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Archive for the 'Statgeekery' Category

LeBron James Passes Michael Jordan on All-Time Win Shares List

13th February 2018

Two years ago, LeBron James passed Michael Jordan to become the NBA's all-time leader in Value Over Replacement Player (which is calculated back to 1973-74). Now, LeBron has passed Jordan on the NBA's All-Time Win Shares list. Both players still trail Kareem Abdul-Jabbar, Wilt Chamberlain and Karl Malone, however.

For more nuanced perspective on how these five players stack up, please visit this detailed comparison from our Player Comparison Finder tool.

Posted in Announcement, Basketball-Reference.com, Data, Features, History, Play Index, Statgeekery | No Comments »

Era-Adjusted Stats Added to Hockey Reference Player Season Finder

15th January 2018

At Hockey Reference, we calculate adjusted stats in order to more accurately compare players from different eras and different goal scoring environments. With Alex Ovechkin approaching his 600th career goal, there has been some chatter about Ovi being the greatest goal scorer in NHL history.

So we thought this made for a good time to introduce the adjusted scoring statistics into the Player Season Finder tool in order to test this hypothesis. As it turns out, Ovechkin is easily the NHL leader in "adjusted goals" through 13 seasons of play. If you click on the link, you'll see he has 691 adjusted goals (through 1/15/18), while Wayne Gretzky had 607 adjusted goals through 13 seasons.

Read the rest of this entry

Posted in Advanced Stats, Announcement, Data, Features, History, Hockey-Reference.com, Play Index, Statgeekery | No Comments »

A Discussion of WAR Wherein I Ardently Attempt to Avoid any WAR-Related Puns

21st November 2017

This article assumes a lot of prior knowledge about the discussion of Wins Above Replacement, you can catch up here

First off, none of us are here without Bill James. We are all at our very best merely Chaucer or Joyce to his Shakespeare. All sabermetrics predating him flowed into his work and all sabermetrics after him carries echoes of his work.

To the discussion at hand.
Read the rest of this entry

Posted in Academics, Advanced Stats, Baseball-Reference.com, Stat Questions, Statgeekery, Trivia, WAR | 9 Comments »

How to Find Postseason Stats and Records on Baseball Reference

29th September 2017

Even though the temperature has been in the 80s here in Philadelphia this week, the calendar insists it's nearly October, which means it's nearly time for glorious postseason baseball! Following last year's World Series will be a tall order, but there are plenty of intriguing matchups lined up and no clear frontrunner to win it all.

To help you get ready, Baseball-Reference has plenty of postseason data. However, we've found that some users aren't quite sure where to find it or don't know quite how deep our postseason dataset goes. So, here's a quick primer on how to get all the information you need on MLB Postseason History. Read the rest of this entry

Posted in Baseball-Reference.com, Playoffs, Statgeekery | 7 Comments »

Neutralized Baseball Stats Back and Better Than Ever

26th May 2017

When we launched our new site three months ago, one of the casualties was the neutralized stats tables we printed on player pages. Those tables were originally built using code that had grown increasingly unwieldy and were not something we'd be able to adequately maintain moving forward. That said, we're happy to announce that we have rebuilt these tables and added new features, as well.

Read the rest of this entry

Posted in Advanced Stats, Announcement, Baseball-Reference.com, Data, Features, History, Play Index, Redesign, Statgeekery | 3 Comments »

Russ & Harden’s Oscar-Worthy Performances

5th January 2017

We all know Oscar Robertson became the only player in NBA history to average a triple-double when he averaged 30.8 PPG, 12.5 RPG and 11.4 APG in 1961-62. Though he didn't have the benefit of first-class air travel, modern nutrition and training techniques, he did have the benefit of playing for a team that averaged an estimated 124.9 possessions per game, while playing over 44 minutes per game. Though I don't want to diminish the stamina required to perform at a high level at such a frenetic pace, the point stands that there were more opportunities for a player to accumulate counting stats in 1962 than there are in 2017, where the average game has about 96 possessions.

Still, even if we adjust statistics to a Per 100 Possessions basis, few have ever matched Oscar's production. Robertson averaged an estimated 26.7 Pts, 10.8 Reb & 9.9 Ast per 100 possessions in 1961-62. At Basketball-Reference, we have estimated per 100 possessions statistics for every player back to 1973-74 (when the advent of tracking of offensive rebounds, among other stats, made the estimates more reliable). From 1973-74 to 2015-16, a total of just four player seasons (by three players) matched The Big O's Per 100 Possession statistics. They were by do-it-all forwards Grant Hill & LeBron James (twice) and then Russell Westbrook, last season. But, now, the 2016-17 NBA season has TWO players doing that. Russell Westbrook, in his most ridiculous form yet, and James Harden, who has emerged as the perfect player for Mike D'Antoni's relentless attack. But it's not that these guys are matching Robertson's production. They're obliterating it.

