Tag Archives: OOTP

Baseball, Career Replay, OOTP

What if it was Called Sandy Koufax Surgery?

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Sandy Koufax was one of the most dominant pitchers in the history of baseball, and at the age of 36 was the youngest to ever be enshrined in the Hall of Fame.

Koufax (Source: Baseball-Reference.com)

The reason for his enshrinement at such a young age was due to his early retirement due to an arthritic condition in his elbow. He pitched the entire ’65 and ’66 seasons in extreme pain but still dominated, pitching over 320 innings in both seasons going a combined 53-17 with 699 strikeouts – and winning the Cy Young both years.

Koufax retired shortly after the 1966 World Series at the age of 30.

Dr. Frank Jobe once said that Koufax had basically the same injury as Tommy John, and that if he had developed the pioneering surgery ten years earlier (Dr. Jobe was already 41 by the time Koufax retired) the surgery would likely have been named after Koufax instead.

We always find it interesting to play out these “what if” scenarios that abound in baseball, so naturally we wanted to see what might have happened if Sandy Koufax had been able to extend his career.

As always, we used OOTP16, starting a historical league on January 1, 1967. In this world, Koufax became the pioneer for the ligament replacement surgery. Having undergone the surgery immediately after the ’66 World Series meant Koufax would likely be ready to play again by the beginning of the ’68 season.

Without Koufax, the ’67 Dodgers slipped back as their offense struggled, finishing the season 82-80, 17 games back of the Cardinals. But it was their hitting instead of Koufax’s absence that was the major reason, as the Dodgers hit a collective NL worst .236 with a lowly .627 OPS.

Koufax was ready to take his rightful place as the ace of the staff at the beginning of the ’68 season. His first start on Opening Day was against the Phillies. Whether rust or nerves got the best of him, he gave up 3 hits, a walk, and 3 runs in the opening frame. He settled down after that, giving up 7 hits over the final 8 frames for a complete game, but the damage was done and the Dodgers lost 3-2.

A no-decision and a tough luck 1-0 loss dropped him to 0-2 before Koufax really caught his groove, throwing 23 straight scoreless innings. He would improve his record to 4-3 before arm troubles would once again strike. He missed two starts with inflammation and struggled once he came back, uncharacteristically dropping 5 straight decisions, including 2 in which he gave up 5 earned runs. But he bounced back with a complete game shutout of Cincinnati to go into the All-Star break. Despite a 5-8 record, his 2.17 ERA, 0.98 WHIP, and 5.2 WAR was good enough for a spot on the All-Star team.

Meanwhile the Dodgers were rebounding from their lackluster ’68 season and were leading the NL at the break – but 5 other teams were within 4.5 games.

Right after the break Don Drysdale wrecked his elbow and would miss the remainder of the season. Without Drysdale and with a completely anemic lineup, the Dodgers couldn’t hold it together in the second half. They plummeted down to 6th place, 10 games behind the NL champion Phillies.

Koufax finished his comeback season with everything except his W-L record resembling his prior dominant years. He ended 11-16, but with a 2.07 ERA, 273 Ks in 270 IP, and a 10.2 WAR. He led the league in strikeouts, WAR, complete games (18), and shutouts (7). Voters didn’t hold his record against him, as he won his 4th Cy Young award.

In ’69 with the new NL alignment, the Dodgers still couldn’t quite get it altogether. Shortcomings at the plate were not addressed during the offseason and Drysdale would miss the entire season as well. Though they finished with a winning record (87-75) the Dodgers finished only 4th in the new NL West, 15 games behind the Astros.

Koufax was still in prime form, however. He finished the season especially strong, going 8-1 over his final 10 starts, 6 of which were complete games. Even with the higher pitching mounds introduced in ’69, at no point during the entire season was his ERA over 2.66. Once again he led the league in strikeouts (320) and WAR (14.0), going 20-10 overall with a 2.10 ERA. He would win both the Cy Young and MVP Award in that season.

The 1970’s arrived and the now 34-year old Koufax wasn’t losing a single step. Again he led the Dodgers’ pitching staff and dominated opposing hitters. A mid-August swoon where he gave up 26 ER over 5 starts was the only blemish, though that period was attributed to some lingering arm issues which caused him to miss 2 starts. Once he returned he went back to his old form, winning his last four decisions.

