Golf Analytics

How Golfers Win

Monthly Archives: February 2014

What’s a Hot Start Worth?

This weekend marks the eighth weekend of professional golf in 2014 and the beginning of the Florida Swing of the PGA Tour schedule. So far this season, guys like Jimmy Walker, Patrick Reed, and Harris English have started off playing like top 20 players in the world. With almost two months of the year (not to mention five months of the Tour season) in the books, it feels like we’re reaching the point where we can start to tell who’s struggling, who’s excelling, who’s going to contend for a Major, who’s the next Big Thing, etc. This post is designed to throw some water on those ideas. Two months doesn’t tell us very much about how the rest of the season will play out, at least when compared to a much larger sample of past tournaments.

To test how predictive the first two months of the golf season are of the rest of the season, I gathered all players 2010 to 2013 who played at least 50 rounds in the two seasons prior to the season in question (ie, 2008-09 for 2010, 2009-10 for 2011, etc.) and who played any rounds in the first two months of the season in question and in the remaining calendar year of the season in question. I kept these requirements fairly loose, but tested other combinations. In total, I found 1984 seasons from players on the PGA Tour, European Tour, Tour, and Challenge Tour. I found the average performance in z-score for the two years prior to the season in question, the first two months of the season in question, and the remainder of the season in question.

To test whether the first two months were predictive of the remainder of the season I first simply found the correlation between the first two months and the remainder of the season. I found a strong correlation (R=0.57) between the two, indicating that the first two months were highly predictive of the rest of the season. However when I examined the correlation between the prior two seasons and the remainder of the season in question (while ignoring the most recent two months), the correlation grew even larger (R=0.68). Note again that this ignores the first two months of the season. That is, if you lock me in a room from New Years until March without access to any information about professional golf I will do a better job predicting the season than someone who only relies on who’s playing well in January and February.

Now, obviously you don’t have to ignore one set of data (two year average) in favor of another (two month average). I ran a simple linear regression of the two variables (two year average and two month average) on the rest-of-season average to see if the accuracy would improve. Indeed, including both variables increased the correlation slightly to 0.72, meaning that this model explains over half of the variance in the remainder of the season (this again shows how random golf is). More interesting are the coefficients the regression spits out: Y = (0.72*Two Year)+(0.20*Two Month)+0.04. That is, the two year average is 3.5 times more important than the two month average.

I followed this study up with another that repeated the methodology, but winnowed the sample down by restricting it to players with > 100 rounds in the previous two season, > 5 rounds in the first two months, and > 19 rounds in the remainder of the season. The results were consistent with what was earlier observed. Using the smaller sample (N=1300 now) slightly improved the predictive strength and also slightly increased the importance of the two year average relative to the two month average.

However, I conducted a further study that showed that drastic improvements in z-score in the first two months were much less predictive of the remainder of the season than the general sample. Using the stricter sampling method above, I split the seasons into those where the two month average was 0.30 standard deviations better than the two year average (basically the sixth of the sample that improved the most), where the two month average was 0.30 standard deviations worse than the two year average (basically the sixth of the sample that declined the most), and the remaining 2/3rds of the sample. I ran the regression using only the data from the +0.30, -0.30, and middle groups.

The results showed that when considering only those who improved the most, you should almost completely ignore what happened in the first two months and rely on the two year average to predict going forward. For the other two groups, the results were largely consistent with what was observed in the previous studies – two year average is roughly 3 times more important than two month average.

Now, I have to stress that the sample of those who improved the most is only 192 seasons and that the standard errors of the coefficients are large (0.11). The confidence interval for the two year coefficient is 0.66 – 1.13, centered on 0.90 while the confidence interval for the two month coefficient is -0.19 to 0.24, centered on 0.03. The standard errors for the previous studies were much smaller (0.02 to 0.03). The finding that two month average should be largely ignored for those who showed the most improvement certainly needs to be tested further with more data.

