Michigan State’s back in the Final Four, and they take on Duke tonight at 6:09 on TBS. In the spirit of the Final Four, here are four good reads on the 2015 Spartans to get you ready for tonight’s game:
Go Green!
A No. 7 seed unseats a No. 2 in the NCAA tournament’s second round about twice every three years, but there was something about Michigan State’s upset of Virginia on Sunday that felt more routine than that. Perhaps it was the fact that the Spartans had toppled the Cavaliers just last season, but beyond that, no second-week tournament run from Michigan State qualifies as surprising at this point. As you might have heard, Izzo’s Spartans are now 13-1 all-time in the round of 32, and they’ve visited the Final Four more often (six times) than they’ve lost in the tournament’s opening weekend (five times).
Digging deeper into the numbers only solidifies Izzo’s reputation as Mr. March. A few years ago, FiveThirtyEight editor-in-chief Nate Silver wrote about how unlikely Izzo’s teams were to have consistently advanced as far as they did from the seeds at which they started — and that was at the very beginning of the five-season stretch (from 2010-present) where the Spartans advanced to four regional semifinals and one regional final. By any standard, Izzo’s teams tend to wildly exceed their expectations once the NCAA tournament commences. … Read More
(via FiveThirtyEight)
In the NBA, the apex of individual shooting is a 50-40-90 season — shooting 50 percent from the field, 40 percent on 3-pointers and 90 percent on free throws. Not many people can sustain that kind of accuracy from inside and out. Since the three-point line was adopted for the 1979-80 campaign, just six players (in 10 seasons overall) have hit 50-40-90 on their percentages.
Kyle Korver is doing his best to become the 11th. There are a handful of players within striking distance of 50-40-90, but only Korver, the Atlanta Hawks’ All-Star shooting guard, is on pace to achieve it. Korver is operating on a different plane of existence right now — shooting 51.2 percent from the field, 52.3 percent on 3-pointers and 91.1 percent from the free-throw line. He could have the first-ever 50-50-90 season. … Read More
(via FiveThirtyEight)
The NFC South’s playoff representative probably will finish the regular season with a 6-10 record, unless Carolina defies the odds and makes it in at 6-9-1. And while NFL analysts often are too ready to call a game a “must-win” game (week 4?), with two regular-season games left, the NFC South has gifted everyone a true must-win game, at least for one participant.
If the currently 5-9 Atlanta Falcons want to make it to the playoffs, they simply must beat the Saints in New Orleans on Sunday.
New Orleans is just a win better than Atlanta at this point, but the Falcons beat the Saints in a fun overtime game back in week 1, and the Saints, which are the hosts of this weekend’s rematch, are just 3-4 at home. Of course, the Falcons, which are sort of weirdly 4-0 in the division, are just 2-5 on the road, so who knows. If Atlanta is going to win, as it must to keep its seemingly improbable postseason hopes alive, one has to think that it will need both of its star receivers, Roddy White and Julio Jones, on the field on Sunday.
Red Klotz, the founder and longtime coach of the Washington Generals, the Harlem Globetrotters’ perpetually feeble opponents, died at age 93 last week (I highly recommend Joe Posnanski’s remembrance). Klotz’s all-time record as a head coach of the Generals and their namesakes was something like six wins and 14,000 losses — they lost 99.96 percent of the time.
How exactly did the Generals lose so consistently? How much of it was their conceding games on purpose, as opposed to simply being really bad at basketball?
Let’s first get a sense for how good the Globetrotters were. … Read More
(via FiveThirtyEight)
Most jr.-tennis coaches are basically technicians, hands-on practical straight-ahead problem-solving statistical-data wonks, with maybe added knacks for short-haul psychology and motivational speaking. The point about not crunching serious stats is that Schtitt . . . knew real tennis was really about not the blend of statistical order and expansive potential that the game’s technicians revered, but in fact the opposite — not-order, limit, the places where things broke down, fragmented into beauty. That real tennis was no more reducible to delimited factors or probability curves than chess or boxing, the two games of which it’s a hybrid. In short, Schtitt and [Incandenza] found themselves totally simpatico on tennis’s exemption from stats-tracking regression. Were he now still among the living, Dr. Incandenza would now describe tennis in the paradoxical terms of what’s now called “Extra-Linear Dynamics.” And Schtitt, whose knowledge of formal math is probably about equivalent to that of a Taiwanese kindergartner, nevertheless seemed to know what Hopman and van der Meer and Bollettieri seemed not to know: that locating beauty and art and magic and improvement and keys to excellence and victory in the prolix flux of match play is not a fractal matter of reducing chaos to pattern. Seemed perversely — of expansion, the aleatory flutter of uncontrolled, metastatic growth — each well-shot ball admitting of n possible responses, n^2 possible responses to those responses, and on into what Incandenza would articulate to anyone who shared both his backgrounds as a Cantorian continuum of infinities of possible move and response, Cantorian and beautiful because infoliating, contained, this diagnate infinity of infinities of choice and execution, mathematically uncontrolled but humanly contained, bounded by the talent and imagination of self and opponent, bent in on itself by the containing boundaries of skill and imagination that brought one player finally down, that kept both from winning, that made it, finally, a game, these boundaries of self.
David Foster Wallace, Infinite Jest 81-82 (Back Bay Books, Nov. 2006) (1996).
In tennis, the better player doesn’t always win. Sometimes, she loses in straight sets.
Imagine if basketball, football or hockey games were decided by which team outscored the other in the most periods. Get outscored by 20 points in the first quarter, and it’s no problem, you just have to eke out the last three by a point each to take the game.
That’s sort of how tennis works. Win more sets than your opponent, and you win the match — even if your opponent played better throughout. These anomalous results happen rarely, but more often on grass, the surface of play at Wimbledon, which started this week.