Let's first consider Westbrook's numbers.

And yet, saying that Westbrook is like a combination of peak Jordan's scoring with peak Malone's rebounding and peak Kidd's passing doesn't even do justice to how breathtaking his level of activity on the floor is.

As for Harden, the numbers aren't as eye-popping as Westbrook's, but his scoring and rebounding are roughly equivalent to peak LeBron James, except with 50% more assists thrown in. So, I guess that's pretty decent.

Query Results Table
Per 100 Possessions
Player Season Age Tm Lg PTS TRB AST
James Harden 2016-17 27 HOU NBA 37.8 10.9 15.9
Russell Westbrook 2016-17 28 OKC NBA 44.1 15.0 14.9
Russell Westbrook 2015-16 27 OKC NBA 33.9 11.3 15.1
LeBron James 2012-13 28 MIA NBA 37.5 11.2 10.1
LeBron James 2008-09 24 CLE NBA 40.8 10.9 10.4
Grant Hill 1996-97 24 DET NBA 30.9 13.0 10.5
Provided by Basketball-Reference.com: View Original Table
Generated 1/5/2017.
Tonight, the former teammates will square off for the 13th time in their regular-season careers, with each player owning six wins to this point. Harden is currently the overwhelming favorite to the win the MVP Award, but it's still early. Anyways, with their matchup tonight, we just wanted to take the opportunity to gawk at their absurd 2016-17 seasons.
Top Candidates Table
Rk Player Tm W/L% eFG% FT% TRB AST STL BLK TOV PTS Prob%
1 James Harden HOU .750 .528 .847 8.2 11.9 1.4 0.3 5.7 28.4 57.6%
2 Kevin Durant GSW .861 .594 .868 8.6 4.7 1.2 1.6 2.3 25.8 16.1%
3 LeBron James CLE .765 .559 .683 7.8 8.5 1.4 0.6 3.9 25.8 8.8%
4 Russell Westbrook OKC .583 .462 .821 10.5 10.5 1.4 0.3 5.3 30.9 5.2%
5 Stephen Curry GSW .861 .575 .929 4.3 5.8 1.7 0.1 2.8 24.2 3.0%
6 Kawhi Leonard SAS .800 .530 .918 5.9 3.1 2.0 0.6 1.9 24.0 2.9%
7 Chris Paul LAC .632 .543 .877 5.3 9.5 2.2 0.2 2.3 17.7 1.9%
8 Kyle Lowry TOR .676 .585 .854 4.9 7.1 1.4 0.3 2.9 22.2 1.6%
9 Giannis Antetokounmpo MIL .529 .559 .779 9.1 5.8 1.9 2.0 2.9 23.9 1.5%
10 Kevin Love CLE .765 .534 .872 10.9 1.7 1.1 0.4 2.1 21.8 1.3%
Provided by Basketball-Reference.com: View Original Table
Generated 1/5/2017.

Posted in Advanced Stats, Announcement, Basketball-Reference.com, Data, History, Ridiculousness, Statgeekery | 1 Comment »

2016-17 NBA Player Projections Added to Basketball Reference

18th October 2016

We have added 2016-17 NBA player projections, using our Simple Projection System, adapted from Tom Tango's Marcel the Monkey Forecasting System.

Please bear in mind that these projections are being published because (1) they were easy and (2) they were fun. That said, we do believe these results will hold up quite well when compared at the end of the season to other (and much more sophisticated) projection systems.

Since we're not controlling substitution patterns, all projections are for per-36 minutes statistics. Please use these responsibly and enjoy!

Posted in Announcement, Basketball-Reference.com, Data, Features, Statgeekery | Comments Off on 2016-17 NBA Player Projections Added to Basketball Reference

What the Heck is Corsi? A Primer on Advanced Hockey Statistics

13th October 2016

Good news for fans of zambonis, fighting, and the greatest video game of the 1990s: the NHL has finally returned! After a wild season last year, there are all kinds of juicy storylines to follow this year. Can the Pittsburgh Penguins become the first back-to-back Stanley Cup winners since the Detroit Red Wings of the 1990s? How will the San Jose Sharks bounce back from coming so close and falling short. Will Alex Ovechkin reach 1,000 goals? Can Connor McDavid build upon a promising rookie year and live up to the hype? What round of the Eastern Conference Playoffs will the Washington Capitals be eliminated in this year (I kid, I kid)?

This blog post will seek to answer none of those. Instead, this week, I wanted to dig into one of the major trends that's been sweeping across the NHL the last few years, among fans and front offices alike. I'm talking, of course, about the rise of advanced statistics.