With Drysdale back, the two of them anchored the pitching staff. The previously anemic Dodgers lineup was bolstered by the production of Al Herrera, who hit 24 HR, a young Steve Garvey, and the acquisition of Earl Williams as the number one catcher, who smashed 40 HR. With all the pieces in place, the Dodgers won the NL West, going 92-69.

Koufax and the Dodgers would face the Phillies for the NL Championship, with Koufax pitching game 1 against Rick Wise. Wise outperformed Koufax pitching 7 shutout innings of 5-hit ball in a 3-0 win. The teams would split the next two before Wise and Koufax would square off again with the Dodgers facing elimination. This time Koufax came out on top 3-2, thanks to a two-run HR from Williams. Drysdale would finish them off in the 5th game and the Dodgers went on to face the Tigers in the World Series.

Koufax was excellent in his first World Series start since 1966, pitching a complete game 4-hitter with a sac fly as the only run scored. Unfortunately for him, the Tigers had acquired Jerry Reuss who pitched a shutout and the Dodgers lost 1-0. Once again the teams would split the next two games and Koufax would face Reuss in Game Four. Koufax pitched another complete game winning 5-1. The teams would again split the next two games setting up another Koufax/Reuss matchup for the 7th and decisive game.

Koufax cruised through the first 3 innings but in the 4th was forced to exit the game as his arm acted up yet again. The bullpen pitched admirably but a solo shot by Jim Spencer in the 5th was the only run of the game and the Tigers blanked the Dodgers to win the World Series. For Koufax it was a heart wrenching end to an otherwise brilliant season.

1971 was another down year for the Dodgers – their worst since 1958 winning only 75 games. There was one bright spot, which occurred on July 21st. Koufax took the mound and pitched a complete game 7-hitter against the Reds to win his 200th career game. He finished that season 17-12 with a 2.26 ERA and 11.9 WAR, good enough for his 6th Cy Young.

He would win 20 games again in 1972 to go along with a 2.58 ERA and an 8.3 WAR. On October 3rd he took the mound against the Atlanta Braves who got to him early and often. While he stuck it out to go 7 innings, he tied his career high by giving up 9 earned runs. That outing was topped off by a 2-run HR by Hal McRae. It would be the last pitch Koufax would throw, as he retired at the end of the season at age 36.

Coming back from Tommy John surgery extended Koufax’s career 5 full seasons and allowed him to reach the 200-win milestone along with winning 3 more Cy Youngs and one more MVP. He finished 252-143 with a 2.62 ERA and a career 116.8 WAR. While Koufax certainly wasn’t the only factor, he contributed to giving the Dodgers one extra NL championship than they did in real life, but his arm let him down in the most important game.

Koufax Stats

So would Koufax coming back have positively or negatively affected his legacy? He still didn’t rack up 300 wins, but his 6 Cy Young Awards would today be second only to Roger Clemens (7) – a number made more impressive by the fact that before his injury it was a combined AL/NL award. Add to that the likelihood that Tommy John surgery would have been called Sandy Koufax surgery makes us wish Dr. Frank Jobe had developed his groundbreaking surgery earlier.

 

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Baseball, OOTP

Why Babe Ruth Should Have Hit Leadoff

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Most baseball fans have a good handle on what type of hitter should in which spot in the batting order. For instance, a speedster should hit leadoff, your big slugger hitting cleanup, etc. Tom Tango, Mitchel Lichtman, and Andy Dolphin in their book “The Book” provided statistical analysis to optimize a batting order. They based their analyses on the number of plate appearances and the frequency of base/out states (e.g. how often the cleanup hitter comes to bat with runners in scoring position).

I won’t go through all the explanation as Tango, Lichtman, and Dolphin did a much better job. If you don’t want to read the original source, Beyond the Box Score did a great job providing an overview and Bluebird Banter went through some of the statistical analysis.

We wanted to see how that analysis would transfer to actual wins and losses. We looked at two scenarios using the greatest leadoff hitter, Rickey Henderson, and the greatest hitter of all-time, Babe Ruth.

As we normally do, we used OOTP16 and created 9 teams filled with average clone position players and pitchers. Then we imported the 1982 version of Rickey Henderson and cloned him to make nine Rickey’s – one for each team. For each team, he hit in a different spot in the batting order (including the ninth spot – there was no DH in this league so the pitcher batted eighth on that team).

