Tangotiger Blog

Thursday, June 18, 2020

Floating Replacement Level

This discussion is easier to think of it for hockey: When Sidney Crosby goes down, his 22 minutes gets picked up by the other 11 forwards (1 minute each) and the 13th forward (11 minutes). So basically, Crosby gets replaced by 50% an average Penguins forward and 50% the bubble player.

On the other hand, when the 12th forward goes down, his 11 minutes gets picked up totally by the 13th forward. Same thing with the six defenders, or with the goalie.

When it comes with baseball, the concept of chaining would also apply, BUT NOT AS MUCH, as Patriot describes very well here (look for the section titled Chaining).  In hockey, players are much more fluid in terms of giving out playing time.  There's 120 minutes to give out to the defenders.  When one guy goes down, everyone below him steps up a bit, getting a couple more minutes, and the 7th player slides into the 6th slot.  With baseball, it's somewhere between goalie and defender: not as rigid as a goalie, but not as fluid as a defender.  You could slide someone up the batting lineup, but you wouldn't necessarily slide the regular 2B to SS.  It would be too unfamiliar.

And so, in the Crosby example, where you could argue it's basically half way between average and bubble, in baseball, it's going to be much closer to the bubble line, even for the top-end player.  And so we kinda take the lazy way out and apply 100% the bubble player.  But don't think that's RIGHT.  It's just EASY and close enough.  Be careful in applying the concept to other sports like hockey or basketball.

If you want a thought exercise: if your active roster was 40 players or 100 players in MLB, NHL, or NBA, would you take the LAST player as the bubble player?  No.  Then we can see how the easy way we applied on a 25-player roster is the WRONG way. It won't be close enough to right.  It'll be close enough to wrong.

So, you just have to be careful to understand WHY we made the choices we made, and see how it can apply to your circumstances.

Thursday, April 02, 2020

Do fans prefer small or large post-seasons?

​I asked that question of NHL, NBA, NFL, CFL, and Euro soccer fans. And to guage their interest in a tiny to wide open post-season, I offered stark choices: either 2 teams, or 75-80% of all the teams. No middle-ground. When the chips are down, are you a small-playoff or big-playoff fan?

I’ll start with NFL. I first asked to consider an 18-game season (which is more than the current 16, but it’s been talked about forever and it’s in-line with the CFL). By a 70/30 margin, those fans preferred a 2-team playoff (in other words, play right away for the Super Bowl) than a 24-team playoff. In other words, by going to 18 games, the fans did not have an appetite for an extended playoff season.

However, when I suggested an 8-game season, the tables were reversed: By a 60/40 margin, those fans preferred a 24-team playoff to a 2-team playoff. That is, when the regular season is too short, the fans would like an extended playoff season.

Logically though, 100% of fans should have preferred the 24-team playoff. After all, that would suggest another 4 or 5 rounds of playoffs, meaning that the bottom teams would play 8 games, while the rest of the teams would play 9 to 13 games, depending how far they go into the post-season. If you have an appetite for an 18-game regular season, why would you not want an 8-to-13 game regular+post season?

Anyway, so the midpoint is 12 games: if you have a 12-game regular season, fans are just as likely to prefer a 2-team post-season as a 24-team post season.

***

The NBA fans showed a similar split: 65% of fans prefer a 2-team post-season, after an 82-game regular season, while 57% of fans prefer a 24-team post-season after a 36-game regular season. The midpoint where fans are split down the middle we would infer as a 52-game regular season.

***

The NHL fans are much hungrier for the post-season, maybe lending to its history. At one point, they had 16 of 21 teams make the playoffs. As more teams have been added, the 16 became a mainstay.

So, 55% prefer a 2-team to a 24-team playoff with an 82-game schedule, while 63% prefer 24 to 2 with a 36 game schedule. Fans are split down the middle with an inferred 68-game regular season.

***

For Euro soccer fans, things are QUITE different. With a 38-game season (34 to 38 is the standard there), 73% prefer 2 teams. With an 18-game season, still 58% prefer 2 teams. Which logically makes no sense at all.

For example, suppose we construct a 38-game season such that the first 19 games is one game played against each of the other 19 teams in the league. Then, after that happens, the top 10 teams play one game against each other, while the bottom 10 teams play one game against each other. We’ve now constructed a 28-game regular season schedule.

