One of the coolest things about working for Sports Reference is access to the vast library of historical almanacs, encyclopedias, media guides, record books, etc. And for 50+ years, NBA books of this type have been unified in how they present the 1956-57 statistics for shooting guard Larry Hennessy. They all say the Villanova product played all 21 of his games that season for the Syracuse Nationals. However, thanks to our ever-expanding box score coverage, we noticed that we had record of him playing 19 games for the Nationals, after playing in two earlier games for the Philadelphia Warriors. Hennessy played for the Warriors on November 3 and November 9, 1956 before being waived and then signed with the Nationals on November 15. Accordingly, we have adjusted his career statistics to reflect this.

Part of the celebration of the National Football League's 100th anniversary included celebrating the top 100 in the league's history in various categories. Pro Football Reference has collected the major awards for display on the site: top 100 games of all time, top 100 teams of all time, and the NFL's 100th Anniversary All-Time Team. You can find them all linked on PFR's Awards index. The top 100 games list is unique in that we include a summary of what made the games notable, as well as a link to YouTube for games that the NFL has officially uploaded in full in case you want to go through history in the offseason.

If you have any questions or suggestions, feel free to contact us through our feedback form or Pro Football Reference's official Twitter account. Thanks for following us!

As we approach the beginning of the 2020 season, we have made some updates to our Wins Above Replacement calculations.  You may notice some small changes to figures as you browse the site. As always, you can find full details on how we calculate WAR here.

Defensive Runs Saved Changes

Last week, we updated Defensive Runs Saved (DRS) totals across the site with new figures from Baseball Info Solutions.  The new methodology involves breaking down infielder defense using the PART system - assigning run values to Positioning, Air Balls, Range, and Throwing.  Under the new system, an infielder’s total DRS is the sum of his Air Balls, Range, and Throwing runs saved, while Positioning runs saved are credited to the team as a whole.  You can read more about the updates in the Sports Info Solutions blog.  The PART system applies to all infielders since 2013.

Folding these numbers into WAR, we see some significant changes for individual player seasons.  The 2019 Oakland A’s get even more recognition for defense on the left side of their infield, with shortstop Marcus Semien gaining 0.7 WAR and third baseman Matt Chapman gaining 1.6 WAR from the new DRS numbers, lifting both players above Mike Trout and into second and third place respectively on the 2019 AL WAR leaderboard.  Chapman’s 1.6 additional WAR represents the largest single-season change in this update.

On the other end of the spectrum, we see Adrian Beltre with the most significant drop in this update, losing 1.5 WAR in 2015.

Since we use DRS to measure the quality of a team’s defense, these new values also impact pitcher WAR values.  Team total DRS changed by as much as 46 runs for a given team and season - the 2019 Dodgers defense improved from 75 DRS to 121 DRS by non-pitchers under the new system.  Once applied to a specific pitcher, however, the changes to WAR are much smaller in magnitude than the changes to individual fielders. The most extreme example is Hyun-Jin Ryu, who pitched 182.2 innings in front of the 2019 Dodgers defense.  Considering the Dodgers defense to be 46 runs better across the entire season, and considering that Ryu was the pitcher for 13.52% of the Dodgers’ balls in play in 2019, we adjust our expected runs allowed for Ryu by 6.2 runs for the season. After following the rest of the steps in our pitching WAR calculation, the end result is a drop of 0.3 WAR for the season.  All other changes to pitching WAR from this change to team defense are smaller than Ryu’s 0.3 WAR drop in 2019.

Park Factors

Park factors for 2018 have been re-computed to include the 2019 season, since WAR uses a three-year average for park factors when computing pitching WAR.  The most significant change here is the Miami Marlins, whose pitching park factor rose from 90 to 95 (where <100 represents a pitcher’s park and >100 represents a hitter’s park).  José Ureña sees the biggest benefit from this, with his 2018 WAR rising by 0.7 wins. All other changes to pitching WAR from updated park factors are smaller than Ureña’s 0.7 WAR gain in 2018.

New Game Logs from Retrosheet (1904-1907)

Last month, we updated the site with new data from Retrosheet, including new game logs for players from 1904 to 1907.  Having game-level data allows us to be more precise in our WAR calculations, since we can consider the specific ballparks a pitcher played in and the opponents he faced.