…
Wacky outcomes like [Rajeev] Ram’s pair of lottery matches happen more often at Wimbledon than at the other Grand Slams. Since 1991, 8.8 percent of completed Wimbledon men’s matches have been lottery matches, won by the player who was less successful at protecting his serve than his opponent. At the other three Grand Slam tournaments, that proportion ranged between 6.4 percent and 6.6 percent, according to data provided by Jeff Sackmann of Tennis Abstract.
…
The sport’s time-tested scoring system has many virtues, even if total fairness isn’t one of them. Its symmetry makes players alternate the deuce and advantage sides, switch sides of the net, rotate serving and returning. It guarantees that a player trailing by a big margin gets all the time it takes to stage a comeback, provided she performs well enough to earn that time. It keeps matches that are lopsided short, and lets close matches take all the time they need.
Carl Bialik, “An Oddity of Tennis Scoring Makes Its Annual Appearance at Wimbledon,” FiveThirtyEight.com (June 25, 2014, 7:31 a.m.).
Part of the reason baseball is so susceptible to statistical analysis is that the season is long enough for players’ and teams’ statistical averages to settle out and meaningfully describe their performance. Another reason is that the game itself is comprised of isolated interactions. No other sport is so susceptible, but the reasons appear to be different in each case. Basketball may be next up, held back only by our (diminishing, thanks to technology) inability to track and store data. Hockey statistics are thought to be less meaningful because the season isn’t long enough for the random bounces of the puck to settle out from the averages.
To my poorly informed knowledge, advanced statistical analysis has made few inroads into tennis. Part of the reason for this may be that tennis’ scoring structure, alluded to in the second passage above, does not as easily allow for the clean, direct reflection of averaged rates of good things or bad things in individual (and therefore aggregated) match outcomes. On the other hand, maybe looking to a statistical rationale for an explanation of statistics’ inability to aid in the understanding of tennis is futile. Or at least I think that’s what the first passage means. Continue reading
Recife, Brazil, site of today’s final group-stage match between the United States and Germany, is under water. I’ll leave the real soccer talk to Brendan and Marcus (and Chris)– here’s the latest episode of the ALDLAND Podcast— and proceed with the essential information.
If the Americans beat or tie Germany, they’re into the knockout round. If the U.S. loses, though, they’ll need one of a few different outcomes in the Ghana-Portugal match, which will be played simultaneously. This chart from FiveThirtyEight summarizes what Ghana-Portugal outcomes will allow the U.S. to advance despite a loss to Germany:
Both matches begin at noon Eastern.
Following the San Antonio Spurs’ dominant win over the Miami Heat in the NBA finals, FiveThirtyEight decided to examine whether the popular narrative about the winners and losers– that the Spurs played a more complete, team-oriented style of basketball the Heat, increasingly reliant on their solitary superstar, could not combat– was borne out in the numbers. They did this by comparing the relative usage rates (USG%) of the teams’ lineups. Plotting the difference in USG% between each team’s “top” player, the one who “used” the most possessions to either shoot, be fouled, or commit a turnover, and each successive player, should show how well the team spread the ball around. A team that did a good job of sharing the ball should plot a flatter line than a team that did not. FiveThirtyEight’s chart supported the popular narrative: San Antonio’s line was flatter than Miami’s, and the league average, while Miami’s line topped both.
As FiveThirtyEight pointed out, this isn’t how NBA championships are supposed to be won. As much as the Heat’s assemblage of its “big three” was seen as groundbreaking, it fit the narrative that grew out of Michael Jordan’s Bulls and Kobe Bryant’s Lakers (and certainly existed before Phil Jackson coached both of those teams to multiple championships) that the NBA was a star-driven league, and the way to win championships was to have a superstar. The Heat simply presented as an extreme version of that reality, with little in the way of supporting cast members.
FiveThirtyEight only compared this year’s teams, but the article made me wonder how the last NBA champions who deviated from the star-heavy model– the Detroit Pistons team that won it all exactly ten years ago amidst a solid run– compared statistically to this year’s Spurs.
I tallied the numbers using Basketball-Reference‘s team playoff data, sorted by USG%. Before doing so, though, I made an executive decision to omit data from players who appeared in fewer than ten playoff games that year, which swept out Austin Daye (one game for the 2014 Spurs) and Darko Milicic (eight games for the 2004 Pistons). The resulting plot lines for each team are essentially equally flat:
For perspective, keep in mind where the Spurs’ line– red on my chart, black on the one above– is situated relative to the rest of the (2014) league. It seems these Spurs and those Pistons were on the same page when it came to playing team-oriented basketball. Meanwhile, Miami is discussing adding Carmelo Anthony for next season. Anthony has been in the top ten in the league for USG% in nine of the past ten years.
Found this from FiveThirtyEight:
With the Stanley Cup finals set to start tonight, I thought this would be a fun game to play, especially for hockey fans whose teams are done for the season.
For me, the picking went pretty easy, probably because there are lots of good combinations here. I went with Ken Dryden ($2); Lidstrom, my favorite player, potentially overvalued but always undervalued while he played ($5); Chelios ($1); Mr. Hockey ($5); Super Mario ($4); and John Bucyk, never of whom I have heard ($1). (I originally had Shanahan at LW before realizing I needed two defensemen, hence Cheli and Mr. Bucyk.)
FiveThirtyEight offers a team “formed from an advanced stats point of view.” In this case, that mostly means referencing Goals Versus Threshold (“GVT”), a WAR-like statistic that seeks to present “the value of a player, in goals, above what a replacement player would have contributed.” Their picks:
Post your team in the comments below, and cast your predictive vote for the outcome of this year’s Stanley Cup finals right here:
ALDLAND 