And we add a provision that a win in the second half counts twice as much as a win in the first half. In other words, we get that playoff feel, but every team gets to play the same number of games. Wouldn’t THIS be preferred to stopping after 19 games, and simply awarding the championship to one of the top 2 teams?

***

The 9-team CFL fans were offered no playoffs at all, just award the Grey Cup to the top team after 18 games, or 8 of the 9 teams making the post-season. 59% preferred an auto Grey Cup. For a 12-game regular season, 54% preferred an 8 team post-season. The midpoint is a 14-game season.

Friday, December 20, 2019

NFL: How much more is a rushing yard worth compared to a passing yard?

Followup to part 2, and part 1.

If we treat successful passes as uniform from 6 to 16 yards, that gives us an average EPA of +0.851 (on +11 yards).  And if we assume 64% success rate, that means 36% of the time we get 0 yards (which is an EPA of -0.474. 

Our weighted average for passing therefore is 64% of +.851 and 36% of -.474 for an average of +0.374 points (on 7 yards).

Now, what would be the equivalent in passing yards to match the rushing yards?  That would be 38.1% successful passes, incredibly.  This is how it works out: 38.1% of +0.851 EPA and 61.9% of -0.474 gives us an average of +0.031 EPA (same as rushing), and an average yardage gain of +4.2 yards (compared to +4.0 for rushing).

In other words, while you get more bang for your buck for each rushing yard, it is BARELY more.  4 rushing yards = 4.2 passing yards.  And therefore, it is VERY fair to compare the overall rushing yards and passing yards per play (after turnover adjustments), at least if you look at 1st-and-10 situations.

Under these assumptions, and given this data.

So, what I'd like is for the aspiring saberists to use the actual rushing distribution and the passing distribution (aka, not uniform, and almost certainly closer to normal) to give us the better answer.  Given what I see in the data, it's extremely unlikely we'll see anything much different than what I've presented.

NFL: Is it better to be 1st-and-10 or 2nd-and-5?

?Given the data provided to me by aspiring saberist @alevine1986, that's pretty close to the breakeven point.

?

I put a callout, and Adam was generous enough to respond, by making use of NFLscrapR. Focus on the black dotted line, as that's the simple average of the other 5 lines.  That black line goes through the "5" in Yards Gained from Scrimmage.  (Data is limited as in the prior post to 1st-and-10.)

There's also the interesting and expected flat line right at the 10 yard point: the jump from 9 yards (0.76 Xpoints) to 12 yards (0.88 Xpoints) is a gain of only 0.12, which the 3 yards before that (6 to 9) is a gain of 0.64 points, while the 3 yards after that (12 to 15) is a gain of 0.29 points.  

So, we can say that the average yard is worth about 0.10 points (i.e., 10 yards per point, which is something we can easily figure out in many other ways), and then we have a "leverage" aspect to yards based on how many yards we toward that 1st down, and past that 1st down.  And roughly speaking, the Leverage Index (LI), given this data is about 0.4 when gaining 9 to 12 yards (and you need 10), and it's 3.0 when going from 8 to 9 yards.

I thought there was an issue with this data when so far away from the endzone (81 to 99 yards).  I thought that should be the flattest.  But now that  think about it:it's important because you don't want to turnover to your opponent in a favorable spot.  So, that's something I learned here as well.  The yards gained from 21 to 60 yards from the endzone are the least valuable.  And that's because you are in a good spot for a FG or a punt to push your opponent deep.

Fun stuff.

Wednesday, December 18, 2019

NFL: Should teams pass even more?

UPDATE: Thanks to @WhisperScrape for doing all the work.

?I put a call out to the Twitter world for the aspiring saberists. And a few people asked for my requirements.  These were the specs I laid out.

