillValues>(() => {
const initial: SkillValues = {};
loaderParticipants.forEach((p) => {
const existing = skillsMap[p.id];
initial[p.id] = existing ?? {
sgTotal: '', datagolfRank: '', mastersOdds: '', usOpenOdds: '',
openChampionshipOdds: '', pgaChampionshipOdds: '',
};
});
return initial;
});
const [bulkText, setBulkText] = useState('');
const [parseResults, setParseResults] = useState<ParseResults | null>(null);
const pendingSkillsByName = useRef<Map<string, ParsedSkill>>(new Map());
useEffect(() => {
if (
createFetcher.state !== 'idle' ||
!createFetcher.data ||
!('intent' in createFetcher.data) ||
createFetcher.data.intent !== 'create-participant' ||
!createFetcher.data.success
) return;
const { participant } = createFetcher.data as Extract<ActionData, { intent: 'create-participant'; success: true }>;
setLocalParticipants((prev) => {
if (prev.some((p) => p.id === participant.id)) return prev;
return [...prev, participant];
});
const pending = pendingSkillsByName.current.get(participant.name);
if (pending) {
setSkillValues((prev) => ({
...prev,
[participant.id]: {
sgTotal: pending.sgTotal !== null ? String(pending.sgTotal) : '',
datagolfRank: pending.datagolfRank !== null ? String(pending.datagolfRank) : '',
mastersOdds: pending.mastersOdds !== null ? String(pending.mastersOdds) : '',
usOpenOdds: pending.usOpenOdds !== null ? String(pending.usOpenOdds) : '',
openChampionshipOdds: pending.openChampionshipOdds !== null ? String(pending.openChampionshipOdds) : '',
pgaChampionshipOdds: pending.pgaChampionshipOdds !== null ? String(pending.pgaChampionshipOdds) : '',
},
}));
pendingSkillsByName.current.delete(participant.name);
}
setParseResults((prev) => {
if (!prev) return prev;
return { ...prev, unmatched: prev.unmatched.filter((u) => u.inputName !== participant.name) };
});
}, [createFetcher.state, createFetcher.data]);
function findParticipantMatch(inputName: string, pool: LocalParticipant[]) {
const normalizedInput = normalizeName(inputName);
const normalized = pool.map((p) => ({ p, n: normalizeName(p.name) }));
const exact = normalized.find(({ n }) => n === normalizedInput);
if (exact) return exact.p;
const contains = normalized.find(({ n }) => n.includes(normalizedInput) || normalizedInput.includes(n));
if (contains) return contains.p;
const inputWords = normalizedInput.split(' ').filter((w) => w.length > 2);
const overlap = normalized.find(({ n }) => {
const pWords = n.split(' ').filter((w) => w.length > 2);
const shared = inputWords.filter((w) => pWords.includes(w));
return shared.length > 0 && shared.length >= Math.min(inputWords.length, pWords.length) * 0.5;
});
return overlap?.p ?? null;
}
function getFuzzySuggestions(inputName: string, pool: LocalParticipant[], exclude: Set<string>): Suggestion[] {
const normalizedInput = normalizeName(inputName);
return pool
.filter((p) => !exclude.has(p.id))
.map((p) => ({ participantId: p.id, name: p.name, score: diceCoefficient(normalizedInput, normalizeName(p.name)) }))
.filter((s) => s.score >= 0.3)
.toSorted((a, b) => b.score - a.score)
.slice(0, 3);
}
/**
* Parse bulk import text.