Take Christy Mathewson in 1907 as an example.  Prior to this change, we used the league average (excluding his team) of 3.36 runs per nine innings as the expected quality of his opposition.  However, with game-level data, we can see that Mathewson’s actual opponents averaged 3.55 runs per nine innings, showing that Mathewson was probably used strategically and started more games against better opponents.  Indeed, Mathewson pitched in 10 of the Giants’ 22 games against the league’s best offense, the Pirates, as well as 7 of the Giants’ 22 games against the Cubs, the NL’s second-best offense. Against the Dodgers and Cardinals, who each struggled offensively and scored fewer than 3 runs per game, Mathewson pitched in just 8 games total.

Knowing this about his usage, we can set more accurate expectations for how many runs an average player would have allowed under Mathewson’s circumstances.  By adjusting the quality of his opposition, we expect an average pitcher to have allowed about 7 more runs over the course of the season, resulting in a bump of 0.9 WAR in 1907.  All other changes to pitching WAR from new game log data are smaller than Mathewson’s 0.9 WAR gain in 1907.

Baserunning and Double Plays from Play-by-Play Data (1931-1947)

When calculating runs from baserunning and double plays, we use play-by-play data from seasons where it is complete enough to credit players for things like scoring from first on a double, advancing from first to third on a single, and hitting into fewer double plays than expected.

In the past, we have taken play-by-play data into account back to 1948 for baserunning and double plays, because the data further back than that has been incomplete and could give players an advantage in their WAR simply by having more complete play-by-play records than their peers.  As this data has become more complete over time, we have moved this cutoff back to 1931. The data is still somewhat sparse for games that took place during World War II (1943-45), but we felt it was worth including those years as well.

Pete Reiser of the Brooklyn Dodgers was skilled at taking extra bases, and it showed in the play-by-play accounts.  In 1942, he took extra bases at a rate of 55%, compared to the league average of 45%. Additionally, the Dodgers were tied with the Cardinals as the league’s top scoring offense, so Reiser had many opportunities to put his speed to use.  He scored from first on doubles a league-leading ten times in just 15 opportunities, and also scored from second on a single 24 times, good for 5th in the NL that year, in just 29 opportunities. Using this play-by-play data while computing WAR gives Reiser an additional 1.2 WAR in 1942.  All other changes to batting WAR from this change are smaller than Reiser’s 1.2 WAR gain in 1942.

Caught Stealing Totals from Game Logs (1926-1940)

When crediting runners for how many runs they contributed with their baserunning, we take into account their stolen base and caught stealing totals.  Caught stealing totals are missing for many players between 1926 and 1940, but we have complete game logs for players in that span.

In the past, when we didn’t have a caught stealing total for a player, we would estimate how many times they were likely to have been caught stealing based on the league’s stolen base success rate and the ways the player reached base during the season.

We are now using actual caught stealing totals from the players’ game logs, so there are some changes for players who did considerably better or worse than we had been estimating.

Take, for example, Freddie Lindstrom.  In 1928, the Giants third baseman stole 15 bases, but his official season stat line does not have caught stealing available.  Previously, we had estimated that he was caught stealing 11.57 times, based on everything else we knew about his performance and the league he played in.  However, game logs indicate that Lindstrom was caught 21 times, nearly twice as often as we had estimated. This difference gets folded into our baserunning runs calculation and results in a drop of 0.4 WAR.  All other changes to batting WAR from this change are smaller than Lindstrom’s 0.4 WAR drop in 1928.

Biggest Career Movers

Hall of Famer Ernie Lombardi sees the biggest change to his career WAR with this update, sinking from 46.8 WAR to 39.5 WAR, a drop of 7.3 wins.  The largest gain goes to infielder Lonny Frey, who picks up 5.2 wins. Both these players played in the 1930s and 1940s and saw big changes because of their baserunning.  Lombardi is known for being one of the slowest runners in baseball history, and this update shows that the numbers back that reputation. Frey was a fast runner in an era where stolen bases were rare, so he has been underrated to this point when it comes to his baserunning contributions.

On the mound, previously cited Hall of Famer Christy Mathewson is the big winner.  As discussed above, his WAR now recognizes how his manager would use him against tougher opponents, and he sees his career WAR jump by 2.2 wins.  Barney Pelty experiences the biggest drop of 1.9 wins.

We’ve highlighted some of the more extreme changes here, but to see full lists of the largest changes to season and career WAR totals, please see the spreadsheet here.

We're very excited about these new additions and hope you enjoy them as well. Thanks to Baseball Info Solutions for their contributions. Please let us know if you have any comments, questions or concerns.

The Play Index launched on Baseball-Reference.com over thirteen years ago and has been one of the most used research tools for baseball ever since. We've made a few additions over the years, but the tools have largely stayed the same and the price has only gone from $29/year to $36/year during those thirteen years.

