ProPlace

← Blog · Reviews · 23 June 2026 · 8 min read

ProPlace Review 2026: An Honest Look at the Golf Analytics Platform

What ProPlace does, where it works well, and where it has limits - so you can decide whether it fits how you research PGA Tour and DP World Tour events.

By Doug Dinwiddie

Founder of ProPlace. Former DP World Tour caddie.

If you've spent time researching golf tournaments, you've probably hit the same wall. Available tools either hand you raw data with no interpretation, or they surface curated shortlists that feel closer to tipster content than actual analysis. ProPlace sits in a different category. This review covers what the platform does, where it works well, and where it has limitations - so you can decide whether it fits how you research.

What ProPlace Is

ProPlace is a golf analytics platform covering the PGA Tour and DP World Tour. It produces a model probability for every player in every tournament field, compares that probability to the prevailing market consensus, and ranks players by the size of the gap between the two.

The output is a single ranked list. Players appear at the top when the data and the market are disagreeing most sharply. That gap is where the signal lives.

What the Model Uses

The model builds each player's probability from 5 inputs: strokes gained data, course history, course fit, recent form, and field strength. These are the standard inputs for serious golf modelling. What matters is how they're weighted and combined - and ProPlace doesn't ask you to take that on trust.

Every player card shows the model probability, the market consensus figure, the gap between them, a conviction score out of 10, and a plain-English summary explaining why that player has been flagged. No black box. You can see the reasoning before you decide whether to act on it.

Full Field Coverage

Most golf analysis tools surface a shortlist - 15 or 20 names, with everything outside that list invisible. ProPlace covers every player in every field. That matters because the signal doesn't always sit at the top of the market. A player ranked 60th in the consensus might carry a model probability that makes the gap significant. You won't find that if you're working from a curated shortlist of 20 or 30 names.

Full field coverage means you're working with the complete picture, not an edited version of it.

The Conviction Score

The conviction score runs out of 10 and appears on every player card. It tells you how strongly the data lines up - not just that a gap exists, but how much weight the model places on it.

Gap size matters, but so does conviction. A large gap with a low conviction score means the model sees a difference but isn't confident in the inputs behind it. A smaller gap with a high conviction score can carry more weight. The score lets you distinguish between the two without having to interpret the underlying data yourself.

Track Record

ProPlace publishes its historical performance at proplace.golf/performance. The framing matters: the track record is presented as something you should scrutinise, not just accept. That's a deliberate choice. Any analytics tool can claim its model works. Fewer publish the full record and invite you to audit it.

If you're evaluating whether the model has delivered over time, that page is where you start. Past performance doesn't guarantee future results, but a transparent record is a meaningful signal about how the platform operates.

How It Compares to Alternatives

DataGolf is the most credible alternative for serious researchers. It produces strong strokes gained modelling and publishes detailed methodology. The limitation is structural: DataGolf is built for analysts who want to work with the data directly. The interface reflects breadth rather than depth of interpretation. You get the numbers; you do the synthesis.

SportsLine produces golf content with model-backed analysis, but the framing sits closer to tipster output than research infrastructure. The content is readable, but it doesn't surface the gap between model probability and market consensus as a primary signal.

ProPlace's specific value is the combination: full field coverage, the gap already calculated, conviction scoring applied across every player, and plain-English summaries that explain the reasoning. It's built for researchers who want the synthesis done - not the raw data handed over.

Pricing and Trial

ProPlace costs £20 per month, or £200 per year (equivalent to £16.67 per month). A 7-day free trial gives you full access from day one - no restricted features, no preview mode. No card is required upfront, and the trial cannot convert to a paid subscription on its own.

The practical way to evaluate the platform is to run the free trial against a live tournament week. Compare the rankings to how the field actually performs, and check the track record while you're at it.

What It Does Well

  • Ranks every player in every field by signal strength, not by name recognition or market position
  • Shows exactly where the data and the market are disagreeing, with the gap calculated for you
  • Applies conviction scoring so you can weight signals appropriately
  • Covers both the PGA Tour and DP World Tour within a single subscription
  • Publishes its track record in full

What to Be Aware Of

ProPlace focuses on top-finish probabilities. If you want granular round-by-round modelling or head-to-head matchup data, that's not what the platform is built for. It's designed around one question: which players does the model see differently from the consensus, at the tournament level.

It's also subscription-based. You're paying for a weekly research tool across the season, not a one-off data pull. That's the right model if you follow golf consistently. It's less suited to occasional use.

The Core Question

The question ProPlace answers is specific: where does the model see a player differently from the market consensus, and how strong is that signal? If that's what you're trying to establish before each tournament, the platform is built around it. If you're looking for raw strokes gained tables, DFS lineup tools, or tipster content, it's not the right fit.

Understanding how to find value using PGA Tour model vs consensus data is the underlying research skill the platform supports. ProPlace does the calculation; you apply the judgement.

The platform is straightforward to evaluate. Run it through a live tournament week, compare the ranked list to how the field performs, and check the published track record at proplace.golf. The data is there to scrutinise.

Frequently asked questions

What does ProPlace actually produce each week?
A ranked list of every player in the current PGA Tour and DP World Tour fields, ordered by the size of the gap between model probability and market consensus. Each player card includes the model probability, the consensus figure, the gap, a conviction score out of 10, and a plain-English summary.
How is ProPlace different from DataGolf?
DataGolf is a strong research tool for analysts who want to work directly with strokes gained data and model outputs. ProPlace is built for researchers who want the synthesis already done - the gap calculated, conviction scored, and reasoning summarised in plain English. The two tools serve different research workflows.
Does ProPlace cover DP World Tour as well as PGA Tour?
Yes. Both tours are covered within a single subscription. Every player in every field on both tours is analysed by the model each week.
What is the conviction score?
It runs out of 10 and appears on every player card. It reflects how strongly the data lines up behind the signal - not just whether a gap exists, but how much weight the model places on the inputs driving it.
Can I see the track record before subscribing?
Yes. ProPlace publishes its historical model performance at proplace.golf/performance. It's there to audit, not just accept.
How does the free trial work?
7 days of full access. No card is required upfront, and the trial cannot convert to a paid subscription on its own - you are only charged if you choose a plan.
Is ProPlace built for casual fans or serious researchers?
It's built for research-first fans who want structured, data-backed analysis before each tournament. The platform assumes you know what a golf model is and want the output interpreted - not that you want to build the model yourself.
18+ | BeGambleAware.org — Please gamble responsibly. Past performance is not a guide to future results.