* Format (CSV, one per line): Player Name, SG_Total
* Optional additional columns: Player Name, SG_Total, Masters, USOpen, TheOpen, PGA
*/
function parseBulkText() {
const lines = bulkText.split('\n');
const matched: MatchedItem[] = [];
const unmatched: UnmatchedItem[] = [];
const seen = new Set<string>();
for (const line of lines) {
const trimmed = line.trim();
if (!trimmed) continue;
const parts = trimmed.split(/[,\t]/).map((s) => s.trim());
if (parts.length < 2) continue;
const inputName = parts[0];
const sgTotal = parts[1] ? parseDecimalOrNull(parts[1]) : null;
const mastersOdds = parts[2] ? parseIntOrNull(parts[2]) : null;
const usOpenOdds = parts[3] ? parseIntOrNull(parts[3]) : null;
const openChampionshipOdds = parts[4] ? parseIntOrNull(parts[4]) : null;
const pgaChampionshipOdds = parts[5] ? parseIntOrNull(parts[5]) : null;
if (sgTotal === null && mastersOdds === null) continue; // no useful data
const skill: ParsedSkill = {
sgTotal,
datagolfRank: null,
mastersOdds,
usOpenOdds,
openChampionshipOdds,
pgaChampionshipOdds,
};
const participant = findParticipantMatch(inputName, localParticipants);
if (participant && !seen.has(participant.id)) {
seen.add(participant.id);
matched.push({ participantId: participant.id, name: participant.name, inputName, ...skill });
} else {
const suggestions = getFuzzySuggestions(inputName, localParticipants, seen);
unmatched.push({ inputName, suggestions, ...skill });
}
}
setParseResults({ matched, unmatched });
}
function assignSuggestion(item: UnmatchedItem, suggestion: Suggestion) {
setParseResults((prev) => {
if (!prev) return prev;
return {
matched: [
...prev.matched,
{ participantId: suggestion.participantId, name: suggestion.name, inputName: item.inputName,
sgTotal: item.sgTotal, datagolfRank: item.datagolfRank, mastersOdds: item.mastersOdds,
usOpenOdds: item.usOpenOdds, openChampionshipOdds: item.openChampionshipOdds,
pgaChampionshipOdds: item.pgaChampionshipOdds },
],
unmatched: prev.unmatched.filter((u) => u.inputName !== item.inputName),
};
});
}
function handleCreateParticipant(item: UnmatchedItem) {
pendingSkillsByName.current.set(item.inputName, {
sgTotal: item.sgTotal, datagolfRank: item.datagolfRank, mastersOdds: item.mastersOdds,
usOpenOdds: item.usOpenOdds, openChampionshipOdds: item.openChampionshipOdds,
pgaChampionshipOdds: item.pgaChampionshipOdds,
});
const fd = new FormData();
fd.set('intent', 'create-participant');
fd.set('name', item.inputName);
createFetcher.submit(fd, { method: 'post' });
}
function applyMatches() {
if (!parseResults) return;
const newValues = { ...skillValues };
for (const m of parseResults.matched) {
newValues[m.participantId] = {
sgTotal: m.sgTotal !== null ? String(m.sgTotal) : '',
datagolfRank: m.datagolfRank !== null ? String(m.datagolfRank) : '',
mastersOdds: m.mastersOdds !== null ? String(m.mastersOdds) : '',
usOpenOdds: m.usOpenOdds !== null ? String(m.usOpenOdds) : '',
openChampionshipOdds: m.openChampionshipOdds !== null ? String(m.openChampionshipOdds) : '',
pgaChampionshipOdds: m.pgaChampionshipOdds !== null ? String(m.pgaChampionshipOdds) : '',
};
}
setSkillValues(newValues);
setParseResults(null);
setBulkText('');
}
const setField = (participantId: string, field: keyof SkillValues[string], value: string) => {
setSkillValues((prev) => ({
...prev,
[participantId]: { ...prev[participantId], [field]: value },
}));
};
const isSubmitting = navigation.state === 'submitting';
return (
<div className="container mx-auto py-8">
<div className="mb-8">
<h1 className="text-3xl font-bold mb-2">Golf Skills</h1>
<p className="text-muted-foreground">
{sportsSeason.sport.name} {sportsSeason.name}
</p>
</div>
{/* Bulk Import */}
<Card className="mb-6">
<CardHeader>
<CardTitle>Bulk Import</CardTitle>
<CardDescription>
Paste one player per line. Format:{' '}
<code>Player Name, SG_Total</code>
{' '}(optional extras: <code>Masters odds, US Open odds, Open Championship odds, PGA odds</code>).