Here's what I'd like to see:

• limit the data to 1st 25 minutes of the 1st half and 1st 25 minutes of the second half (i.e., exclude last 5 minutes of each half)
• limit only to 1st-and-10 plays
• tag every play as an intended-pass or an intended-rush; count all QB runs, sacks or any other non-handoff play as intended-pass; so if we want to be more specific, it's nonhandoff v handoff plays
• break up the field into zones of 20 yards (so own 0 to 20, own 20 to 40, 40 to 40, opponent 20 to 40, opponent 0 to 20)... so that we can speak math, show the yardages as "yards to endzone": 0-20, 20-40, 40-60, 60-80, 80-100
• count the number of events, handoff v nonhandoff, and the average yardage gained
• the yardage gained include penalties, so we are looking at the difference in scrimmage line between that play and the next play (unless of course it's a TD, in which case it's just the actual yardage gained)
• break it up by offensive team (so 32 results)
• break it up by defensive team (so 32 results)
• Run it for 2019 season only.

Someone sent me the results within 24 hours, so here's how I aggregated it. I've asked them for permission to identify them, and I will when they assents(*). It is a simple average of 64 rows for each breakdown.

(*) Since they can now be used as a singular pronoun, does that mean that I can say they assents as opposed to they assent?

?

What is clear is that the redzone is definitely different, and clearly that has to be treated differently, which is what we expected.  Really, the next step is to see where to draw that line.  I just used 20 yards as the standard, but it could be 25 or 30. We also see some impact within your own 20.  The likely reason is that the defense is allowing the run, to keep the offense as deep as possible, and not let a successful pass play give them breathing room. Again, whether it's inside the 20 or inside the 10, that's for a future iteration of research.

We see from 40 to 80 yards to go, that's probably the most neutral area on the field.  With a pass play giving you 7 yards and a run giving you 4, the pass play is a huge winner.  However, we have to remember that in football, you get a reset in downs once you get 10 yards.  So, there's a bigger difference between a 9 yard and 11 yard gain than there is in an 11 and 13 yard gain.  Again, that's another future iteration for study.  That said, it's extremely unlikely that the expected point gain on 4 yards per run (on this area of the field) can match 7 yards per pass.  If it was 5 and 6 respectively, maybe that would be equivalent.  Indeed what we see inside the 20 (or maybe inside the 10) would likely represent that.

Another interesting result to me is that the % of pass plays on 1st and 10 are not very much linked to the spot on the field.  The overall average is 44%, with the 20 yard breakdowns as: 43%, 41%, 44%, 47%, 42%.  I'd tell you which order it is, but it doesn't seem to matter!  (I will tell you anyway, the order is from the redzone to the offense inside their own 20.  So the highpoint of 47% is with 60-80 yards to go.)  So, it's a little confusing to me that the yards per pass was not dependent on the frequency of passes.  Presumably, it has more to do with an expectation that it's intended short passes inside your own 20, since you are just trying to march the ball downfield a bit, rather than taking big risks on 1st and 10.  And maybe they SHOULD take bigger risks.  I dunno.  I should probably watch more football at this point.

The average yards per play was also very similar in your own 20 (5.5), 60-80 yards to go (5.6), 40-60 yards to go (5.4).  This also points to the idea that maybe we do have equilibrium.  After all, we see the shift in approach inside your own 20 shows a drop in passing yards per play and a gain in running yards per play.  But we're still at the same spot in terms of yards gained.  I really should watch more football now.

Hopefully, with the above specs and what our aspiring saberist has done gets us into the wading pool, and now someone can take this to the shallow end and wow us with more results.

And you can tell the sign of a good study when answering one question leads to two more questions.  And that's what we have here. Most people are happy coming to a conclusion, but that happiness is shortlived.  Because there are even more questions to give you even more contentment.  Thank you to our aspiring saberist!

Monday, July 29, 2019

We’re all Statheads; we just choose our own stats

"We're all Statheads; we just choose our own stats"

-- Cory Schwartz

I was reminded of what Cory likes to say when I made a flippant remark, in a not-so-subtle guise of a poll, to the point that hockey's plus/minus is better than totally useless.  I figured being better than totally useless was an easy bar for a baby to crawl over.  Unfortunately, a healthy one-third disagreed, and those who disagreed were more vocal about it.  Some like the usually loquacious MannyElk went with the direct "delete this".  CJ tried to be more nuanced. And everyone and his brother at EvolvingWild just disagreed.

Score Differential

In baseball, it's natural for us to look at team run differential, and make that the core to our metrics.  Indeed, that's the core to WAR found at Baseball Reference, extended down at the player level.