I am much more confident in the main conclusions, however. When attempting to predict performance over the rest of the season – like who will contend for Majors, Ryder Cup berths, and the FedEx Cup – weigh more heavily how a golfer has played in the prior few seasons than how they’ve started off the calendar year. If that means we pump the brakes a little on Walker, Reed, and English, so be it. And don’t write off Tiger, Kuchar, Poulter, and Luke Donald for a poor couple months. Those guys have shown for years that they belong in the world’s elite; that’s worth more than a cold start.

Honda Classic Preview


The tournament is played at the PGA National Champions course. The course has bermuda grass greens (the first appearance of bermuda grass greens in over a month) and is most notable for the amount of water hazards the golfers will navigate this week. At least four holes require shots to be played over water where it will be directly in play and several other holes have water in play left or right of the green. In the finishing four holes, there are two par 3s with shots entirely over water and a par 5 where going for the green requires a shot entirely over water to a difficult pin.

2013 averages: Driving Distance – 283 yards, Driving Accuracy – 62%, GIRs – 59%, Scrambling – 55%

Relative to average, the course depresses driving distance, greens in regulation, and scrambling.

Past Performance:

The tournament has been held at the PGA National since 2007, meaning past data is limited. Only 17 players in the field this week have 20+ rounds at the course and the median number of prior rounds is 10. Among the notable favorites, Phil Mickelson has never played the Honda at PGA National, while Adam Scott has only 2 rounds.

Because of the limited samples of prior performance here, there are hardly any golfers who have shown a statistically significant difference in their performance at PGA National versus in all other tournaments. I took each player’s 2007-2013 Honda Classic average performance and their average performance in all tournament from 2007-2013 (weighted by # of rounds played in a season so that if a golfer did not play in 2010, his 2010 performance did not factor into their overall average).

I used a t-test to check for statistical significance. Only three golfers entered this week have played better or worse at a statistically significant level – Erik Compton (12 rounds, better), Geoff Ogilvy (4 rounds, better), and Will MacKenzie (16 rounds, better). It’s important to note that we would expect a similar number of golfers to be significantly better by chance alone. There’s simply not enough data for this tournament, at this venue, to make conclusive statements about how certain golfers over or under-perform here.

Who Do the Stats Fit?:

More generally, I wondered whether PGA National fits a certain type of golfer’s game. Does it favor those who drive for distance? Or accuracy? I gathered individual player data for driving distance and driving accuracy for 2011 to 2013, standardizing the values to the average observed over both years. I then gathered corresponding performance in standard deviations from the mean for each player, stripping out their putting performance using each golfer’s strokes gained putting. For example, Michael Thompson was 1.48 standard deviations better than the field last year. 0.49 of that was from putting, meaning he played tee to green in ~1.0 standard deviation better than the field per round. I then regressed driving distance and accuracy on each golfer’s performance tee to green relative to the field.

The results suggested that there’s a slight bias towards those who drive the ball longer at PGA National. Golfers who were above-average in distance/below-average in accuracy outperformed golfers who were below-average in distance/above-average in accuracy by 0.6 strokes/round, which is fairly significant. For all tournaments in 2013, +drivers/-accuracy outperformed -drivers/+accuracy by roughly 0.2 strokes/round. This suggests that driving for distance is more important at PGA National than in the average PGA Tour tournament. A regression based on only 360 rounds over three years is not airtight, but it does suggest PGA National is biased towards those who hit for more distance.

Distance & Difficulty:

I have a stat to measure the distance a course plays called True Distance. True Distance standardizes the length of each hole based on whether it’s a par 3, 4, or 5. This is necessary because the main factor that effects the listed length of courses is the number of this number of par 3 and par 5s. PGA Tour courses with only 2 par 5s play to 7177 yards on average, while those with 4 par 5s play to 7337 yards. That extra yardage doesn’t make those courses with extra par 5s more difficult.