The Sports Reference sites have continued to grow in traffic and advertising revenue over that time to the extent that the Play Index and our ad-free options are a very, very small portion of our revenue. Most of that is on us, as we have not done a great job of promoting and marketing tools that are highly valued by a dedicated group of users. The Baseball Play Index represents less than 4% of our revenue and ad-free memberships are less than 1%. In addition, the Play Index tools are complicated to maintain and manage, and quite frankly are a money-loser for us at this time. It's well past time to re-think how these tools are setup within our constellation of sites.

While Sports Reference is doing quite well overall, I'm not comfortable with having so much of our revenue dependent on advertising. We are very beholden to search engines continuing to send us traffic, and likewise the ad market can be fickle and difficult for a small to medium size operator to navigate.

Also, advertising on the sites does not make it easier for you to answer the questions you have. This is our primary mission. We maintain a relatively low level of advertising on the sites (at least compared to your regional newspaper), and we are loathe to add additional advertising units or more intrusive units. Some of you may use an ad blocker, in which case we are making no money from your use of the site at all, and the audience for our ad-free product has proven to be very small as well.

A subscription model aligns our interests much better with our users' interests as well. I realize that users are being asked to sign up for lots of subscriptions these days, but we feel the tools within the Play Index are so specialized and useful that they warrant a paywall.

So we are making some changes. The Play Index for each site will be moving to Stathead.com. Stathead.com will become the center for all of our subscription products. We expect these products to include tools and information beyond just a redesigned set of Play Index tools. This won't happen all at once, but we'll start with baseball and then proceed through the remainder of our sports. Also, we will be ending our ad-free product and instead Stathead memberships will have ad-free built-in. There just aren't enough users to justify a separate ad-free product. These changes will begin this month and continue through April on baseball and then continue with the other sites after that.

If you are a subscriber, we will make every effort to make certain you are happy with the options we provide to convert your ad-free or Play Index subscription over to Stathead including the option of a refund on your subscription. You will be hearing more from us about the changes over the next few weeks as we will email users directly.

During the deployment of these changes, the Play Index on Baseball-Reference.com (and the to be launched Stathead.com Baseball) will be free. They will continue to be free through at least April 30th. If you are a current subscriber to either of our products, we have already extended your subscription by an additional two months during this free period.

--sean forman

Basketball-Reference is now utilizing BPM 2.0, an improved version of Box Plus-Minus. Like the original BPM, BPM 2.0 is a statistic created by Daniel Myers which aims to estimate a player's performance relative to league average by using a player's box score information and his team's overall performance. On the site, BPM 2.0 will appear just as BPM did. On player pages it can be found in 'Advanced' section with columns dedicated to OBPM (Offensive Box Plus-Minus), DBPM, (Defensive Box-Plus Minus), BPM (Box Plus-Minus) and VORP (Value Over Replacement Player). OBPM and DBPM, when summed, equal BPM. They are all rate stats. VORP is a counting stat since its inputs are BPM and playing time. As before, these statistics are all available back to the 1973-74 season (though we're hopeful to eventually extend the measure back to 1951), when critical statistics such as blocked shots, steals and offensive/defensive rebounds were first officially tracked. For the nitty-gritty details on BPM 2.0, please see Daniel Myers's explainer.

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Thanks to the efforts of our friends at Retrosheet, we have added box scores back to the 1904 season to Baseball Reference. Previously, our game log coverage was back to 1908. Additionally, we have added partial play-by-play coverage for games games as far back as 1918. Previously, our oldest play-by-plays were from 1925. Since our last major Retrosheet update, the final two missing full play-by-plays of 1973 were added which means we now have complete PBP data back to that season now. In addition to the boxes and PBPs themselves, this update allows for a variety of new information searchable in the play index, as well as new rows of information in team/player/league statistics tables.

Here are some examples of the new information/searches available on the site.

• With box scores back to 1904, we now have game logs for the full careers of Hall of Famers Ty Cobb and Walter Johnson.
• We now have partial play-by-play coverage in all of Babe Ruth's seasons with the Yankees plus his final two with the Red Sox. This can be used in a lot of ways like seeing how well he did against various pitchers.
• Additionally, incomplete splits have been generated for player seasons from 1918 to 1924. In Babe Ruth's 1923 MVP season, from the play-by-play we have available he recorded a 1.554 OPS with runners in scoring position, a mark only Barry Bonds has reached since (min. 100 PA in this situation). Splits determined by play-by-play are searchable back to 1918 and more basic split data (home/away, month, etc) are searchable back to 1904 now.
• League-wide batting splits and pitching splits have been fleshed out with the new play-by-play data back for the years 1918-24.
• Batting Game Finder and Pitching Game Finder searches are now opened up back to 1904.
• Batting and Pitching Event Finder searches have also been opened up back to 1918. Of the games we have PBP for in 1918, Wally Pipp leads with 3 walkoff hits that season, for instance.
• Searches in the player and team streak finders now go back to 1904
• Win Probability, Baserunning, Situational and Batting Against tables are all available back to 1918 now.