In hockey, you can follow a similar idea, look at goal differential, and make that the core to our metrics.  (And similar for basketball, football, soccer.  And while I know nothing about cricket, I'll say: cricket too.)  And naturally, if you are looking at it at the team level, you'd want the sum-of-the-parts to equal the whole.

Now, it's NOT NECESSARY that you apply the sum of parts theory.  After all, to do that, you'll have to decide how to handle Random Variation.  There's only so much you can identify at the player level, and so, there's going to be a gap in our knowledge.  Bill James for example in Win Shares simply plows through it, and insists on it.  I on the other hand am content to say "I dunno", and create a timing bucket.  Regardless though, the key point is that all the runs are accounted for.  They may not be accounted for at the PLAYER level (which Bill would insist upon), but at least I can account for the existence of all of them.

And the same would work in hockey.  If a team scores 4 goals and allows 2 goals, we should account for 4 goals scored and 2 allowed. And while we'd like to have all six goals assigned to players, I am content to say "I dunno", and create some sort of unknown bucket.  This could be timing, or random variation, or simply data that is too hard to assign to players.

If you do not do this, if you don't account for all the goals, then you are simply telling the reader: "trust me, I know what I'm doing, and it doesn't add up, because I don't need it to add up".  You can of course do this.  But you are creating an unncessary hurdle.  Rather, it's simpler to just acknowledge the gap.  In the above case, you may say a team scored 4 and allowed 2, but your process say the team is going to be assigned 2.7 goals scored and 3.2 goals allowed, because, "the process".  That's not the best way to sell something.

Extending Differentials

Now, goal differential is a core metric at the team level.  And extending it at the player level is also a core metric.  Hockey complicates things because of the man-advantage scenarios. And that players don't play with everyone.  And the number of goals is low to begin with.  Which is why we talk about adjustments.  This is common in baseball, where we can adjust our core metric, like say wOBA or ERA, based on the scoring environment or other influences.

Hockey's plus/minus is already in the currency we want for a core stat: goal differential.  However, there are other plus/minus stats you can do.  You can do it for all shots, which of course includes goals.  So as to not mix anything, I'll call goal differential as NetGoals.  And so we also have NetShots.  NetShots is of course at its core, NetGoals plus NetNongoalShots.  In other words, if you are going to praise NetShots and deride NetGoals, what you are saying is that NetNongoalShots is pivotal.  That including NetNongoalShots is what makes or break NetShots.  That relying on NetGoals is totally useless, even with adjustments.  And that is an untenable position.

Merging and Unraveling

You can also try to argue that since we have both NetGoals and NetNongoalShots, that we therefore no longer need to focus on them as components, that we can simply look at NetShots.  Or some sort of weighting of the two, but still, amalgamized into one metric.  This is like arguing that if you have wOBA, you don't need OBP.  Or you don't need K/PA.  Au contraire, the components are the key.  And that's because the weightings of the various components are not a given.  They are often necessary to keep them separate, because the weightings are dependent on the number of trials.

RBIs are totally useless if you already have wOBA and RE24.  That's because you can get to RBI through those two metrics.  But if you don't have RE24, then RBIs (and Runs Scored) do have some non-useless value.  They are not totally useless.  The timing of events is important.  And distinguishing between goals and non-goal-shots is important.  And how you distinguish between goals and non-goal-shots is not a constant.

The key thing that I follow in my metrics is "how".  How did this happen, why did this happen, how do we explain this happened.  I don't roll my stats up into one number to let it sit there and... sit there.  The metric has to be able to be unraveled back to its components.  And I have to be able to explain it all in english (or french if I'm feeling confident). That's how I construct my metrics.  You don't have to do it this way of course. The world is a big place.  

Monday, January 28, 2019

How do we know how many WAR to give out to nonpitchers and pitchers?  Or goalies?  Or QB?  Or?

?If you notice on Fangraphs, they hand out 57% of the WAR to nonpitchers and 43% to pitchers. This is actually the split that I determined some 15 years ago. Baseball Reference hands out at around 59/41, presumably based on a similar technique that Straight Arrow reader Rally Monkey came up with. I don't know how much Win Shares gives out, but I think it's around 64/36?