To find the True Distance of a course I compare the length of each hole to the average length of all PGA Tour holes of that particular par. The average par 3 on Tour is 198 yards, par 4 is 433 yards, and par 5 is 563 yards. A 500 yard par 4 is +67 yards in true distance while a 160 yard par 3 is -38 in true distance. I sum the true distance value for each hole to determine the course total. A table of course, tournament, scorecard yardage, and True Distance is below.

PGA Tour Courses

Immediately it’s obvious why judging a course by its True Distance is superior. Kapalua, site of the season opening Tournament of Champions, is typically considered a bomber’s paradise, but it actually plays as one of the shortest courses on Tour once you factor in that it’s a par 73 with only 3 par 3s. It plays short because 8/11 par 4s and 3/4 par 5s are below average in terms of distance. Opposite of Kapalua are a half-dozen par 70 courses which play as some of the longest courses on Tour, despite having scorecard lengths considered roughly average.

PGA National is one of those par 70s that plays much longer than it is listed. Eight holes play at least 20 yards longer than average, while only 4 holes play at least 20 yards shorter than average. That’s a major reason why this course has played an average of 6.7 strokes over par since 2007.

Will Jimmy Walker Continue to Putt at an Elite Level?

I got some push-back from Chris Catena on twitter today about my contention that Jimmy Walker’s recent run of great play was driven by lucky putting. In that post, I showed that Walker had established himself recently as an above-average, but not elite putter (a strokes gained putting of around +0.25-0.30/round for the last five years). During Walker’s recent run ( Open through Northern Trust Open), he’s putted at a +1.20 level. That +0.9 strokes/round improvement is entirely what carried him to three wins in the last four months. I also contended that Walker continuing to putt at this level is very unlikely, simply because no one ever has for a full-season. Moreover, Walker’s best putting season (+0.46) and average putting season (+0.26 from 2009-2013) are far short of the kind of elite, sustained level of play we often see out of the golfers who lead the Tour in strokes gained putting. This post is to defend those claims in more depth and show why I think it’s very unlikely that Jimmy Walker will continue putting and playing as well as he has in the last four months.


Above is a graph of Walker’s strokes gained putting performance per tournament in every tournament the PGA Tour has data for since the start of 2012. The red dashed line is a linear trendline of his performance. It has basically zero (R=0.03) relationship with the passage of time, indicating that on the whole, Walker’s performance hasn’t improved over time. This is important to note because if we hypothesize that Walker changed something in his ability to putt, it clicked in only weeks after his worst putting stretch of the past 2+ years. Now, poor performance is certainly a motivator to change and try to improve, but a simpler explanation is that Walker got unlucky during the summer, and has been riding a combination of luck and improved putting since.

What Walker has done in the past 23 rounds on Tour isn’t unprecedented even during the 2013 season. I divided the tournaments in 2013 (Hyundai ToC to Tour Championship) into four quartiles with 7-8 tournaments in each quartile. I then found the golfers who had participated in 4+ tournaments in each bucket and averaged their SGP for each quartile. I gathered all golfers who had qualifying consecutive quartiles and compared them using Q1->Q2, Q2-Q3, etc. For Q4, I compared it to performance so far in 2013-14 from the Open to the Northern Trust Open. From all that, I had 365 pairs of quartiles where a golfer had played at least four tournaments during each quartile. A graph of of those pairs is follows.

pairs of SGP quartiles

There was very little relationship between a golfer’s performance in one set of tournaments and their performance in the following set of tournaments (R=0.04, indicating a tenuous at best relationship). I had 61 quartiles with a performance > +0.50, averaging 0.72. Those quartiles played to only +0.12 in the next set of tournaments. In fact, in only 12 of those samples of > +0.50 performance did a golfer again average > +0.50 the next quartile. None of the six samples of > +1.00 SGP had > +0.52 SGP in the following quartile. In short, we should be very skeptical of elite putting performances over fairly short periods of time.