If you have any questions about our data coverage, you can always see it here.

We're very excited about these new additions and hope you enjoy them, as well. Please let us know if you have any comments, questions or concerns.

And thanks again to Retrosheet!

After years poring over play-by-plays, watching videos (tough, I know) and reading thousands of game stories in newspaper archives, Basketball-Reference has compiled the first comprehensive list of every buzzer-beating game-winning shot in the history of the NBA and the BAA. To date, there have been 772 such shots in NBA history, including free throws with time expired. I'm defining game-winning buzzer-beaters as successful shots taken with the shooter's team tied or trailing which left no time on the clock after going through the net. These are true game-enders leaving no opportunity for the opponent to respond. As Tim Duncan knows, there are no such thing as game-winning buzzer-beaters that leave even 0.4 seconds on the clock.

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We have compiled every game-winning buzzer-beater in NCAA Tournament history. Since you cannot advance the ball to half-court with a timeout in college basketball, we have been lenient with how we define "buzzer-beating game-winner" and included all shots in the final 2.0 seconds of a game that put the winning team in the lead (so either tied or trailing at time of shot, and leading afterwards). However, it wasn't until the 1993-94 season that the clock automatically stopped on makes in late-game situations. Consequently, we have included some shots from 1993 and earlier that were made with more than 2 seconds left, but which left the opponent with 2 seconds or fewer left to respond by the time they chased down the make to inbound or call a timeout. An additional wrinkle is that the NCAA added tenths of a second to the clock for the 1990-91 season, but just had whole numbers for earlier seasons. One notable exception is Tate George's buzzer-beater against Clemson, since that was played in an NBA arena (The Meadowlands).

A few notes about how this data was compiled:

• • • • We read recaps or watched video of every NCAA Tournament game decided by three points or fewer. It's possible there was a game with free throws shot after time expired due to a technical foul (or something else) that we missed because the final margin ended up being 4+ points. Same with a three-pointer made at the buzzer on which the player was also fouled or a team that scored multiple times in the final two seconds.
      • The distances and assists listed are unofficial, gathered from play-by-plays, video review and newspaper accounts. Distances sometimes varied in different accounts, so we used the distances listed in the most comprehensive game stories we could find.

    If you have any additions to this data, please
    let us know

Earlier this season, there was some buzz that LeBron James had lost to Kemba Walker for the first time in their 29 head-to-head appearances. However, did you ever consider who LeBron loses most often to? If you set a minimum of 10 head-to-heads (regular season and playoffs), that would be Patrick McCaw, who is 4-1 against James in the regular season and 8-1 against him in the playoffs.

This is now more easily searchable thanks to Basketball-Reference's new Teammates And Opponents tool, located in the Frivolities section of the site. This will produce a list of either every player your choice, in this case, LeBron, has played against, or played with. As an example of the teammates function, here's a link to every player Russell Westbrook has played with. You may be surprised that among players who've been in 50 games with Westbrook, Hasheem Thabeet has the highest winning percentage with him.

So try out our new Teammates and Opponents tool and see what interesting results you can find! If you have any questions or suggestions, feel free to contact us through our feedback form.

On our sites that cover the pro sports, we at Sports Reference make an effort to include portraits of the players being covered, as there is power to attaching a name and stats to a face. With that in mind, we're happy to announce both the addition of headshots for players currently participating in the 2019-20 college basketball season, as well as pictures for 500 major historical players.

If you're subscribed to our College Basketball Stathead daily recap newsletter, you may have noticed we recently added the headshots of the top 5 players for each night to give your inbox a splash of color. (And if you're not subscribed but are interested, sign up here!) Luka Garza, Markus Howard, Xavier Tillman, they've all got their faces on the site now.

As for the historical players, check out Bill Walton when he was playing college ball instead of commentating on it, or Tony Bennett's big smile back when he was shooting threes for Green Bay instead of coaching the Cavaliers. Charles Barkley when he had hair, or David Thompson rocking the 'fro at NC State are also choice additions.

We do plan to incorporate historical coach headshots in the near future as well. If you have any questions or suggestions, feel free to contact us through our feedback form. Thanks for following us!