How did I come up with 57/43? We have to know the spread in TRUE TALENT. The problem is we don't actually know the spread, so we need to infer it. And we infer it based on observing what has actually happened, and removing the Random Variation that pollutes all observations. And when you go down that road, we end up with a standard deviation of a talent distribution that is roughly a ratio of 4:3 for nonpitchers and pitchers.

If you tried to do this for the NHL, the spread is going to be roughly 60/30/10 for forwards, defensemen, goalies.

I've never done it for the other sports. However, what you will typically find (not always, and not so strict) is that player salary is a decent approximation for the split. Again: not always; not so strict. But it's a decent guidepost. And where it deviates, then you will find a market inefficiency.

Friday, December 28, 2018

How to create WAR for any sport

?While WAR is wins above REPLACEMENT, the most important part of WAR is the comparison to AVERAGE. Indeed, the replacement step is both an after thought, and in some respects, unnecessary.

I'll use baseball and hockey as examples, but any sport will work the same way, whether basketball, volleyball, or cricket.

What you want to do is measure all the aspects of a player's performance relative to the league average. Not for the position, but the player, unless that position is very (VERY) distinct, like pitcher in baseball or goalie in hockey. Infield/outfield, and defenseman/forward are not distinct enough. Catcher might be, but we'll let that go for this thread.

So, figure out all the components. Hitting, running, fielding, pitching, scoring, passing, checking. As long as you got all the components, you are good. Measure the player however you want to, and compare to the league average. 

You want to measure in the currency that you can measure in, meaning bases, outs, runs, goals. And eventually, you want to convert into wins. For baseball you can use a standard 10:1 runs to win converter and in hockey 6:1 goals to wins. But, we can get into another thread how to get it more dynamic.

Once you have all that, you will have an Individualized Won-Loss Record for a player, or what I call The Indis. You simply add it up. For hockey, it might look like this:

• 2.0 wins, 0.5 losses, scoring
• 1.5 wins, 1.0 losses, passing
• 0.5 wins, 1.0 losses, checking
• 0.5 wins, 0.5 losses, positioning

You'd probably want to break it up into EV, PP, PK, and if you have more components, then by all means, include those.

Anyway, so now you have The Indis of:

• 4.5 wins, 3.0 losses, total

And you can stop right here. Notice I haven't even talked about replacement level. Like I said: after thought. But people love lists and single dimensions, and so, we need a way to convert thatto a single dimension.

Replacement level in MLB is around .300 and probably .250 or .200 in NHL. That too is yet another thread. For the sake of illustration, I'll use .333.

• 4.5 wins, 3.0 losses, total
• 2.5 wins, 5.0 losses, replacement level for 7.5 individualized "games"

=========

• +2 wins above replacement

That's how it works. This is the framework. Don't try to get cute and try to create a "offense above replacement". You will be wrong. Not as a matter of opinion, but a matter of fact. You CAN say "offense above the offense generated by a replacement level PLAYER". That's as far as you can take it.

But like I said, anything after The Indis is an after thought.

If there is one thing I did wrong when I rolled out WAR on my blog some 12 years ago was that I did not pause at The Indis level, and went straight to WAR. That's because that's what I needed at the time. Had I known WAR would take off the way it did, then I would have ensured that intermediate step would be more forceful. And it would reflect the replacement step is just a secondary optional step.

The replacement step IS required if comparing a position player to a pitcher, or a skater to a goalie, or two players of uneven playing time, like a starting pitcher and relief pitcher, or simply an injured player to a full time player. THEN we need it. Because we eventually want to translate that into some sort of dollar value, or any kind of value.

Have fun!

***

UPDATE in response to a comment below:

I literally spent 5 minutes writing that, so it was just a stream of consciousness how-to. So, yes, there’s about two hours worth of things I didn’t write!

But to your point: what you want to do is create “game spaces”.  Let me explain it in hockey and in baseball.

In hockey, about 10% of the game space goes to goalies, 30% to defensemen and 60% to forwards.  With 82 games, you assign 8.2 games to G, 24.6 to D, and 49.2 to F.  For each player at each position, you give him his share of those game spaces based on how much ice time he had.  It gets a bit more complicated because of EV, PP, PK.