Now, when I said that Jimmy Walker’s performance was largely driven by luck I meant the “largely” part. I think it’s extremely unlikely that all of his putting performance can be explained by variance alone. Jimmy Walker has +1.20 strokes gained putting/round in 23 measured rounds so far this season. The observed standard deviation between 23 round samples for PGA Tour players is around 0.35 strokes. That means if an average (+0.00) putter plays an infinite number of 23 round samples, 68% of them will yield an SGP average of -0.35 to +0.35, while 95% of them will yield an SGP average of -0.70 to +0.70. In short, there’s a ton of variation between 23 round samples. For an average golfer, it wouldn’t be shocking for them to putt extremely poorly or very well over 23 rounds. Plugging that standard deviation (0.35), Walker’s 2013-14 SGP (+1.20) and Walker’s five year SGP average (+0.26) into a Z-score equation yields a Z of 2.7 which indicates <1% chance that Walker’s SGP is entirely due to chance. That means there is some signal in all that noise.

But how much? I consider myself a Bayesian in that I think it’s very important to compare any observed performance to our prior expectation for that performance. Up until October 2013, Jimmy Walker was an above-average, but not elite putter. Since then, in 23 rounds, Walker has putted out of his mind. Surely we should consider Walker a better putter than we did in October, but how much better? Fortunately, there’s a simple equation we can use to estimate how the 23 round sample should change our expectation for him. It’s ((Prior Performance)/(Prior variance) + (Sample performance)/(Sample variance))/((1/Prior variance)+(1/Sample variance)). Basically, this equation tells us how confident, statistically, we should be about a golfer establishing a new level of performance based on how far his performance is from the prior expectation and how large of a sample we’re dealing with.

We know the prior performance and sample performance from the previous paragraph. The sample variance is simply the 23 round standard deviation from above (0.35) squared (0.12). To find the prior variance, I was forced to run some simulations as my data was limited. I know the variance for 100 round sample is around 0.025, so the prior variance for Walker over his >300 rounds in 2009-2013 must be no greater than that. Simulations indicated to use a figure around 0.02.

Plugging those values into the equation yielded a new expectation for Walker of around +0.40. That’s significantly higher than his five year average, but also much less than what he’s done recently. The equation is saying that Walker’s been much better, but that 23 rounds isn’t nearly enough to say that he should be expected to continue to putt at an elite level. If we had just seen Walker putt at a +1.20 SGP level for 80 rounds, we’d be much more confident in him continuing to putt at an elite level.

The tl;dr here is that extremely good SGP performances over small samples (~4-8 tournaments) sharply regress to the mean in the following 4-8 tournaments. Sustaining the kind of putting Walker has shown recently is unprecedented over a large sample of rounds from 2013-14. Moreover, the expected level of variance of 23 rounds is very large. It would not be abnormal for an average putter to putt at a top 20 or bottom 20 level over 23 rounds. Considering all that, we should expect Walker to putt better over the rest of the season than he did in 2009-2013, but not nearly as well as he has since October.

We Need to Talk About Jimmy

After his win at last week’s Pebble Beach National Pro-am, Jimmy Walker has run his 2013-14 PGA Tour record to 3 wins, another top-ten, only 1 missed cut, and 1st place in the FedEx Cup standings. Prior to his win at the Open in October, Walker was certainly a strong PGA Tour player, but not widely considered among the elite golfers in the world. His world ranking peaked at 59th after the Players Championship in 2013, but has shot to 45th after winning the Open, 32nd after winning the Sony Open, and 24th this week. All of a sudden, Walker is entering tournaments as one of the touted favorites. What I’d like to do is to show where Jimmy Walker has come from and why you should be skeptical that he should be considered one of the Tour’s elite players.

Walker emerged as a PGA Tour regular in 2008 after bouncing around between the Nationwide Tour and PGA Tour between 2004-2007. Initially, he wasn’t a particularly good player. My Z-Score ratings have him at +0.16 in 2008, +0.16 in 2009, and -0.08 in 2010. For context, 0.00 is set as the average of all players who play on the Tour (down to the lowest qualifier, past champion, and club pro who competes in a tournament) while around -0.10 is the average player who holds a PGA Tour card. His seasons reflected those underlying stats; he was forced to re-earn his card at Q-School in 2008 and finished outside the top 100 on the money list in each of the next two seasons. Up to the beginning of 2011, Walker was a 32 year old who had never won a PGA tournament. It was as likely as not that he would fall off the PGA Tour in the next five years at that point.

