Pardle

How the Round Score Forecast works

A plain-English tour of the model. Every parameter the tool exposes, what it means in golf terms, and how the model uses it to turn today's wind, pins, and player skill into a projected round score.

What's on this page
  1. 1. The big picture — three layers of the forecast
  2. 2. The setup — describing today's course
  3. 3. Adding a player — skill, tee time, form
  4. 4. Advanced knobs — form weight, compression, skew
  5. 5. Reading the results
1

The big picture

What the forecast answers, and how the model splits the problem

The Round Score Forecast answers one question: if this player teed off right now under today's conditions, what score would we expect them to shoot?

The model splits that into three layers, in this order:

  1. The field baseline. What the average PGA Tour player in this field would score today, given the wind, pin positions, and yardage the tour has posted for this round.
  2. The player's skill edge. How much better (or worse) than average this player is, adjusted for the type of course. An elite player at a course that flattens the field gets a smaller edge than the raw skill number implies.
  3. The player's recent form. How much their scores this week suggest they're currently playing above or below their baseline — weighted by which skills carry from round to round.

Each layer is a knob you can inspect and override. The rest of this page walks the knobs in the order they appear in the tool.

2

The setup — describing today's course

Tournament, round, conditions, yardage, pins, wind

These six inputs describe the world the round will be played in. Together they feed the field baseline from the first layer above.

Tournament

Auto-locked to the active event

The tool follows the currently active PGA Tour event. You'll see the tournament name populated automatically once the field roster loads. Once the event finishes, the tool switches to next week's.

Round to forecast

1 · 2 · 3 · 4

Pick which round you want a forecast for. R4 today, R1 for a Wednesday preview, R3 for a Saturday morning look at the day ahead.

Conditions

How much yesterday tells us about today

Same course, different day — how much has this week's play already revealed about the setup?

  • Conditions like the most recent finished round (default for R3+): if yesterday played softer than typical because greens were receptive and pins were fair, the model expects today to play similarly.
  • Based on R3 / R2 / R1: anchor on a specific round rather than the most recent one.
  • Average of the week: blend every played round. Softer signal, less R3-heavy.
  • Typical setup for this course: ignore this week's data entirely and use the historical baseline for this round.

Behind the scenes this becomes a level shift — a per-hole stroke adjustment carried over from the reference round(s). The measured softness of the reference round is spread evenly across today's 18 holes.

Example
When yesterday plays softer than the historical mean for that round, the softness carries forward. With "Conditions like the most recent finished round" selected, the model measures the prior round's per-hole residuals and applies them as a level shift across today's round — expecting today to play softer than the untouched historical baseline by the same amount the prior round did.

Yardage

Auto from the pin sheet, or a manual delta

Pardle's prediction (default): pulls the exact yardages the tour has posted for the round. Each hole plays at the length the setup team has actually set up, not some rounded value.

Manual delta from a prior round: when the tour hasn't posted yardages yet, you can say "the course will play 100 yards longer than R3" and the model spreads that delta evenly across the 18 holes. Useful for early-week previews.

The yardage impact per hole is derived from per-hole regression coefficients — every hole at this course has its own historical yardage sensitivity. Long par-5s scale differently than drivable par-4s.

Pins

Cluster-match, or a manual scoring adjustment

Pardle's automated clusters (default): several years of pin-by-pin scoring at this course have been clustered by green zone (front-right, back-left, etc.). Each hole's pin position today is matched to its nearest historical cluster, and the model uses that cluster's residual scoring difficulty.

Manual scoring adjustment: skip the auto-match; enter a single total-round stroke adjustment (+0.5 = the setup plays 0.5 strokes harder than the historical average). Useful when the setup team has done something novel that the historical clusters can't capture — new pins outside any known zone, or an unusually fast green speed the sample doesn't reflect.

Wind

HRRR hourly, GFS blend, or manual

The forecast defaults to HRRR — a high-resolution NOAA weather model that updates hourly and provides wind speed + direction at the course location for every hour of the day. This lets the model give late tee times the wind they'll actually face at 3pm rather than a smoothed daily average.

GFS blend: a global forecast model, smoother in the mid-afternoon peaks but longer forecast range. Useful for Sunday when we're looking at Thursday.

Manual override: force a specific wind speed (mph) and direction (degrees FROM). Useful for what-if analysis or when you disagree with the forecast.

Wind translates to scoring via per-hole headwind coefficients. Each hole's historical sensitivity to headwind is baked into the regression — a downhill par-3 into the wind plays much harder than an easy short par-4 with the wind at your back.