Then we simmed almost 2000 games for each team, and (WARNING!!!! MATH TERM!!!) checked the binomial probability of each winning percentage to see if it was significantly different than what you might see flipping a coin 2000 times.

Here are the winning percentages for when Rickey hit in each spot in the lineup and the result of the binomial distribution calculation:

 

Henderson

All values were not significantly different from a coin flip (a value of less than .050 would have meant they lost more significantly more games and a value greater than .950 would have meant they won significantly more games).

Surprisingly, the second spot in the batting order was the closest to being significant – but in the opposite way than expected, with the team losing more games than they won when Rickey hit second. The team performed the best when Rickey hit sixth.

So after almost 2000 games (more than 12 full seasons), it didn’t significantly matter where Rickey batted in the lineup. Each team’s win total was no different than what you might expect from flipping a coin 2000 times.

We did the same for Babe Ruth, using the 1921 version of Ruth that won our League of All-Time Greats. With Ruth, we found different results.

Ruth

 

Hitting Ruth leadoff resulted in a significantly greater number of wins than expected by chance, due to the number of additional plate appearances by the leadoff hitter (4.66 PA/game as a leadoff hitter compared to 4.46 in the #2 spot, decreasing steadily down to 3.81 in the #9 hole).

Hitting Ruth second approached but did not meet the criteria for significance, while hitting Ruth 9th approached but did not reach significance for fewer wins than by chance. Surprisingly, hitting Ruth 5th did result in significantly fewer wins than expected over the course of almost 2000 games. We have no explanation for this, as Tango’s analysis says the number of plate appearances and the expected baserunner/out situations has the #5 spot as the fourth most important (after #1, 2, and 4).

Ruth’s RBI stats would have likely suffered by hitting him leadoff – in 12+ seasons he had 7% fewer RBIs than the Babe Ruth who hit 3rd and 18% fewer RBIs than the one who hit 4th – but the extra plate appearances would have likely led to marginally more home runs (4% more in our sim), and his relatively high on-base percentage would have had him on more for later hitters to bring in (the leadoff Ruth had 15% more runs).

Most  importantly hitting him in the leadoff spot might have meant even more wins for the Yankees.

 

 

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Baseball, Career Replay, OOTP

How Charlie Ferguson and a Toad Could Have Altered Phillies’ History

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Charlie Ferguson was a young promising pitcher for the Philadelphia Quakers in the 1880’s who more than held his own with the bat. SABR biographer Paul Hoffman claims that Charlie Ferguson was one of the “first tragic figures in major-league baseball” and could have “become one of the greatest players of all time”. Ferguson passed away at the age of 25 before the 1888 season from typhoid fever. His career stats were impressive.

On some days when he wasn’t pitching, he played in the field. In what would be his final season, he played 27 games at 2B, 5 at 3B, and 6 in the OF. In 300 plate appearances, he hit .337 with 85 RBIs, 13 SB, and an .886 OPS. He was well on his way to being an everyday player.

In his SABR bio, Hoffman notes that in 1925 – a whole 37 years after his death – a sports editor for the Philadelphia Evening Public Ledger called Ferguson “the greatest ballplayer who ever lived.” Hoffman concludes the bio by saying “One can only imagine how many games Ferguson might have won or what kind of everyday player he would have developed into had he lived to play an additional 12 to 15 years.”

Ferguson picCharlie Ferguson (from Baseball-Reference.com)

We decided to imagine by replaying history as if Charlie had never succumbed to typhoid fever.

We went back to 1888 using OOTP 2016 (and restructured the league to have accurate teams and rosters for that year). Charlie Ferguson then took his rightful place at the top of the rotation as well as their starting second baseman on days he did not pitch (all team settings were set to AI control except for the lineups and rotation for Philadelphia to accommodate for Ferguson playing every day. The game AI was in charge of everything else including all trades and signings).

The 1888 season for the Philadelphia Quakers as a whole did not start off too well. After a quick start they had fallen back to .500 by mid-May. Then the injury bug hit, and four regulars went down for the bulk of the rest of the year. While the Quakers rallied in the second half, they had dug themselves too deep a hole behind the Detroit Wolverines. Ferguson finished the season 30-23 with a 2.50 ERA and a 0.99 WHIP, leading the National League in WAR (10.1), innings pitched (479.2), most K/9 (4.50), and fewest BB/9 (1.05). He was tied for second in shutouts with 3. At the plate he hit a respectable .275 in 374 AB with 6 HR and 44 RBI, finishing with a 3.7 batting WAR, which was third on the Quakers.