American odds format (e.g. 400 for +400). Player names are fuzzy-matched to participants.
</CardDescription>
</CardHeader>
<CardContent className="space-y-4">
<Textarea
placeholder={`Scottie Scheffler, 2.91\nRory McIlroy, 2.45, 450, 600, 350, 800\nXander Schauffele, 2.12`}
value={bulkText}
onChange={(e) => { setBulkText(e.target.value); setParseResults(null); }}
rows={8}
className="font-mono text-sm"
/>
<Button type="button" variant="outline" onClick={parseBulkText} disabled={!bulkText.trim()}>
Parse Players
</Button>
{parseResults && (
<div className="space-y-3">
{parseResults.matched.length > 0 && (
<div>
<div className="flex items-center gap-2 text-sm font-medium text-emerald-400 mb-2">
<CheckCircle2 className="h-4 w-4" />
Matched ({parseResults.matched.length})
</div>
<div className="rounded-md border border-emerald-500/30 bg-emerald-500/10 divide-y divide-emerald-500/20 text-sm">
{parseResults.matched.map((m) => (
<div key={m.participantId} className="flex justify-between px-3 py-1.5 gap-4">
<span className="text-muted-foreground">{m.inputName}</span>
<span className="font-medium">
{m.name} SG: {m.sgTotal ?? '—'}
{m.mastersOdds ? ` | Masters: +${m.mastersOdds}` : ''}
</span>
</div>
))}
</div>
</div>
)}
{parseResults.unmatched.length > 0 && (
<div>
<div className="flex items-center gap-2 text-sm font-medium text-amber-400 mb-2">
<AlertCircle className="h-4 w-4" />
Not matched ({parseResults.unmatched.length})
</div>
<div className="rounded-md border border-amber-500/30 bg-amber-500/10 divide-y divide-amber-500/20 text-sm">
{parseResults.unmatched.map((u) => {
const isCreating =
createFetcher.state !== 'idle' &&
pendingSkillsByName.current.has(u.inputName);
return (
<div key={u.inputName} className="px-3 py-2 space-y-2">
<div className="font-medium text-amber-300">{u.inputName}</div>
{u.suggestions.length > 0 ? (
<div className="space-y-1">
<div className="text-xs text-muted-foreground">Did you mean</div>
{u.suggestions.map((s) => (
<div key={s.participantId} className="flex items-center gap-2">
<Button
type="button"
size="sm"
variant="outline"
className="h-6 text-xs px-2"
onClick={() => assignSuggestion(u, s)}
>
Use this
</Button>
<span className="text-muted-foreground">{s.name}</span>
<span className="text-xs text-muted-foreground/60">
({Math.round(s.score * 100)}% match)
</span>
</div>
))}
<Button
type="button"
size="sm"
variant="ghost"
className="h-6 text-xs px-2 text-amber-400 hover:text-amber-300"
disabled={isCreating}
onClick={() => handleCreateParticipant(u)}
>
{isCreating ? (
<><Loader2 className="mr-1 h-3 w-3 animate-spin" /> Creating</>
) : (
<><UserPlus className="mr-1 h-3 w-3" /> Create new participant</>
)}
</Button>
</div>
) : (
<div className="flex items-center gap-2">
<span className="text-xs text-muted-foreground">No close matches found.</span>
<Button
type="button"
size="sm"
variant="outline"
className="h-6 text-xs px-2"
disabled={isCreating}
onClick={() => handleCreateParticipant(u)}
>
{isCreating ? (
<><Loader2 className="mr-1 h-3 w-3 animate-spin" /> Creating</>
) : (
<><UserPlus className="mr-1 h-3 w-3" /> Create participant</>
)}
</Button>
</div>
)}
</div>
);
})}
</div>
</div>
)}
{parseResults.matched.length > 0 && (
<Button type="button" onClick={applyMatches}>
Apply {parseResults.matched.length} matched players to form
</Button>
)}
</div>
)}
</CardContent>
</Card>
<div className="grid gap-6 lg:grid-cols-3">
<div className="lg:col-span-2">
<Card>
<CardHeader>
<CardTitle>Player Golf Skills</CardTitle>
<CardDescription>
Enter SG: Total (strokes gained per round vs. field average, e.g. 2.5) and
optionally per-major American odds. Saving will run the simulation and update
expected values. Leave fields blank to use field-average (SG = 0).