If you're a sports fan, you're probably at least vaguely familiar with Moneyball and the advanced stat wars in baseball. And you may have read articles about how thinkers in other sports, like basketball, have used similar principles to deepen their understanding of the game. This movement has reached hockey in recent years, as researchers have uncovered several new ways of understanding the game beyond the traditional stats like goals, assists, and plus/minus. These new analytics can help us understand why a team is over or under-performing, and whether that performance is sustainable. They can also help us appreciate unsung players who do more for their team than we may realize, because they don't put up flashy traditional numbers.

So, with that in mind, here's some of the basics to get you started in the world of advanced hockey stats. Read the rest of this entry

Posted in Advanced Stats, Announcement, Hockey-Reference.com, Stat Questions, Statgeekery | 2 Comments »

Explaining our Handling of “Holds”

24th February 2016

UPDATE (Feb. 25, 2016): MLB has informed us that they will be updating Brach's 2015 holds total to 15 (matching us). MLB's Cory Schwartz commented: "We do credit Holds whenever the pitcher enters in a Save situation and leaves with the lead intact, so this was an oversight on our part."

It recently came to our attention that for the 2015 season, we credited Brad Brach with 15 holds. MLB, meanwhile, credited Brach with just 14 holds (NOTE: After reading this post, MLB has agreed that 15 is the correct number of holds for Brach in 2015). It was discovered that the difference was in the handling of the Orioles 5-4 win over the Mariners on May 21. Before we jump into the details, let's examine MLB's definition of a hold (bolding is ours, for emphasis):

"The hold is not an official statistic, but it was created as a way to credit middle relief pitchers for a job well done. Starting pitchers get wins, and closers -- the relief pitchers who come in at the end of the game -- get saves, but the guys who pitch in between the two rarely get either statistic. So what's the most important thing one of these middle relievers can do? "Hold" a lead. If a reliever comes into a game to protect a lead, gets at least one out and leaves without giving up that lead, he gets a hold. But you can't get a save and a hold at the same time."

UPDATE (Feb. 26, 2016): Please see MLB's updated Holds definition here

As you can see, this isn't really much of a definition at all. There's little in the way of criteria here, and it's also pointed out that the statistic isn't even official, anyways. In fact, there's enough confusion that MLB.com credits Cory Rasmus with 2 holds in 2015, but Elias (MLB's official statistician) credits him with 1 hold in 2015. We credit him with 2, for what it's worth. This "definition" provides enough room for interpretation that variance in recorded totals is not uncommon.

Being that the statistic is unofficial, explaining all of this might be a pointless exercise, but in an effort to be transparent, we at least want to point out what standard we are using to assign holds.

Our standard is to give a pitcher a hold any time they protect a lead in a save situation (meaning they could have been eligible for a save if they finished the game). Brach presents an interesting study in that May 21 game. Starter Chris Tillman pitched 3 innings and left with a 4-1 lead. Obviously, he was not eligible for the win due to Rule 10.17(b), as he did not complete 5 innings. Tillman was relieved by Brian Matusz, who allowed 2 runs in the 4th, but completed the inning of work and left the game leading 4-3, when Brach took the mound for the 5th inning. Brach completed 2 scoreless innings, but the Mariners tied it up in the 7th after Brach left the game. The Orioles eventually won the game.

With the benefit of hindsight, you could say that Brach would have been in line for the win (not the save) if he had finished the game, since he ended up being more "effective" than Matusz, which would make it nearly a lock that the official scorer would have given him the win. But, hypothetically, Brach could have given up 20 runs in relief, but maintained the lead, and earned the save (with Matusz getting the win). As unlikely as that scenario is, the point here is that we're not using hindsight in assigning holds. In our opinion, the opportunity for a hold is defined when you enter the game and is only removed retroactively if you are given the win.

To be as clear as possible: our policy is to credit a hold when a pitcher enters the game in a save situation and leaves with the lead (and is not later given the win by the official scorer).

As we bolded in MLB's definition of a hold, "If a reliever comes into a game to protect a lead, gets at least one out and leaves without giving up that lead, he gets a hold." It would sure seem to us that Brach's May 21st appearance fits that criteria.

Posted in Announcement, Baseball-Reference.com, FAQ, Ridiculousness, Stat Questions, Statgeekery | 10 Comments »

Try Our New Passer Rating Calculator

18th February 2016

We have added an NFL Passer Rating Calculator to our frivolities page which will allow users to calculate NFL passer ratings on the fly. All you need to know to calculate a passer rating are attempts, completions, yards, touchdowns and interceptions. A "perfect" rating comes out to 158.3.

Posted in Announcement, Features, Pro-Football-Reference.com, Statgeekery | Comments Off on Try Our New Passer Rating Calculator