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.

Basketball-Reference has added a section to team pages that displays what players on the team finished in the top 20 of league leaderboards in various statistical categories. This section is found near the bottom of team pages, and is useful if you want a quick view of which players on the team were best in the league in a certain field. For example, the 2018-19 Golden State Warriors section will show you Kevin Durant and Stephen Curry's appearances on many leaderboards, with cameos from Klay Thompson, Draymond Green and Kevon Looney. A more stark example of a single-player dominated team would be the 2002-03 Minnesota Timberwolves, where Kevin Garnett was the lone Timberwolves player to appear in the top 10's of most of the league leaderboards, aside from stray appearances by Rasho Nesterovic and Troy Hudson.

Keep an eye on our Sports Reference Blog for more announcements of added features to Basketball-Reference! If you have any questions or suggestions, feel free to contact us through our feedback form.

With Chris Clemons and Mike Daum on the verge of becoming the 9th and 10th 3,000-Point scorers in major men's college basketball history, we have added a master list of every 2,000-Point scorer in major men's college basketball history to the Frivolities section of our college basketball site.

The list currently features 579 names, including 11 players active in 2018-19: Clemons, Daum, Jon Elmore, Tyler Hall, Fletcher Magee, Garrison Mathews, Matt Morgan, Nick Mayo, Tookie Brown, Jordan Davis and Justin Wright-Foreman.

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With last week's announcement of the 2018 All-Pro teams, we're pleased to report that we've added 2018 Approximate Value (AV) numbers to the site for all NFL players. Note that these numbers are just provisional right now; the final numbers will be released after the Pro Bowl rosters are finalized. However, there's already some interesting preliminary information to take a look at.

As of now, Patrick Mahomes is the clear AV leader at 22, with Jared Goff, Tyreek Hill, Mitchell Schwartz and Darius Leonard tied at 18. Leonard currently has the second-highest AV by a defensive rookie since 1960, only trailing Patrick Peterson's 20-AV season in 2011. As for Mahomes, his AV is second only to Priest Holmes' 2002 season in Kansas City Chiefs history.

Not sure what AV is? To learn more about PFR's attempt to put a single number on each player-season since 1960 (for the purposes of comparing players across position and era), check out this link. For this year's full AV leaderboard, go here.

We have added a new tool the Frivolities section of Basketball Reference: The Franchise Milestone Watch. This new tool will allow you to quickly select any active franchise and see if any players are approaching franchise records or are due to pass someone in the franchise record books. We are currently tracking most box score stats in this tool, with separate lists for the regular season and playoffs.

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On Pro-Football-Reference, we've made a small addition to our franchise coaching encyclopedia pages, adding a cumulative statistics table on top of our year-by-year results table. With this, it's now a little easier to look at franchise leaders in wins and playoff appearances. The wide berth between Bill Belichick and the rest of the Patriots' coaches is that much more evident on New England's franchise coaches page, and now there's a place on the Philadelphia Eagles' page to have Doug Pederson sandwiched by Greasy Neale and Buck Shaw in the franchise championships column.

If you have any questions or suggestions, feel free to contact us through our feedback form.

Regular Basketball-Reference users are well acquainted with the Play Index, which allows us to compare players across eras and slice and dice season-level data by many criteria. Today we are now introducing the WNBA Player Season Finder, which will be accessible from both the Play Index page and from our WNBA home page. We have WNBA stats back to the league's inaugural 1997 season, which means you can now search all of WNBA history with this tool.

Just like our NBA Player Season Finder, with the new WNBA tool you can do single-season, combined season and total season searches. For example, with the combined season search, you can now create franchise career leaderboards, maybe to see how far ahead in first place Tamika Catchings is among point scorers in Indiana Fever history. Or with the total seasons search, you can now execute a search like players with the most qualified seasons of 2 blocks per game; Margo Dydek and Lisa Leslie lead with nine seasons each finishing with that mark in their career.

Of course, current season stats are also searchable with the Player Season Finder, so you can give them some perspective with past stats. A'ja Wilson is burning up the league in her first WNBA season, currently averaging over 20 points per game. Here's a look at the others in WNBA history who finished with 20 points per game in their rookie season.

Stay tuned for more additions to the WNBA section of our site here on the Sports-Reference Blog. If you have any questions or suggestions, feel free to contact us through our feedback form.

Hockey-Reference has now added goaltenders' Shots Against data back to the 1955-56 season; we previously only had that back to 1983-84. This addition enables us to calculate season and career save percentages for all goaltenders, including several Hall of Famers. For example, a contender for greatest goalie of all time, Jacques Plante, is now listed with a career .9196 SV%, putting him at eighth all time and fifth among retired players. Plante also now occupies two of the top five spots in the single-season Save Percentage leaderboard. Johnny Bower is the top addition to the career Save Percentage leaderboard, as his career .9219 SV% puts him at third all time and second among retired players, only trailing Dominik Hasek.

We also now have data available that gives us precise Time On Ice numbers for goalies down to the second, going all the way back to the beginning of the NHL. As a result, there have been some changes to the Minutes Played data, and subsequent re-calculations of everyone's Goals Against Average. This pertains, mainly, to goalies prior to 1999. We always had Time On Ice data for goalies from 1999 onward.

We pride ourselves on providing the most accurate information available and we hope fans of NHL history enjoy this addition. Please let us know if you have any questions or comments.

We're happy to announce that you can now find every Hat Trick in NHL history on Hockey Reference. We have integrated these additions across many sections of the site.

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Thanks to the addition of nearly 50 seasons of historical player statistics, we have extended our statistical leaderboards for several categories through the beginning of the shot-clock era (1985-86). These categories include games, field goals, field goal attempts, free throws, free throw attempts, total rebounds, assists, steals, blocks, and points (as well as their "per game" versions). Additionally, we have extended all 3-point shooting leaderboards back through 1986-87, which was the season the NCAA adopted the shot.

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