But then something changed. Walker posted his best season in 2011 by actual results and underlying performance. His -0.24 Z-Score was well above PGA Tour average and he recorded four top-tens (including at Pebble Beach, Riviera CC, and the Sony Open). He followed that success up with a -0.31 Z-Score and five top-tens (again at Pebble Beach and Riviera CC) in 2012. Entering last year, Walker had posted consecutive solid seasons, but certainly no one was touting him as someone due to win a tournament. In fact, in this Golf Channel article from 2012 his name isn’t mentioned among eight guys (including Jeff Overton, Charlie Wi, and Brendon de Jonge).

Statistically up to 2012, Walker was decidedly a bomber. His average driving distance rank was 45th between 2008-12, while his average accuracy rank was 181st. He showed little ability to consistently hit greens, finishing no higher than 116th in GIR from 2008-12. Mostly, he putted well – he averaged 0.18 strokes gained putting over that period, solidly above PGA Tour average.

With all that context, Walker’s emergence looked unlikely as 2013 began. However, he played even better in the first half of the season, continuing a streak of 25 straight made cuts from the 2012 John Deere Classic to the 2013 Memorial. That run included four top-tens (again at Pebble Beach). From the Memorial onward, he missed six of nine cuts, crashed out of both Majors he competed in, and failed to reach the Tour Championship. For 2013 as a whole, Walker posted a Z-Score of -0.46 (including his fall swing) which is roughly what is expected out of a top 20 player in the world. The he went out in 2014 and won twice in four starts.

So did something change for Walker in 2013 that he carried over this year? Or is he suddenly a different player this season? In 2013, he remained wedded to distance above accuracy with his drives, finishing ~25th best in distance, but outside the top 150 in accuracy. He also putted about as well as he did in the previous five years, finishing with an average strokes gained putting of 0.27. What did change was his ability to hit greens. This article claims that Jimmy changed his aggressive style to chase pars on par 3/4s. It’s possible to imagine a more conservative game plan for attacking pins would lead to more greens hit, but his average proximity in 2013 was two feet closer to the pin than in 2012. What we’re likely looking at instead is a general improvement in Walker’s approach game. He was hitting more greens and hitting it closer because he was playing his irons better.

In his eight 2013-14 tournaments, Walker’s stats (adjusted for field and course conditions) are basically exact copies of his 2013 performance in terms of driving distance, driving accuracy, and greens in regulation. In fact, the only major statistical indicators that are different are his scrambling (surged from 60% to 65% this season) and his putting (he’s gained an additional +1.06 strokes on the field each round due to his putting). Now, obviously scrambling well is a typical result of putting well. I examined his proximity to the hole after the scrambling shot for 2014 and prior seasons to see if he was hitting it closer. Instead, he’s actually hitting it around 2 feet further from the pin, leaving himself more difficult putts to earn his par. From that, all I can conclude is that his putting results are driving all of his improvement from 2013 to this new season.

That conclusion is all well and good, but is it realistic to expect him to maintain such a putting improvement? In short, no. Since the Tour started tracking shot-by-shot data in 2004, only one player (Ben Crane 2005) has maintained a SGP above +1.00 per round. Most seasons, the leader is around +0.90 and those leaders are players who are demonstrated elite putters (Luke Donald, Brandt Snedeker, Greg Chalmers, etc.) who have multiple seasons of near that level of play. Walker only has one such elite season (+0.46 in 2012). Right now his SGP for 2014 is based on only 19 recorded rounds. There’s a ton of room for randomness to creep in over such a small number of rounds. In comparison, he has over 300 rounds of prior play that show that he is an above-average, but not elite putter. Being a proper Bayesian, that’s not enough to convince me that he’s significantly better going forward. At most, I’d place him as something like a +0.30 to +0.40 putter, enough to be in the top 20 putters on Tour, but not nearly the +1.33 figure he’s sporting so far.