Example
A long par-3 that plays roughly south sits with its bearing pointing straight into an SSW wind (bearing ~200°), so the full wind speed acts as headwind. A short par-4 playing north-west with the same SSW wind sees only a fraction of that as headwind — the model computes the component of the wind vector along each hole's bearing and multiplies by that hole's own fitted coefficient.
3

Adding a player

Skill baseline, tee time, and this week's form

Once the setup describes the field baseline, adding a player lets the model project their personal expected score. This is where SG, form, and tee-time-aware wind come in.

Season SG

Talent — how many strokes above/below the tour average

Strokes Gained (SG) is the standard measure of golf skill. It counts how many strokes better or worse than the tour average a player is, per round, after adjusting for the fields they've played.

  • Roughly +3 SG: elite, top-of-the-world level
  • Roughly +1.5 SG: top-50-in-the-world level
  • Roughly +0.5 SG: solid tour regular
  • Roughly −0.5 SG: below-average tour player, cut risk most weeks

The tool auto-fills this from Pardle's pre-tournament model when the player is in this week's field. You can override with your own number.

Tee time

Local time — makes wind personal

When set, the model reads the wind at the specific hour this player will face each hole. It assumes ~15 minutes of walking per hole from tee-off, so a 1:30 PM starter is playing hole 9 around 3:30 PM, hole 18 around 5:00 PM.

This matters most when a late tee time faces a building afternoon wind. On a calm morning that gusts up by mid-afternoon, the day-average forecast blends the two regimes and understates the difficulty for the late group.

Example
Two players with identical SG, one teeing off at 7:00 AM when the wind is light and one at 1:30 PM when the wind has built. Under the day-average model they project the same score. With tee-time-aware wind, the late tee's projection is meaningfully harder — a systematic edge for betting the morning group UNDER and the afternoon group OVER.

Rounds this week (auto-filled)

Form is over/under-performance vs baseline, not raw score

Every player who's completed at least one round shows up with per-round tiles: their vs-par score plus the four strokes-gained categories (OTT, APP, ARG, PUTT) and a persistence factor.

The form signal isn't the raw vs-par score. It's how much a player over- or under-performed their own expected score for that round — the round's actual field average adjusted for the player's season SG. An elite player is expected further under par than the field mean; an average tour player is expected right at it. An average tournament round for an elite player is a negative form signal because he under-performed his baseline. A tour- average player shooting the same round is performing exactly to expectation and gets no form bump either direction.

Example
Say the field averages a few strokes under par for the round. An elite player is expected to shoot several strokes further under than that. If he shoots only the field average, the model treats that as a negative form signal — several shots of underperformance vs expected — and nudges his projection up tomorrow (worse than his season baseline suggests).

The persistence factor is the model's smartest trick. Not all strokes-gained categories persist equally from round to round. Once we know the over/under-performance, we scale it by which skills drove it — approach and driving carry forward reliably, putting mostly regresses to the mean.

SG CategoryPredictive strengthInterpretation
Off-the-tee (OTT)
Very repeatable — driving swing
Approach (APP)
Highly repeatable — iron accuracy
Around-the-green (ARG)
Moderate — chipping, some noise
Putting (PUTT)
Mostly noise round to round

The persistence factor shown on each round tile compares that round's skill mix to a category-balanced round. A balanced round sits at 1×; approach- or driving-heavy rounds tilt above 1× and count for more; putt-heavy rounds tilt below 1× and count for less.

Example
Two players who both beat their expected score by the same 3 shots this round. Same over-performance — but very different signals about tomorrow:
Player A — approach-driven round
Most of the SG total came from iron play, a repeatable skill.
Persistence factor above 1× — the model carries a stronger form bump into tomorrow's projection.
Player B — putt-driven round
Most of the SG total came from hot putting, which regresses hard round-to-round.
Persistence factor below 1× — same 3 shots of over-performance, but the model discounts it and barely nudges tomorrow's projection.
4

Advanced knobs

Form weight, skill compression, skew adjustment

These three sliders live behind "Show advanced" on each player card. Every player uses sensible defaults; touch them only when you have a specific reason.

Form weight

How much this week's rounds shift the projection

Slide left to ignore form entirely and project purely from season SG. Slide right to lean heavily on this week's scoring.

The default sits at Pardle's calibrated value — informed by the Connolly-Rendleman shrinkage literature and our own back-testing. Enough to catch a genuine hot streak, not so much that a few outlier rounds dominate.