</CardDescription>
</CardHeader>
<CardContent>
<Form method="post" className="space-y-4">
<div className="space-y-1">
<div className="grid grid-cols-7 gap-2 text-xs font-semibold text-muted-foreground uppercase tracking-wide pb-1 border-b">
<span className="col-span-2">Player</span>
<span>SG Total</span>
<span>Masters</span>
<span>US Open</span>
<span>The Open</span>
<span>PGA</span>
</div>
{localParticipants.map((p) => (
<div key={p.id} className="grid grid-cols-7 gap-2 items-center py-1">
<Label htmlFor={`sgTotal_${p.id}`} className="col-span-2 truncate text-sm">
{p.name}
</Label>
<Input
type="number"
step="0.01"
id={`sgTotal_${p.id}`}
name={`sgTotal_${p.id}`}
placeholder="2.50"
value={skillValues[p.id]?.sgTotal ?? ''}
onChange={(e) => setField(p.id, 'sgTotal', e.target.value)}
className="h-8 text-sm"
/>
{(['mastersOdds', 'usOpenOdds', 'openChampionshipOdds', 'pgaChampionshipOdds'] as const).map((field) => (
<Input
key={field}
type="number"
name={`${field}_${p.id}`}
placeholder="400"
value={skillValues[p.id]?.[field] ?? ''}
onChange={(e) => setField(p.id, field, e.target.value)}
className="h-8 text-sm"
/>
))}
{/* Hidden rank field */}
<input type="hidden" name={`datagolfRank_${p.id}`} value={skillValues[p.id]?.datagolfRank ?? ''} />
</div>
))}
</div>
{actionData && !('intent' in actionData) && !actionData.success && actionData.message && (
<div className="text-sm text-destructive">{actionData.message}</div>
)}
<Button type="submit" disabled={isSubmitting}>
{isSubmitting && <Loader2 className="mr-2 h-4 w-4 animate-spin" />}
{isSubmitting ? 'Saving & Running Simulation...' : 'Save Skills & Run Simulation'}
</Button>
</Form>
</CardContent>
</Card>
</div>
<Card>
<CardHeader>
<CardTitle>How It Works</CardTitle>
</CardHeader>
<CardContent className="text-sm space-y-2 text-muted-foreground">
<ol className="list-decimal list-inside space-y-2">
<li>Enter SG: Total for each player (strokes gained per round vs. average field)</li>
<li>Optionally enter American odds per major (e.g. 400 for +400) for players without SG data</li>
<li>For each of 10,000 simulations, simulate each incomplete major using a Plackett-Luce model</li>
<li>A synthetic rest-of-field fills the 156-player field at SG = 0 (average)</li>
<li>QP awarded per finishing position per the season QP config (1st = 20, 2nd = 14, etc.)</li>
<li>Players ranked by total QP across all 4 majors</li>
<li>Placement probabilities (1st8th) determine expected fantasy value</li>
</ol>
<div className="mt-4 text-xs space-y-1">
<div className="font-medium text-foreground">SG: Total reference points:</div>
<div>+3.0 Elite (5% win prob per major)</div>
<div>+2.0 Very good (2.6% win prob)</div>
<div>+1.0 Good (1.3% win prob)</div>
<div>0.0 Field average (0.6% win prob)</div>
</div>
</CardContent>
</Card>
</div>
</div>
);
}