His 1889 season ended early as he succumbed to injury on June 20th. While his pitching that year was not up to par (10-10, 3.61 ERA, 1.36 WHIP) his bat was more than making up for it. He had been leading the National League in OPS (.971) and was second in BA, OBP, and SLG when he went down.

In 1890, the now 27-year old was hitting his prime. The Quakers had now officially changed their name to the Phillies, and Ferguson continued to anchor their pitching staff. The Phillies were a game behind the Pittsburgh Alleghenys approaching the last series of the season. As luck would have it, they faced the Alleghenys in that series. Ferguson was given the ball for the first game of the three-game set. Unfortunately, Ferguson did not have his best stuff and he wasn’t helped by 5 Phillies errors. The Pirates won 7-2. They finished 91-63, one game behind Pittsburgh. That last start notwithstanding, Ferguson had bounced back from his injury to further his reputation, going 27-19 and leading the league in ERA (2.28) and WHIP (1.10). He finished 3rd in WAR (9.9). Playing right field when he wasn’t pitching, he again finished third on the team in batting WAR (3.9), hitting .283 with 73 RBI. If baseball back then had a most valuable player award and an award to honor the best pitcher, Ferguson would have won both of them.

1891 once again started slowly for both the Phillies, who quickly sank to 7th place and stayed there for most of the year. Management wouldn’t have it, and made the deal that would be celebrated for a generation. The Phillies traded four players: Billy Clingman, Fred Siefke, Bill Merritt, and Floyd Ritter to the Louisville Colonels for Toad Ramsey.

Toad, apart from having a memorable first name, is widely credited with inventing the knuckleball thanks to a tendon injury he had suffered in his index finger. In 1886 and 1887 he had two dominant seasons including one where he struck out 499 batters. In real life his career took a very quick downturn and he was out of the league after the 1890 season. However, in this world he was still the single most dominant pitcher in the American Association, winning 165 games over five years.

Ramsey picToad Ramsey (from Baseball-Reference.com)

The deal struck new life into the Phillies who went on a second half tear. In September they brought it to a new level, winning an incredible 16 straight games to end the season, with Ferguson winning his last 7 starts. But it was too little too late as they finished 2 games behind the Chicago Colts. But with two superstars leading the team, the time was ripe for the Phillies to finally make a push for a championship.

1892 turned out to be Ferguson’s best year yet. He tossed his first no-hitter on August 19th against the Pittsburgh Pirates, giving up only 1 walk. Ferguson and Toad Ramsey provided a dominant one-two punch that propelled the Phillies to their first ever National League pennant.* While Ferguson certainly shined, going 28-20 with a 2.24 ERA, 1.05 WHIP and 11.7 WAR, he was outdone by Toad who won the pitching triple crown, going 33-16 with a 1.59 ERA and 332 Ks.

With Toad and Ferguson, the Phillies cruised to the NL pennant again in 1893, finishing 13 games ahead of the Pirates. Ramsey won the pitching triple crown for the second straight year going an amazing 31-8 with a 1.97 ERA and 201 Ks. Ferguson again played second fiddle going 25-10 with a 3.25 ERA.

Toad would continue his amazing run, winning the pitching triple crown for an incredible third straight year in 1894, and fourth in 1895. But not all was stellar with Ferguson. In 1893 he had his worst season on the mound since his injury-shortened 1889 campaign, with the fewest wins, innings pitched, Ks, and WAR since that season. As their center fielder on days when he wasn’t pitching, Ferguson also had his worst year at the plate since his rookie campaign of 1884, hitting only .248 with 47 RBI and a 1.4 WAR in 508 plate appearances. Was the grind of playing every day getting to him?

Prior to the 1895 season in which Ferguson’s pitching stats declined farther, the decision was made to remove him from playing the field on his non-pitching days. Instead, Kid Gleason – who would often have the back end spot in the Phillies rotation – became a full time 3B, allowing Ferguson to focus solely on pitching. That move paid off as Ferguson had a bounce-back year at the age of 32, going 28-11 with a 2.75 ERA and a 9.2 WAR. The added rest also helped his hitting, as he topped .300 for the first time since 1889. More importantly Ferguson and Ramsey once again led the Phillies to a runaway NL pennant, as they won the league by 21 games over Cincinnati.

