Will there be a 62 at the U.S. Open?
by Ken Pomeroy on Wednesday, June 12, 2013
The 113th U.S. Open Championship starts tomorrow, though not much golf will be played on Thursday with heavy rain expected most of the day. This continues a trend at Merion where nearly a half a foot of rain has fallen over the past two weeks. The U.S. Open typically features the most difficult scoring conditions of the year primarily due to a combination of course length and firmness of greens and fairways. The latter defense has been removed by the weather and the former is also missing this week, what with Merion being the shortest U.S. Open course since 2004.
Because of this, scoring is expected to be among the lowest in U.S. Open history. Sportsbook.com lists an over/under of 270.5 (9.5 under par) on the winning score. Just once has a U.S. Open participant posted a better score – Rory McIlroy’s winning 268 in 2011.
Quantifying the bad greens of Quail Hollow and Mickelson’s dominance of them
by Ken Pomeroy on Friday, May 3, 2013
The story this week at the Wells Fargo Championship has been the poor quality of the greens. After a harsh winter and perhaps some questionable efforts to nurse them to health in recent weeks, the greens at Quail Hollow were borderline unplayable days before the tournament began on Thursday. Only the finest care and attention from the PGA Tour over he past week has allowed them to be playable.
However, barely playable is probably an accurate description of what the pros are facing this week. Several players withdrew earlier in the week, with Ian Poulter being the most transparent about his reasoning. On Friday, Sergio Garcia chipped on what would have normally been a six-foot putt due to some irregularities in his path. (ShotLink actually recorded Justin Hicks as missing a 7-inch putt while recording a double-bogey on the seventh hole yesterday, but I’m chalking that measurement up to a glitch.)
Fun with hole-by-hole stats
by Ken Pomeroy on Thursday, April 11, 2013
Which single hole was the most representative of a player’s performance in the first round of the Masters? It turns out it was the 13th. Dustin Johnson was the only player to eagle it an he finished one shot off the lead. The 38 golfers that birdied it finished with an average score of 71.7. The 40 players that parred it finished with an average score of 73.0. Not much difference there considering there was a one-stroke advantage built into the birdie group. But the 12 players that bogeyed it finished with an average of 77.0. Basically, if you played the hole poorly, you probably were not good by professional golf’s standards. The R2 for a player’s score on 13 and their final score was 0.53.
Your 2013 kPOY: Russ Smith
by Ken Pomeroy on Wednesday, April 10, 2013
It is my honor to announce that Louisville’s Russ Smith is the winner of the 2013 kenpom.com Player of the Year award. Smith posted a 109 offensive rating while using a whopping 32 percent of Louisville’s while he was on the floor. He also played a key role in the Cardinals’ defense, which was rated the best in the land in adjusted defensive efficiency.
After looking at shot chart data from last offseason, it seemed like a reasonable conclusion that it would benefit Louisville if Smith shot less this season. Smith did shoot slightly less, but mainly he elevated the Cardinals by making more of his many two-point attempts, approaching the D-I average in shots within six feet (53.7% vs. the national average of 54.5%) and two-pointers outside of six feet (33.5%, exactly the national average). Overall, Russ raised his two-point accuracy from 37.9% last season to 45.8% this season.
Three point accuracy by shot angle
by Ken Pomeroy on Monday, April 8, 2013
Sometime during the national semifinals Clark Kellogg remarked that some threes were easier than others. I can’t remember his statement exactly. It had to do with Wichita State getting open looks against Louisville and the particular shots they were getting were the easiest shots to hit.
In the NBA, it’s been documented that the corner 3 is the best value but at least some of that advantage is due to the irregular dimensions of the NBA three-point line. The college line is a fixed 20’ 9” from the center of the hoop at all points on the floor. Fortunately, this is easily testable since shot chart data is posted for hundreds of games at cbssports.com. To be exact, there are 3,435 games since the line was moved to its current distance for the 2009 season.
Final Four Paths and Wichita State
by Nic Reiner on Friday, April 5, 2013
The unpredictability of the NCAA tournament often leads to Final Four teams meeting via completely divergent paths. Sometimes we talk about a team reaching the Final Four because the bracket broke in a favorable way— a one-seed was knocked out early or a team drew a Sweet 16 date with an 11 seed. Ken Pomeroy recently wrote about how largely, at the top of the field, the best teams’ chances of a title are not affected much by their draw.
Nate Silver had a take on the seeding topic a few years ago, demonstrating that certain seeds counterintuitively and unequivocally are at a disadvantage. (For instance, he argues that a team would rather be saddled with a 10 seed instead of an 8, because of the ensuing path each team takes after winning its first game.) Both points are valid and provide background for this analysis.
A look back on preseason ratings
by Ken Pomeroy on Thursday, April 4, 2013
I try to avoid dropping names, but allow me to use a one-time Nate Silver exception. It was in 2007 when the old Basketball Prospectus site was launching that I spoke to Nate. One of his first questions was whether I had some sort of projection system for the upcoming season. I had to politely explain to him that was a silly idea. There is so much roster turnover and so many of the new players have no prior statistical track record, that it’s nothing like doing MLB projections.
But it really wasn’t as preposterous as I thought then. A few years later, I cranked out some preseason ratings based on little more than returning minutes, a team’s performance in recent seasons, and some recruiting information, and they didn’t look too bad. Actually, the top four teams in the first edition for the 2011 season managed to end up as one-seeds. That may never happen again as long as I’m doing this, but algorithm-based projections have since gained some measure of credibility with others joining the fray.
This season’s least-likely comebacks
by Ken Pomeroy on Saturday, March 30, 2013
Michigan’s comeback over Kansas, trailing by ten with 2:32 left and playing defense, had a 0.62% chance of occurring according to my win probability model. This was the 15th least-likely comeback of the season. (Ranking just ahead of Michigan’s own collapse to Penn State on February 27.) What follows are the 13 comebacks from this season that ranked as more unlikely.
Quantifying the dome-effect on three-point shooting
by Ken Pomeroy on Friday, March 29, 2013
With action moving to Cowboys Stadium tonight, there’s liable to be some discussion about how such a large venue affects the participants’ shooting. Or at least there should be, considering both Florida and Michigan are likely to be more dependent than normal on three-point shooting. Brian Cook at MGoBlog recently summarized what little research there is on the subject. A few weeks ago, John Ezekowitz put some stuff together attempting to quantify the effect of Princeton’s voluminous Jadwin Gym on shooting percentages. This is one of the better datasets pertaining to the issue since we can compare what Princeton’s opponents do between home and road games.
Why isn’t Ron Baker getting the Dominic Artis treatment?
by Ken Pomeroy on Tuesday, March 26, 2013
Explaining the game-to-game variation in a team’s performance is difficult. Sometimes, a team’s star player just plays well, or the opposing team plays more poorly than usual, or a team avoids foul trouble, or most of the dozen or so 50/50 calls go a particular team’s way. These explanations are uninteresting and not satisfactory, though, and so observers must come up with more meaningful explanations whether they are real or not. Be it a famous alum giving a pep talk before the game, a team focusing on starting the game better, or an injured player returning to the lineup.
Evaluating the impact of of a player’s injury is perhaps something that highly-trained humans can do better than computers. Not that computers can’t help in this regard, but it’s a complex problem, which is why I’ve been disappointed in the approach to this sort of analysis in some cases this season. Maybe it just seems like it started this season, but instead of critically evaluating how a player’s absence affects a team, the experts now just look at a team’s record with and without that player on the floor.