Now that doesn’t mean Walker isn’t going to continue to be a very good player. He didn’t receive nearly the recognition he deserved over the past two seasons when he was legitimately playing at a top-50 in the world level. His three wins, 25 tournament streak of made cuts, and -0.36 Z-Score from 2011 to present are fantastic achievements for a guy who didn’t look like he’d ever contend for anything as recently as 2010. He’s has to be considered a favorite to earn a spot on the Ryder Cup team as a bonus. But no one should expect him to continue playing like he has since October. His putting is likely being driven by a ton of luck right now and luck cannot be relied on to stick around. Going forward, he’s probably not going to be able to putt nearly as well as he has; that doesn’t mean he’s not going to be successful, just that he shouldn’t be considered one of the favorites in a field with Dustin Johnson, Webb Simpson, Bubba Watson, Jordan Spieth, and Matt Kuchar.

How He Won: Jimmy Walker (Pebble Beach Pro-am)

Jimmy Walker did it again. After taking home both the Open and Sony Open to begin his season, Walker burst out to a huge lead after round 3 and survived a pretty poor 4th round to win by one at Pebble Beach. I wrote about Walker in my Thursday post, noting that he gained a lot on the field with two hole-outs for birdie from far off the green – overall scrambling 5/5 on Thursday. He kept that up at Monterrey Peninsula and Spyglass Hill, finishing Saturday having successfully scrambled 15 of 16 missed greens. Even considering his poor 2/5 on Sunday he finished at 81% for the tournament. The field, over all four rounds and three courses, scrambled at 56%; Walker gained over 5 strokes on the field just through his scrambling.

Walker’s other conventional stats were strong as well. He hit 72% of his greens for the week (field hit 63%) and out-drove the competition by 8 yards.

Thankfully this is the last multi-course event of the season so a clearer statistical picture will be available for the winners going forward. This week in particular I have no idea how much putting factored into Walker’s success because we don’t have Strokes Gained Putting numbers or even shot tracker data for Spyglass Hill or Monterrey Peninsula. As I noted on Thursday, Walker’s putting wasn’t particularly notable. His SGP figure was 0.76, which is great on average, but fairly low for being one of the best rounds of the day. His success was mostly driven by the aforementioned two hole-outs and a slew of approach shots hit close. Then on Sunday he putted horribly (-1.51 SGP). Despite generating 3.9 expected birdies, he only converted 3 of them.

Walker’s main issue on Sunday was leaving his birdie putts too far from the hole. He birdied 3 holes and had putts for par on 14 more (#10 he was forced to recover from the fairway bunker which cost him a stroke). Of those 14 par putts, he left his on #1, #12, and #13 beyond 10 feet – making bogey on all three holes. He almost did the same on #18 when he needed to par to win outright, but kept his par putt to 5 feet despite rolling it aggressively past the hole.

I hope to have more this week detailing just what Walker is doing differently this year that he didn’t last year, but  I don’t think I’ll find much. Walker rated very highly in the Z-Score model last year (and had five top tens) despite really not getting any attention (probably because he missed 6/9 cuts to close the season). Walker is just the third player in the last ten years to win twice before arriving at Riviera (counting his fall win is unfair to the competition). Phil began 2005 with two wins in six events before winning twice more, while Mark Wilson began 2011 with two wins in six events before basically reverting back to the average player he was prior to that run. It’s anyone’s guess what Walker will do the rest of the season, but with 3.6 million banked already, he should make arrangements to be in Scotland at the end of September.