On May 9, 1896 Charlie Ferguson and the Phillies beat the Pittsburgh Pirates 17-1 for Ferguson’s 300th win, going the distance and giving up only 5 hits and no walks. Although the Phillies fell short of the pennant that season, Ferguson and Ramsey would win it again in 1897 for the Phillies’ fourth title.

Things went downhill for the Phillies as the century came to a close. They were leading the National League in late June of 1898 but then went on a 7-30 run to drop to last place despite excellent pitching from Ferguson and Ramsey. Ramsey would once again win the pitching triple crown (for an incredible 5th time in his career) and also notched his 400th win during that campaign.

Ferguson would get his 400th win in July of 1900 in a 3-2 win over the Chicago Orphans. The Phillies were back on top as they had signed Deacon Phillippe who now gave the Phillies three formidable starters. They won the National League pennant by 11 games over the Brooklyn Superbas.

That would be Ferguson’s and Ramsey’s last pennant. Toad would go on to win his 450th game in June of 1901, and Ferguson his in July of 1903 at the age of 40. On August 15th 1903, 39-year old Toad Ramsey beat the Chicago Cubs 9-4 for his 500th career win, but those two milestones weren’t enough as the Phillies finished third in the NL. In 1904 Ferguson would be removed from the rotation and relegated to mop up duties while Ramsey remained strong, winning his unprecedented 550th game September 27, 1905. and his 600th on July 31, 1908.

Ferguson would retire at the end of the 1905 season with a career record of 456-312, a 2.85 ERA and a 146.2 career WAR. His 456 wins would have put him second behind Cy Young, and his 146.2 career WAR would have been third behind Cy Young and Walter Johnson.

Ferguson Pitching

Toad would stick around for four more seasons, and would win his 600th game on July 31, 1908. He retired at the end of the 1909 season with a mind-boggling 603 wins, 5587 strikeouts, and a career 257.2 WAR. His wins and career WAR would top today’s all-time leaderboard, as would his 8636 career innings pitched. He would have been second all-time in strikeouts behind Nolan Ryan.

Ramsey Pitching

Meanwhile, without Charlie Ferguson and Toad Ramsey the real life Phillies would have to wait until 1915 for their first pennant and 1980 for their first World Series win.

* The World Series in its present form did not start until 1903. There was a championship series between the American Association and the National League up until the American Association folded after the 1891 season. While in some years there was either a split season championship series or a 1st vs 2nd place series at the end of the year, those permutations were not included in this sim, so there was no championship series from 1892 until 1903.

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Baseball, OOTP, Sabermetrics

Exploring the Impact of Fielding on Wins

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We’ve previously used Out of the Park Baseball (OOTP) to test out theories on hitting, such as how well OPS and Runs Created predict team win totals. The sabermetrics folk have made great strides in trying to create meaningful statistics for fielding, including Ultimate Zone Rating (UZR), Total Zone (TZ), and Defensive Runs Saved (DRS). We won’t go into great detail about what each of those do – FanGraphs does a better job than we ever could. But it’s not as easy to take the results of any of these statistics and translate it to what matters most – a player’s contributions to a team’s win total.

Baseball Reference does include DRS into its WAR calculations, but there’s always a danger when we’re extrapolating one step beyond any one particular calculation. For instance, DRS provides an estimate of runs saved which is then used in a calculation to estimate how many additional wins you might expect. But each of those calculations will have an error range and will be impacted by a myriad of other factors. We were looking to use OOTP for a more direct way to see how fielding impacts a team’s win total.

Our first foray simply looked at teams with different overall fielding capabilities. OOTP uses several different ratings for fielding, available when editing player characteristics. For instance for an infielder there is Infield Range, Infield Error, Infield Arm, and Turn Double Plays. Each rating is based on a scale of 1-250.

OOTP Fielding

We set up an 11-team league, with each player on each team having the same overall fielding ability but with each team varying in their abilities. So for instance one team had each player with a “1” rating for each fielding ability, while another team had each player with a “250” for each fielding ability. All players had the same league average ratings for hitting. All pitchers were equivalent pitchers with average ratings, and an average ground/fly ratio.