In baseball, about 4/7ths of the game space goes to nonpitchers and 3/7ths to pitchers.  For nonpitchers you give them their share based on PA, though things get a bit complicated with subs (and DH).  For pitchers you base it on innings, or more accurately, leveraged-innings.

Basketball is the easiest, because it’s just a pure share by court time, no positional restrictions.  Or at least I don’t think so.  I don’t follow basketball.

Sunday, June 11, 2017

What is the true home site advantage of each sports team?

?I don't know what the true answer is yet.  But my expectation (very strong expectation for whatever that is worth) is that it is far tighter in NFL and NBA than in MLB and NHL.

What do I mean by that?  Well, each NBA game tells you a great deal more about the teams than each NHL game.  So, if we suspect that the Celtics have a .620 home site advantage and the Bruins have a .550 home site advantage, then we'd guess something like .610-.630 for Celtics and .525-.575 for Bruins.

Now, if we bring in the Patriots, we know more on a per-game basis for the Patriots home site advantage than the Celtics.  However, because we have so many more NBA games, our uncertainty level will get reduced far faster with NBA than NFL. 

More to come as I try to compose my thoughts on this matter...

Friday, January 20, 2017

Phil v ELO, men v women chess

?Phil is at it again, this time going through the obvious incompatibilitiy with NCAA v NBA (making you wonder why is he even bothering, but is actually a foreshadowing) to then look at men v women chess ratings.

I'll offer Phil even more relevant cases: MLB AL v NL, 2005-present (but since I cherry picked 2005, you should start in 2004).  You can look at NBA West v East.  And closer to home: CFL West v East, and NHL West v East.

It offers a good look at the "leakage" issue that Phil brings up, especially since inter-conference games are much fewer in MLB than NBA.  IIRC, I think I looked at the CFL, and it seemed that the proportion of games was just about right, such that their win% represented their true talent levels.  I think.

Anyway, would love to see the Phil-touch applied here.

Wednesday, March 23, 2016

How the fielding shift in baseball plays out in football

?Well, well, well.  The NFL is changing the touchback rule on kickoff so that it goes back to the 25 yard line.  Since the breakeven point is right around the 20 yard line, the returning team is HIGHLY incentivized to do a touchback.  You can't just automatically give one side 5 yards and expect nothing to change.  Well, they will change.  The kicking team is now incentivized to kick it short enough to not allow a touchback to begin with.

See, if the touchback was the 10 yard line, the kicker would simply do one thing: kick it as hard as he can.  If the touchback was the 40 yard line, the kicker would simply do one thing: make the trajectory a high enough launch angle so that distance is "sacrificed", a sacrifice that benefits the kicker.  At 20 yards, there was harmony.

How does this apply to fielding shifts in baseball?  Well, if a hitter is smart, he (a) wants the fielders all to one side and (b) he would continually poke the ball or bunt the ball to the open side.  But if the fielders see the batter adjusting, the fielders will suddenly play defense normally.  In which case the huge advantage for the batter disappears.  Which forces the batter to now pull the ball more, forcing the fielders to shift more, which allows the batter to not pull as much... until we have harmony.  The batter therefore doesn't want to do this too much.  He has to hit suboptimally (not always bunt) to keep the fielders to continue to play suboptimally!  It's just a matter of how suboptimally the hitter is to maintain the oppositions suboptimization.  Weird, I know.

Indeed, the NFL can make the rule so that the defense decides on what the touchback line is!  A team can say "touchback to 40", in which case the kicker will "bunt" it (i.e., high short kick).  A team can say "touchback to 20", in which case the kicker will "pull" it (long straight kick).  Basically, letting the defense call the touchback line is just like fielders positioning themselves on a baseball diamond!

Monday, February 01, 2016

Are parents rolling the dice on their children’s health when it comes to football?

Football in high school is pretty big in this one town near where I live.  I've been thinking that because of concussion news, that simply by attrition, football in high school would dwindle.  But in this one town, it's as big as ever, if not bigger.  "Why", I asked someone there.

