Category Archives: Oddities

Tied Up in Knots

Apologies for the gap between posts–travel and whatnot. I’ll hopefully have some shiny new content in the future. A narrow-minded, two part post inspired by the Bears game against the Vikings today:

Part I: The line going into the game was pick ’em, meaning no favorite. This means that a tie (very much on the table) would have resulted in a push. Has a tie game ever resulted in a push before?

As it turns out, using Pro Football Reference’s search function, there have been 19 ties since the overtime rule was introduced in the NFL in 1974, and none of them were pick ’em. (Note: PFR only has lines going back to the mid-1970s, so for two games I had to find out if there was a favorite from a Google News archive search.) (EDIT: Based on some search issues I’ve had, PFR may not list any games as pick ’ems. However, all of the lines were at least 2.5 points, so if there’s a recording error it isn’t responsible for this.)

Part II has to do with ties, specifically consecutive ones. Since 1974, unsurprisingly, no team has tied consecutive games. Were the Vikings, who were 24 seconds 1:47 shy of a second tie, the closest?

Only two teams before the Vikes have even had a stretch of two overtime games with one tie, both in 1986. The Eagles won a game on a QB sneak at 8:07 of OT a week before their tie, in a game that seems very odd now–the Raiders fumbled at the Philly 15 and had it taken back to the Raiders’ 4, after which the Eagles had Randall Cunningham punch it in. Given that the coaches today chose to go with field goal tries of 45+ even before 4th down, it’s clear that risk calculations with respect to kicking have changed quite a bit.

As for the other team, the 49ers lost on a field goal less than four minutes into overtime the week before their 1986 tie. Thus, the Vikings seem to have come well closer to consecutive ties than any other team since the merger.

Finally, a crude estimate of the probability a team would tie two consecutive games in a row. (Caveats follow at the end of the piece.) Assuming everything is independent (though realistically it’s not), we figure a tie occurs roughly 0.207% of the time, or roughly 2 ties for every thousand games played. Once again assuming independence (i.e. that a team that has tied once is no more likely to tie than any other), we figure the probability of consecutive ties in any given pair of games to be 0.0004%, or 1 in 232,000. Given the current status of an 32 team league in which each team plays 16 games, there are 480 such pairs of games per year.

Ignoring the fact that a tie has to have two teams (not a huge deal given the small probabilities we’re talking about), we would figure there is about a 0.2% chance that a team in the NFL will have two consecutive ties in a given year, meaning that we’d expect 500 seasons in the current format to be played before we get a streak like that.

I’ll note (warning: dull stuff follows) that there are some probably silly assumptions that went into these calculations, some of which—the ones relating to independence—I’ve already mentioned. I imagine that baseline tie rate is probably wrong, and I imagine it’s high. I can think of two things that would make me underestimate the likelihood of a tie: one is the new rules, which by reducing the amount of sudden death increase the probability that teams tie. The other is that I’ve assumed there’s no heterogeneity across teams in tie rates, and that’s just silly—a team with a bad offense and good defense, i.e. one that plays low scoring games, is more likely to play close games and more likely to have a scoreless OT. Teams that play outside, given the greater difficulty of field goal kicking, probably have a similar effect. Some math using Jensen’s inequality tells us that the heterogeneity will probably increase the likelihood that one team will do it.

However, those two changes will have a much smaller impact, I expect, than that of increasing field goal conversion rates and a dramatic increase in both overall points scored and the amount of passing that occurs, which makes it easier for teams to get more possessions in one OT. Given the extreme rarity of the tie, I don’t know how to empirically verify these suppositions (though I’d love to see a good simulation of these effects, but I don’t know of anyone who has one for this specific a scenario), but I’ll put it this way: I wouldn’t put money down at 400-1 that a team would tie twice in a row in a given year. I don’t even think I’d do it at 1000-1, but I’d certainly think about it.

Don’t Wanna Be a Player No More…But An Umpire?

In my post about very long 1-0 games, I described one game that Retrosheet mistakenly lists as much longer than it actually was–a 1949 tilt between the Phillies and Cubbies. Combing through Retrosheet initially, I noticed that Lon Warneke was one of the umpires. Warneke’s name might ring a bell to baseball history buffs as he was one of the star pitchers on the pennant winning Cubs team of 1935, but I had totally forgotten that he was also an umpire after his playing career was up.

I was curious about how many other players had later served as umps, which led me to this page from Baseball Almanac listing all such players. As it turns out, one of the other umpires in the game discussed above was Jocko Conlan, who also had a playing career (though not nearly as distinguished as Warneke’s). This raises the question: how many games in major league history have had at least two former players serve as umpires?

The answer is 6,953–at least, that’s how many are listed in Retrosheet. (For reference, there have been ~205,000 games in major league history.) That number includes 96 postseason games as well. Most of those are pretty clustered, for the simple reason that umpires will ump most of their games in a given season with the same crew, so there won’t be any sort of uniformity.

The last time this happened was 1974, when all five games of the World Series had Bill Kunkel and Tom Gorman as two of the men in blue. (This is perhaps more impressive given that those two were the only player umps active at the time, and indeed the last two active period–Gorman retired in 1976, Kunkel in 1984.) The last regular season games with two player/umps were a four game set between the Astros and Cubs in August 1969, with Gorman and Frank Secory the umps this time.