We simmed three seasons (with all injuries and player development turned off). Of course, the better fielding teams did better, but it was somewhat surprising as to how much better they did. The team made up of the highest rated fielders average a record of 113-49 with the team made of the lowest rated fielders went and average of 42-120.

What was also interesting were the number of errors committed per game. The best fielding team committed only .28 errors per game with the worst fielding team 1.31. We would have thought with everyone on the team having a 1 rating for every fielding attribute that they would have kicked and thrown the ball around more. But they still on average gave one extra out to the other team than the best fielding team. By comparison in 2014 the Reds had the fewest errors (.62 errors/game) while the Indians had the most (.72 errors/game).
The more important difference seemed to be in balls the fielders didn’t get to due to range issues. Defensive efficiency for the best fielding team was .768 while for the worst it was .606. In 2014 the best team DEF was .712 by the Reds and the worst was .672 by the Twins.

So let’s try to extrapolate this to some meaningful MLB differences. Since the original league took fielding ratings to extremes, we created a league with teams whose defensive ratings more closely resembled MLB. In this 9-team league, fielding ratings for all players ranged between 115 and 155 (the range in the original sim which more closely resembled MLB fielding stats).

Again we simmed three seasons, and the difference between the first and last place teams was again quite large. The top fielding team went on average 92-70 while the worst fielding team went 71-91 – a whole 21 game difference. Here are the results:

Final stats

Along with charts for errors/game compared to wins and team DEF compared to wins.

Def and wins

Errors per game

There are certainly many factors that can influence these results – most notably around balls hit in play (e.g. increased strikeout rate, HR %). But this certainly does suggest that getting a good grasp on accurately rating fielders can have a big impact on a team’s win total.

Baseball, OOTP

The League of All-Time Greats: Part 2

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In our last post, the League of All-Time Greats got underway, pitting the best all-time single seasons for batters up against one another in a 162-game season. April had finished with 2001 Barry Bonds slumping and 1921 Babe Ruth playing to form.

Ruth began to pull away in the Old Timers division in May, pulling off a 10-game winning streak including a three-game sweep of 2001 Sammy Sosa in which he outscored him 24-5. Bonds meanwhile clawed his way to the top of the New Timers division though his record didn’t top .500 until he beat Chuck Klein 3-1 on May 29th. Sosa, 1998 Mark McGwire, and 1932 Jimmie Foxx are bringing up the bottom of the whole league, with McGwire finishing May losing 8 of his last 9 and Foxx his last 6.

Barry really turned it around in June, going 20-10 while Babe kept pace going 19-8. By July 1st, it looked like the two of them would run away with it, with Barry up 10.5 games on Mark McGwire and Ruth 15.5 over Chuck Klein.

Most concerning for Bonds was his performance against Ruth. Barry was a meager 4-10 against him, getting outscored 89-52. This did not bode well for Barry’s chances at taking home the league title.
As the dog days of
summer rolled around though, Babe Ruth started to falter. Maybe his off-the-field antics magnified by having so many clones of himself in the locker room made him lose focus. Ruth played only .500 ball in August, though by then he had built up such a cushion over Chuck Klein that he still entered September up 14.5 games. Bonds, on the other hand, went 19-9 in August and built himself a 22-game lead over Sammy Sosa. But Bonds still could not solve Ruth, losing 4 of 7 against him in July and August.

Ruth got serious again in September pulling off a 12-game win streak to put any talk of distraction behind him. Both he and Barry pulled away as expected and finished the season more than 20 games ahead of the second place team in their respective divisions.
Season

In all, the Old Timers performed better than the “New” Timers, with Rogers Hornsby the only team in the Old Timer division to finish below .500 at 80-82. Mark McGwire meanwhile lost 102 games in the “New” Timers division.

Chuck Klein more than held his own going 84-78 and also won the batting title hitting .329 far ahead of Rogers Hornsby at .312. As a team though, Barry Bonds finished at .288 compared to Chuck Klein’s .286. Babe Ruth won the home run crown with a modest 30. Bonds topped the leaderboard for OBP (.400), wOBA (.387) and WAR (6.3).
Batting leaders

Next up: 1921 Babe Ruth vs. 2001 Barry Bonds in a nine-game World Series.

Baseball, OOTP, Sabermetrics

How well do wOBA and RC Predict Team Performance?