Pebble Beach Pro-Am: Friday

Quick recap of the day’s stats:

All courses in the rotation played more difficult today, with a uniform increase in difficulty of 2-2.5 strokes across the board. Monterrey Peninsula played to 71.3, Pebble Beach to 74.1, and Spyglass Hill to 73.2. The uniform increase means there wasn’t much of an advantage in which courses a golfer played so far. We’ll see if that holds up tomorrow. Pebble Beach, which played as a fairly innocuous course on Thursday (71.6) revealed its teeth Friday. Driving distance plummeted by 9 yards which resulted in a GIR rate of 58%, compared to 66% on Thursday. Average proximity to the hole after approach was 43 feet, 8 more than Thursday.

Looking ahead to Saturday, Hunter Mahan and Jimmy Walker will move to the much easier Monterrey Peninsula course, while Jordan Spieth will play Pebble Beach. If the differentials seen on the first two days hold up, Mahan and Walker will play a course 2.5-3 strokes easier than Spieth, enough to make those two comfortable favorites going into the weekend.

For those playing Pebble Beach tomorrow, the stretch from #9-12 looms large. #9 and #10 are par 4s playing a third of a stroke over par, while #12 is a preposterously difficult par 3 playing a similar third of a stroke over par. Daniel Summerhays recorded perhaps the second best round of the day today, primarily by playing #9-12 at even par. After parring #9, he scrambled successfully from right off the green on #10, before generating birdie putts of 7 and 12 feet on #11 & #12. Summerhays beat the field by 5 strokes, most of that coming with his play from tee to green. Only Victor Dubuisson played better today (67, 7 strokes better than the field), though he relied heavily on his putter (>3 strokes gained there). Dubuisson dropped putts of 37 and 20 feet, but his shot of the day might have been his 2nd shot to 21 feet for eagle on #18. Unfortunately for the Frenchman, this round followed a disastrous Thursday where he blundered around Monterrey Peninsula four shots worse than the field.

Pebble Beach Pro-Am: Thursday

Just a short wrap-up of the important stats for Thursday:

The pro-am is played on three different courses, Monterrey Peninsula, Spyglass Hill, and Pebble Beach. Monterrey Peninsula is typically the easiest track;  on Thursday it played to 69.01 strokes. Spyglass Hill and Pebble Beach were more comparable at 71.15 and 71.62.

The driving stats were: 276.3 yards/77% fairways at Monterrey Peninsula, 282.5 yards/60% fairways at Spyglass Hill, and 278.6 yards/74% fairways at Pebble Beach [1]. Spyglass lived up to its reputation as having tough-to-hit fairways, though players got a little extra distance. It’s important to note that while Monterrey Peninsula is listed at only 6867 yards, that’s because it has a fifth par-3. Monterrey’s par 4/5 average hole length is actually 456 yards, longer than Pebble Beach (439 yards) and Spyglass Hill (449 yards).

Despite the extra length, Monterrey Peninsula’s greens were easy to hit at 80%. MP is one of the easiest courses in terms of GIR the Tour will visit all season. The other two tracks proved more difficult as Spyglass (66%) defends itself with the narrow fairways/rough and Pebble (68%) defends itself with microscopic greens. All three courses played easier in GIR terms than the average PGA track however. The proximity to hole stats from Pebble suggest that the competitors were hitting it to an average of 35.1 feet on their approaches, almost exactly PGA Tour average.

Notably among the leaders, Jimmy Walker posted a strokes gained putting of only 0.76, despite finishing 5.6 strokes better than the average golfer at Pebble Beach (meaning he gained 4.8 strokes elsewhere). Most importantly, Walker holed his scrambling shots on #10 and #14, from 40 and 21 yards. From the fairway from those distances the average golfer takes ~2.5 strokes to finish the hole, meaning Walker netted around 3 strokes on the field just from those hole-outs. Walker also hit a ton of shots close, generating a birdie probability of 4.4 birdies (this sums the expected probabilities of Walker birdieing a hole based on where his approach shot came to rest). He had putts of 5, 5, 6, 8, 10, and 10 feet for birdie, converting 4 of those in addition to his hole-outs.

