{"id":593976,"date":"2025-11-26T01:28:12","date_gmt":"2025-11-26T01:28:12","guid":{"rendered":"https:\/\/www.europesays.com\/uk\/593976\/"},"modified":"2025-11-26T01:28:12","modified_gmt":"2025-11-26T01:28:12","slug":"seven-big-name-players-who-lost-huge-data-golf-ranking-points-in-2025","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/uk\/593976\/","title":{"rendered":"Seven big name players who lost huge Data Golf ranking points in 2025"},"content":{"rendered":"

A handful of golf\u2019s biggest names saw their stock plummet in the Data Golf rankings in 2025 \u2014 none more dramatically than PGA Tour veteran Tony Finau.<\/strong><\/p>\n

While the Official World Golf Ranking remains the sport\u2019s formal benchmark, its continued exclusion of LIV Golf events has pushed many fans and analysts toward Data Golf\u2019s model as a more accurate read on the professional landscape. And according to Golf Digest\u2019s Jamie Kennedy<\/a>, the numbers weren\u2019t kind to several high-profile players this season.<\/p>\n

Kennedy highlighted seven <\/strong>stars from the PGA Tour<\/a> and LIV Golf<\/a> who tumbled from inside the top 50 to outside the top 100<\/strong> in Data Golf\u2019s system \u2014 a group he bluntly dubbed the \u201cbiggest losers\u201d of 2025.<\/p>\n

Finau suffered the steepest fall of all, free-falling from 20th to 147th <\/strong>after a season in which he posted just one top-10 finish.\u00a0<\/p>\n

Once linked heavily to a move to LIV, Finau\u2019s form has slid steadily since, a stark contrast to the six-time winner\u2019s peak years.<\/p>\n

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The drop-offs didn\u2019t stop there.\u00a0<\/p>\n

Sahith Theegala (32 to 155<\/strong>), Tom Kim (21 to 139<\/strong>), Brooks Koepka (45 to 159<\/strong>), Sergio Garcia (40 to 140<\/strong>), Sungjae Im (12 to 109<\/strong>) and Mackenzie Hughes (12 to 109<\/strong>) rounded out the list of major movers in the wrong direction.<\/p>\n

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Biggest losers of 2025…<\/p>\n

The biggest drop in @DataGolf<\/a> ranking of those players who started the year inside the top 50.<\/p>\n

\u2022 Tony Finau (20 \u2192 147)
\u2022 Sahith Theegala (32 \u2192 155)
\u2022 Tom Kim (21 \u2192 139)
\u2022 Brooks Koepka (45 \u2192 159)
\u2022 Sergio Garcia (40 \u2192 140)
\u2022 Sungjae Im (12\u2026 pic.twitter.com\/F8XK7FVMB5<\/a><\/p>\n

\u2014 Jamie Kennedy (@jamierkennedy) November 25, 2025<\/a><\/p><\/blockquote>\n

The big question on everyone’s lips as we head into 2026, is will LIV Golf players receive OWGR points in their events now they have switched from 54 to 72 holes<\/a>.\u00a0<\/p>\n

All will be revealed soon.\u00a0<\/p>\n

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What is Data Golf?<\/strong><\/p>\n

Launched in 2016, Data Golf has become a leading analytics platform, offering statistical models, strokes-gained-based rankings, predictive tools, interactive visualizations and a vast database of global professional golf results.\u00a0<\/p>\n

Its transparent methodology and emphasis on recent performance make it a favourite among fans, media and bettors.<\/p>\n

How does it differ from OWGR?<\/strong><\/p>\n

Unlike the OWGR\u2019s two-year, points-based system weighted by tournament prestige, Data Golf leans on shot-by-shot performance metrics and applies an exponential decay to reward current form.\u00a0<\/p>\n

Its approach is fully transparent \u2014 a sharp contrast to the criticism often levelled at the OWGR\u2019s opaque point structure.<\/p>\n\n

Feature<\/strong><\/p>\n

Data Golf<\/strong><\/p>\n

OWGR<\/strong><\/p>\n<\/tr>\n\n\n

Core Methodology<\/strong><\/p>\n<\/td>\n\n

Strokes gained: measures performance against the field shot-by-shot.<\/p>\n<\/td>\n\n

Points-based: awards points based on tournament strength and finishing position.<\/p>\n<\/td>\n<\/tr>\n\n\n

Ranking Calculation<\/strong><\/p>\n<\/td>\n\n

Uses field-strength-adjusted scoring with exponential time decay to prioritise recent form.<\/p>\n<\/td>\n\n

Two-year rolling window, averaging points; recent updates have added more advanced metrics.<\/p>\n<\/td>\n<\/tr>\n\n\n

Transparency<\/strong><\/p>\n<\/td>\n\n

Fully transparent methodology, including regression models and baselines.<\/p>\n<\/td>\n\n

Frequently criticised for limited transparency.<\/p>\n<\/td>\n<\/tr>\n\n\n

Field Strength<\/strong><\/p>\n<\/td>\n\n

Evaluates players\u2019 strokes-gained profiles to calculate true field quality.<\/p>\n<\/td>\n\n

Uses strokes gained to assess field strength, a change made after consulting Data Golf\u2019s creators.<\/p>\n<\/td>\n<\/tr>\n\n\n

Predictive Accuracy<\/strong><\/p>\n<\/td>\n\n

Widely viewed as more predictive of future performance.<\/p>\n<\/td>\n\n

Considered less predictive than Data Golf by many analysts.<\/p>\n<\/td>\n<\/tr>\n

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Which ranking system do you prefer to look at to see a player’s performance across the season? The traditional OWGR, or the newer Data Golf?\u00a0<\/strong><\/p>\n

Share your thoughts on GolfMagic Facebook<\/strong><\/p>\n

\u00a0<\/p>\n

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