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Okay, so we’ve already done two posts looking at OOTP leagues filled with clones of two players: Slappy Slapstick and Sluggish Slugger. One showed that Sluggish, the low BA guy with sexy power, got walloped head to head by Slappy, the unsexy high BA no power guy. The second showed the same in an MLB environment, but only when Slappy and Sluggish both had OPS high above the league average. Sluggish was better in the MLB environment when both had league average OPS.

These sims showed the limitations of OPS – the first big sabermetric stat to make its way into national telecasts – certainly lacks somewhat in being a robust stat to value all players. Being an arbitrary stat simply combining OBP with SLG it’s not surprising that it lacks robustness. So we went looking for something that might work better.

So we turned to wOBA (weighted On-Base Average). This stat, created by Tom Tango, is based on the common sense premise that all hits are not created equal. The stat uses aggregate league totals to weight the value of each method of getting on base (a good description of wOBA and how it is calculated can be found at FanGraphs).

Unfortunately, OOTP does not deal with wOBA, so transferring this to the Slappy/Sluggish universe took a little bit of work. First, we ran one season with Slappy and Sluggish and calculated the weights for wOBA using league totals, and modified the abilities of Slappy and Sluggish to make them equivalent in wOBA and equal to the wOBA from the previous season. This, by the way, gave a rather sizable advantage in OPS to the Sluggers (.887 to .799). Their attributes stats predicted a line for the Slappy’s of .347/.452/.799 with no HR. The Sluggers were designed to go .253/.303/.887 with 42 HR.

Then we set them loose on 5 seasons – after each season we restored the league back so as not to mess with the weights for wOBA which change from year to year.

In this universe, the results were much closer. Teams made up of Slappy’s won an average of 85 games a year with teams made up of Sluggish Slugger’s won an average of 77. While this still might seem an advantage for the Slappy’s, you have to keep in mind we took two very extreme players – the Slappy’s were give the lowest possible rating (1) for gap and power attributes. Teams made up of Slappy’s never hit more than 2 home runs in any single season (and while I didn’t bother to comb through the individual box scores I would not be surprised if they were all inside-the-park jobs). Also, to create a league made solely of these players (along with clones of the same average pitcher), would greatly amplify any differences between the two groups. In a MLB environment where there is a variation in terms of players’ skills, these differences would likely be noticeable at all.

Then we did the same with RC (Runs Created), created by Bill James. This is in thanks to a suggestion made by a member of the Baseball Sim Addicts!!! Facebook group. As with wOBA this took a little bit of tweaking but both Slappy and Sluggish were made to have an equivalent RC of 99. Slappy’s stat line was created to be .371/.491/.862 with Sluggish’s working out to .220/.332/.868. After running 5 additional seasons we came out with nearly the exact same overall results: Slappy’s teams finished with an average of 84 wins with the Sluggers finishing with an average of 78.

wOBA and RC certainly did a lot better at evening out the two teams. One could argue that a difference of 7 or 8 games in a simulation designed to greatly exaggerate any differences goes a long way in demonstrating the robustness of the two metrics. And even with these small but consistent differences they are the best metrics available when applied to a typical ML team. It does lead me to wonder though what is behind the small (and in the real world likely meaningless) advantage the Slappy’s have. Do the formulas need some minor tweaking? Is there something in the OOTP game engine?

Update: After a night of thinking about it, it likely has to do with fielding. All players were set to equivalent fielding ratings – but they were all average. Since the Slappy’s had a greater number of balls put in play, it allowed for more opportunities for errors. Looking back at the yearly stats the Sluggers did consistently produce more errors, some of which would have led to runs. While I cannot say for certain at this time, it would look like that could very well be the deciding factor between the two teams.

Baseball, OOTP, Sabermetrics

Slappy’s vs. Sluggers Part 2

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My “real” job for the past 20 years has been a researcher. It’s a well-known saying that good research raises more questions than it answers. My previous blog post on singles hitters versus sluggers raised a few questions and comments. One comment came from through Twitter from Geoff M.:

Another well-known fact of research is that a single study will always have inherent limitations (or flaws, if you like). Using just a league of Slappy’s and Sluggers has the shortcoming of potentially amplifying any differences between the two. Just because it shows up in a league made completely out of those types of players doesn’t mean it would have any kind of noticeable impact in a league more representative of MLB.