The pros unsurprisingly eviscerated the two front-nine par 5s at Pebble Beach. #2 (502 yards) yielded a 4.40 average and #6 (513 yards) yielded a 4.49 average. Both had comically easy to hit fairways (79% and 76%) and over 90% of the field hit the green in regulation. It’s a cliche most places, but a par genuinely is almost like a bogey on those holes.

[1] – Driving distance stats for MP and SH include only the two holes designated to be measured each round. PB driving distance stats include all par 4/5s. This likely overstates the distance achieved on those two courses by around ~8 yards; PGA players last year achieved 8 yards more distance when measuring only two designated holes versus all par 4/5s.

How He Won: Kevin Stadler (Phoenix Open)

Most posts here are focused on the macro-level of how to predict performance. That’s my main interest and the most valuable research in terms of the big picture of golf analytics. However, occasionally it’s nice to delve into individual performances and look at how golfers win each week. This week, Kevin Stadler finally broke through and won his first PGA tournament at the Phoenix Open. Stadler’s performance over the 2008-Present period has been approximately that of the 150th best player in the world, though he’s played much better in the last two seasons. Guys like that (even with famous fathers) rarely play their way into a 4th round lead at a tournament, so it’s nice to see Stadler break-through.

How he won is interesting though. This post detailed some quick stats on how PGA tournament winners putted during the 2013 season. The average winner gained ~1.5 strokes on the field each round due to putting. The winner normally gains 14-15 strokes on the field during the week, so putting normally accounts for at least 40% of the winner’s strokes gained on the field. However, Stadler totaled just short of 2 strokes gained due to putting for the entire week, while he finished 14.6 strokes better than the field in total. I don’t have detailed figures for other tournaments at my fingertips, but he must’ve far outperformed the field in all other phases of the game to finish so highly while putting (comparatively) poorly among PGA tournament winners.

TPC Scottsdale is a fairly easy course overall, with the field averaging 70.6 strokes/round for the week. The field averaged 301 yards off the tee (well above PGA average of 287 yards), hit 59% of fairways (slightly short of PGA average of 59%), hit 68% of greens (PGA average of 64%), and successfully scrambled 57% of the time (PGA average 58%). It’s clear that a combination of easy distance and little penalty for missing the fairway made hitting the green more likely.

Stadler as a player is definitely a much better ball-striker/driver than he is at putting or scrambling. He’s finished near the bottom in strokes gained putting in the last several years and he’s finished outside the top 100 in scrambling three of the last five seasons. In comparison, he’s been above-average in both driving distance and accuracy in the last few seasons, parlaying that and his approach shot skill into rankings of 33/26/8 in greens in regulation. We’re talking about a clear top top tier player from tee to green.

This week, Stadler simply played to his strengths, out-driving the field by 8 yards, hitting 9% more fairways, and using that great driving to hit 10% more greens than the field. His proximity to the pin was also 5 feet closer than field average. It helped that he successfully scrambled 12 of the 16 times he missed a green, which likely gained him something like 3 strokes on the field. However, his ability to put the ball in the fairway, further than most others, and then hit the green won him this tournament.

Digging deeper on his final round, I attempted to estimate his strokes gained for different types of shots. Prior work in this vein is here and here. I’m pretty confident in my numbers overall because 1) the course played roughly average in difficulty on Sunday and 2) my strokes gained on putts figure is within 0.3 strokes of the official PGA Tour number. My numbers show that three of Stadler’s best four shots on Sunday were approaches to the green – his approach to 3 feet on #14, his drive onto #17 green, and his approach to 4 feet on #9. In total he gained +2.1 strokes with his par 4/5 driving (14 shots), +1.3 strokes with his approach shots (4 shots), and +0.5 strokes with his par 3 tee-shots (14 shots), while he lost -0.4 strokes on 3 short shots around the green. I show his putting as having gained him no shots on the field in total.

I can explore this further, but it’s likely that Kevin Stadler played unusually well from tee to green for PGA tournament winners. His driving was superb in both distance and accuracy (a rare but potent combination) and he cashed in on those great positions by knocking his approach shots on the green and close.