Scholarships.  Simply put, the parents can't afford to send their kids to the college they want to, but they think they can get them in through an athletic scholarship.  In effect, the parents are signing up their non-adult children to high school football so that they might luck into a scholarship.

There are so many levels of wrong to this.  Take away the chance at a scholarship, and how many parents would not allow their kids to play football?  Would participation drop by half?  Three-fourths?  90%?  Or maybe it's just 10%?

I don't know.  But let me ask this: what if boxing was big?  And scholarships for boxing was big?  How many parents would roll the dice on the health of their kids?

Tuesday, January 12, 2016

Tango’s Lab: Football Game using Playing Cards

So, I have this thought, and football is a great game for it.

Suppose that you have two players, and each one draws five cards.  The reds (diamonds, hearts) are good for running.  Get it, Red, Running.  If the offense throws a Red, that means they are running.  If the defense throws a Red, that means they're trying to stop the run.  Black is passing.  If the offense throws a Black, that means they are passing.  If the defense throws a Red, that means, well, that's bad news for the defense. 

After every card that is thrown, you draw another, so you always have five cards in your hand.

***

Here therefore is how the game works:

Read More

Tuesday, September 22, 2015

Arguing to argue, but not to conclude anything

?I liken the discussion of comparing players decades apart as basically just everyone yapping, without really trying to get to an answer.  Joe lays out the foundation for Bryce v Ted Williams and I chimed in a thing or two.

It's interesting how you get these discussions in baseball, but you don't get them in hockey or football.  Howie Morenz may have been voted the #1 player of 1901-1950, but we all understand that the game is far different today.  And at some point, even Bobby Orr and Wayne Gretzky will get relegated to their own era, especially when all players in a few decades will weigh at least 200 pounds.

It may be fun, but that's pretty much all you can do with these discussions: have fun.

Wednesday, September 16, 2015

NFL Justice

?Interesting article that ends with:

...the difficult questions left in its wake about the right of any employer to access restricted information about an employee’s actions outside the workplace. As the calendar turned to the NFL season once again, Goodell was able to convince America that NFL Justice was real. That’s all that ever mattered.

Tuesday, September 15, 2015

What happens when a rookie football fan liveblogs an NFL game?

?Here's the report, straight from Australia.  Have a drink every time you read the word "break" or "timeout".

Monday, September 14, 2015

Can tackle football in high school survive?

?I am pretty much dumbfounded that this high-profile a sport tied with concussions can exist in high school.  Isn't it just one lawsuit away from being eradicated?  I presume there used to be high school boxing and I also presume it no longer exists? 

In Canada, we don't have this issue because the leagues are NOT tied in to the high school.  Which would seem to be the path that's going to happen in USA.  My question: why hasn't it happened already, and when will it happen?

Now, as for college: because we are dealing with adults, it would have a lesser burden to consider.  But still, once the high school domino falls, the college football program would be in jeopardy(*) as well, wouldn't it?

(*) I always spell it as jeapordy initially, and the spell-checker saves me. I think my spelling is more consistent with the pronunciation.

Thursday, August 13, 2015

How are CFL kickers performing on the new single point after-TD kick rule?

?The CFL adopted a rule that makes the point after-TD kick a 32 yard kick.  (The NFL will do the same.) 

The conversion rate for CFL kickers is 87%.  We obviously expected it to be lower than the high-90 conversion rate.  Should we have expected it to be this low?

If we look at those same 9 kickers during FG attempts of 8 to 49 yards, and their conversion rate is 88%.  And before you think they must be doing great at 8 to 31 yards and poorly at 33 to 49 yards, think again.  The 9 principal kickers are 28 for 31 at 40-49 yards, for a conversion rate of 90%, and 78 for 89 at 8-39 yards or 88%.

If anything, the real interest here is that it seems that distance is not an issue to a CFL kicker until you get to around 50+ yards.

This would suggest that the next rule would be to narrow the uprights.

Sunday, July 05, 2015

Project for aspiring saberists in NHL, NBA, NFL, MLB

?1. For each sport, figure out the median age of players who sign multi-year deals in free agency over the last 30 years (year by year)

2. Figure out the median age of all players

Friday, May 29, 2015

Which major league has the most close-minded fans?

?MLB, NFL, NHL, NBA?  Pick 1, without commentary.