So, two umpires who were players is not especially uncommon–what about more than that? Unfortunately, there are no games with four umpires that played, though four umpires in a regular season game didn’t become standard until the 1950s, and there were never more than 5-7 umps active at a time after that who’d been major league players. There have, however, been 102 games in which three umpires had played together–88 regular season and 14 postseason (coincidentally, the 1926 and 1964 World Series, both seven game affairs in which the Cardinals beat the Yankees).

That 1964 World Series was the last time 3 player/umps took the field at once, but that one deserves an asterisk, as there are 6 umps on the field for World Series games. The last regular season games of this sort were a two game set in 1959 and a few more in 1958. Those, however, were all four ump games, which is a little less enjoyable than a game in which all of the umps are former players.

That only happened 53 times in total (about 0.02% of all MLB games ever), last in October 1943 during the war. There’s not good information available about attendance in those years, but I have to imagine that the 1368 people at the October 2, 1943 game between the A’s and Indians didn’t have any inkling they were seeing this for the penultimate time ever.

Two more pieces of trivia about players-turned-umpires: only two of them have made the Hall of Fame–Jocko Conlan as an umpire (he only played one season), and Ed Walsh as a player (he only umped one season).

Finally, this is not so much a piece of trivia as it is a link to a man who owns the trivia category. Charlie Berry was a player and an ump, but was also an NFL player and referee who eventually worked the famous overtime 1958 NFL Championship game–just a few months after working the 1958 World Series. They don’t make ’em like that anymore, do they?

In Search of Losses/Time

While writing up the post about the 76ers’ run of success, something odd occurred to me. The record for most losses in a season is 73, set by the 1972-73 76ers. As you might notice, that means that their loss count matches the a year of their particularly putrid season. Per Basketball Reference, only one other team has done this: the expansion 1961-62 Chicago Packers. (Can you imagine having a team called the Packers in Chicago now? It’d be weird for a name to be shared by a city’s team and a rival of another team in that city, but I suppose that’s how it was for Brooklyn Dodgers fans in the 1940s and 1950s, and maybe for St. Louis fans when the NFC West heats up.)

That Packers team went 18-62, though BR says they were expected to finish at 21-59. The only player whose name I recognize is the recently deceased Walt Bellamy, who was a rookie that year. They only hung on in Chicago for one more year before moving to Baltimore. They also put up 111 points a game and gave up 119, because early 1960s basketball was pretty damned wild.

So, this is an exclusive club, if a little arbitrary–there are 4 other teams from the 20th century who lost more games than the corresponding year, and obviously every team from the 21st has lost more than the year. Still, it’s a set of 2 truly terrible teams, but the next member is presumably going to be one of the very best teams in the league in the next five years or so. The benchmark will only get more and more attainable, so club membership will rapidly devalue. Regardless, I can’t see the members of those two teams popping champagne like the 1972 Dolphins when the last team hits 14 losses this year–though it’d be hilarious if they did.

Two Step Forwards, Two Steps Back

Reading about Reggie Wayne’s injury, I was moved to look at his page on Pro Football Reference, and noticed something funny: he has four carries lifetime, for a net rushing yardage of 0. (His carries are a loss of 4 in 2004, gain of 4 in 2007, a loss of 5 last year, and a gain of 5 this year in Week 3.) This led me to wonder: who’s the player in the NFL history with the most carries with exactly 0 yards gained? (Look at the list over at PFR.)

The answer, coincidentally, is Wayne’s old teammate Jim Sorgi, best remembered as the guy who would play occasionally late in the season when Peyton Manning’s Colts had locked in their playoff seed. His numbers (including kneeldowns and sacks) give him a pretty hefty 31 carries over his 16 games played. Somewhat poignantly, his last ever game, his first carry went for 12 yards, and he had four subsequent 1 yard kneeldowns to get to exactly 0.

Number two is Tony Bova, who played end and back before you needed modifiers with those positions for a few teams in the 1940s and clocked 21 carries for no net gain. Two other things make Tony a historical outlier: he played for two scab teams created from the flotsam of various ailing franchises, and he was blind in one eye (per Wiki), joining Jim Abbott, Pete Gray, Lance Armstrong, and Zach Hodskins on the list of notable athletes missing one body part that usually comes in pairs.

Skipping a few spots, tied for sixth all time is active leader Shane Lechler, with 6, though checking his game log suggests there might be some irregularities with how punter fumbles are counted. Regardless, given his status as one of the more accomplished specialists currently playing, it’s sort of fitting that he’d have a weird distinction to his name.

It turns out Wayne is tied for ninth and is (along with Dez Bryant) one of the two active players with four. Bryant, however, appears to actually get carries (four in 3+ years), so I can’t imagine he’ll stay on this list very long.

This is a pretty silly topic, and is in the same vein as everyone’s favorite pieces of trivia about Stan Musial, namely that he had the same number of hits at home on the road. It does raise at least one interesting question to me: how does one come up with a theoretical model to handle this? What odds should I get if I wanted to bet that Bryant (or Wayne) finishes his career with exactly 0 rushing yards? It seems like a pretty extreme form of random walk, but given the number of variables involved I don’t know how to rigorously model it. Perhaps something for a stochastic processes class. Ideas, anyone?