The mechanics: the model measures how much a player has over- or under-performed their expectation across their played rounds this week, then applies a fraction of that average delta to the projection. Small fraction, real signal.

Skill compression

How much the course flattens the field

Some courses reward a specific set of skills less than SG:Total captures — a "bunching" course where everyone scores in a tight band regardless of talent.

Slide right for no compression — the player's season edge translates 1:1 into the projection. Slide left for aggressive compression at bunching-friendly venues, where an elite player's edge shrinks meaningfully.

The default is set per-course-type based on eight-plus years of scoring dispersion at each venue. At TPC Twin Cities the field bunches, so the default compresses the raw SG number by a notable but not-extreme amount.

Example
An elite +3 SG player at a bunching course expects to outperform the field by less than 3 strokes — some of that raw edge gets washed out by a setup where the gap between top and mid tightens.

Skew adjustment

The mean-vs-median gap for this player

Golf rounds don't follow a symmetric distribution. The occasional blow-up (a triple bogey, a lost ball) sits in a fat right tail and inflates the mean while leaving the median stable. The skew adjustment is how much wider we assume the mean is than the median.

  • Elite players: tightest gap — blow-ups are rare, so mean and median sit close together.
  • Mid-tier players: moderate gap.
  • Below-average players: widest gap — wider right tail, more blow-ups.

The default gap is picked automatically from the player's season SG tier. You can override with the slider if you have a reason to.

Why this matters for betting: the median is your typical outcome. The mean is inflated by rare catastrophes that don't happen most rounds. When betting UNDER a line, the median is often the right number to compare against.

Example
A player's projected mean sits a fraction of a stroke higher than their projected median because of that fat right tail. Against an UNDER 69.5 line, the median offers a meaningfully bigger buffer than the mean — that extra cushion is why the tool leads with median for UNDER decisions.
5

Reading the results

Hero forecast, model delta, player projections, per-hole detail

The Results panel is the model's answer, broken into a hero card, a secondary strip of context, per-player projections, and an 18-hole detail strip.

Field forecast (hero)

The average score today

The projected total-strokes score for the average player in the field, teeing off with today's setup. This is the top-line answer — the vs-par number below tells you whether it's an easy day (green, under par) or a grinder (red, over par).

Model delta

Today's forecast vs the historical baseline

How much easier or harder the model expects this round to play compared to the historical average for this specific round number at this course.

−0.5 means today should play half a stroke easier than a typical R4 here. +1.2 means it's shaping up as one of the harder R4s in the historical record.

Historical mean

Untouched historical baseline

The historical average total-strokes score for this specific round number at this course, with no adjustment for today's conditions. Useful as an anchor: the field forecast should feel roughly like historical mean + level shift + wind delta.

Wind

Field-averaged across every tee time

The wind figure shown is aggregated across every field member's actual tee time — so an 8am-to-3pm tee-time spread with rising wind produces a higher effective wind than the average of the morning and afternoon peaks alone.

Level shift

Softness carried from prior rounds

The per-hole stroke adjustment carried in from the reference round(s) selected in Conditions. Negative = course expected to play easier than historical because this week has been playing soft.

When you see an attenuated value next to the level shift, the Conditions preset has scaled the raw measurement down. That's a hedge against overnight drying or firming: when we're not fully confident yesterday's softness will persist unchanged, the model carries a fraction of it forward instead of the whole thing.

Player projections

Expected mean and median for each player

For each player added:

  • SG / Edge / Form: the three drivers. SG is season baseline; Edge is that baseline compressed for course type; Form is the Bayesian shrinkage bump from this week's persistence-weighted rounds.
  • Mean: the average score you should expect if this player played the same round 1,000 times. Use for outright bets where blow-ups still count as losses.
  • Median: the middle outcome. Use for round-score UNDER bets, where the fat right tail doesn't hurt you as much as it inflates the mean.

Both are colour-coded: emerald for under par, tang for over par. The Median box is accented emerald because it's the payoff number for most betting decisions.

Per-hole projection

Every hole colour-coded, expandable

Collapsed by default as an 18-block colour ribbon — emerald for under-par, tang for over-par, saturation scaled to how far from par. Click Expand to see each hole's projected score, par, yardage, and headwind.

This is where you spot the model's per-hole story: a drivable par-4 today (H16 at 301 yds instead of 411) shows up as a deep emerald tile with a big negative vs-par projection. A par-3 into a 15 mph headwind shows up as tang.

Ready to run one?
Head to the tool and try it on this week's field.
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