So I went ahead with Geoff’s suggestion.

The original Slappy vs. Slugger sim gave each player an arbitrary OPS of .800. For my initial sim, I gave each player the league average after a 2014 MLB sim, which came out to .732. Turning off injuries, player development, and not allowing the AI to make any roster changes, I simmed 10 singular seasons with 1 team of Slappy’s, 1 team of Slugger’s, and 28 MLB teams. Both the Slappy and Slugger teams had Average Pitchers who were created with expected stats to be the league average.

The first set of 10 seasons was a bit eye-opening:

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In only 2 seasons did the Slapsticks win more games than the Sluggers, and as you can see, both teams made up of league average players were just utterly awful, losing on average more than 100 games a season.

This brought up the question of whether the OPS value used affected the outcome. So I did two additional sims: one replicated the original 4-team Slappy/Slugger league with everyone having a .732 OPS and the other replicated the Slappy/Slugger in MLB with each Slappy and Slugger having an .800 OPS.

First, the original 4-team league. Turns out changing the OPS to .732 made no difference, with season after season having the two teams of Slappy’s well ahead of the Sluggers (I also ran several more seasons of the original experiment just to be sure). The Slappy’s consistently won 90+ games with the Sluggers winning 60+. So the second level of OPS made no difference in that sim.

The MLB sim with both Slappy’s and Sluggers having .800 OPS was different. Here is the average performance of each team over ten seasons comparing both sets of sims:

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In this, the Slappy’s greatly improved their win total and beat out the Sluggers in every category (though OPS was very close). The Slappy’s even had two winning seasons. I wish I had a compelling answer for why the Sluggers outplayed the Slapsticks when each had a low OPS in an MLB environment but the Slapsticks won out in an MLB environment with a higher OPS while the sims with just the 4-team league always showed a consistent Slappy advantage.

At least with the four different sims we ran, the Slappy’s outperformed the Sluggers in three of them, though in a real-life environment it may depend on the value of OPS and not be a very straightforward answer.

If you have any hypotheses feel free to comment below or send us a tweet at @BullpenByComm.

Baseball, OOTP

Singles Hitters vs. Sluggers

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One of the classic baseball debates is the relative worth of Punch and Judy hitters and power hackers. Which one provides greater value to their team?

Using Out of the Park Baseball, we decided to put this to the test. Using their player editor feature, I created the following three players:

Slappy Slapstick
Projected stats
BA: .347; OBP: .452; SLG: .347; OPS: .799

Sluggish Slugger
Projected stats
BA: .216; OBP: .253; SLG: .547 (42HR over 660PA); OPS: .800

Average Pitcher
Projected stats
OAVG: .248; ERA: 3.75

Slappy had high ratings for BABIP, Avoid K’s, and Eye/Patience with the lowest possible scores for Gap and Power. Sluggish had high Gap and Power scores with low scores for other ratings. All other ratings (e.g. basestealing, fielding) were equal. The overriding factor for the main ratings was to get projected OPS to be equal, which I did as best as possible.

I cloned each player to fill up 2 teams of Slappy Slapsticks and 2 teams of Sluggish Sluggers. Each team had an 11-man pitching staff made up of Average Pitchers.

Then I set them loose on a 162-game season. Here is a snapshot of the final standings, with the results plainly clear.
Standings

The two teams of Slappy Slapsticks far and away beat on the Sluggers. The final stats showed that OPS ended up actually somewhat in favor of the Sluggers. Sluggers made up the entire top 5 and 8 of the top 10 league leaders in OPS.
OPS
(Click chart to enlarge)

RC27 (Runs Created per 27 outs) was in favor of the Slapsticks, with 7 of the top 8 leaders in that category.
RC Leaders
(Click chart to enlarge)

WPA (Win Probability Added) was also in favor of the Slapsticks taking the top 6 spots in that category.
WPA Leaders
(Click chart to enlarge)

It’s not possible from this exact run to know what sabermetric stat put the Slapsticks over the top as some (such as BABIP) were designed to be greater for the Slapsticks than the Sluggers. This simulation shows that OPS being equal, a singles hitter is more valuable in the end than a slugger, but it also shows that OPS, being a somewhat arbitrarily derived statistic, is not the defining stat to determine the value of a hitter or how that hitter might translate to team performance.