anyone have ideas or thoughts on football analytics when it comes to judging football talent and how it’s done?
I think it might look like this:
HC says to GM and personnel and computer guys : I want a solid RB as a tough short yardage guy who’s reliable to back up and complement our starter. Can you guys tell me who’s available in FA who rates high in the following. I am not looking for youth here or potential. I amy looking at now. For instance how does CJ Gable rate here.
Fumbles lost %
% of carryies at -1 yard : (for a loss)
%of carries for 4 yards >
% of receptions VS catchables:
% of TD vs Carries
% of games lost to injuries
% of effective blocks enabling QB to gain 2/10 second more
Run appropriate RBs through this prism after your film work and tell me who rates highly in this FA group"
Analytics is a fancy word now for crunching numbers and tendancies for the computer age that coaches used to do with film work and taking notes and using a calculator. Thats just what it seems to be to me bit idk.
Since you bring up CJ Cable. When Kent Austin brought him into the CFL in Hamilton. He was really not used much to actually run the ball but actually he was a great blocker and receiver out of the backfield. And Condell used other ways to run the ball like bubble screens, Jet Sweeps, and a wildcat package that was put in for Masoli at the time.
In that in mind i look back to the 1970s in the NFL.
Tom Landry of Dallas & Chuck Knoll of the steelers come to mind.
For Landry when they drafted Tony Dorsett. He found a journeyman RB named Preston Pearson who he would bring in for 3rd and long as a pass catching RB to save hits on the smaller RB Dorsett.
He also had Preston in as a single set back & pulled the FB and brought in an extra 3rd receiver in Butch Johnson into the slot. So Preston also stayed in to block blitzing LBs.
Chuck Knoll did very much the same. Rocky Blier was the FB and Franco Harris was the tailback. In the same 3rd and long passing situations. Knoll would take Harris out. Bring in Jim Smith as the 3rd receiver in the slot. Rocky Blier would stay in as the single set back not just to stay in and block but was also a great receiver out of the backfield. Franco i remember at the time would also take alot of heat for stepping out of Bounce to avoid hits.
But in both cases with Landry & Knoll (with Harris stepping out of Bounce)
But it was all to keep their 1,000 yard running backs to from taking extra hits to keep them fresh and healthy for the season as well as extending their careers longer.
Remember during that period in the NFL they went from 14 game to 16 game seasons.
And the Cowboys & the steelers at that time appeared in alot of super bowls and went deeper into the playoffs more than most teams to conference finals when not making the super Bowl.
Is that early analytics?
Many moons ago I remember playing and because we were taught to hit low to make the tackle and to always make sure we were lower than the guy hanging onto the ball . BUT Certain running backs knew to chop their feet high . They were not the fastest because that style is different unorthodox .
Some guys were naturally gifted as fast and when they got space they ran fast .They hit the gap at the right time and boom they are gone . Quick acceleration like a sprinter .
Then there were guys who can make you miss in a closet . The quick high step .
The running style did that . They were not the fastest they just ran that high step style and so when you leaned to tackle they broke out .
You needed to tackle higher which is against the doctrine your taught .
How do you calculate that properly ? Tackle high you made your stop . You just better remember to do that with that type of back . Tackle low and the guys running by you .
Then change up for the regular running back so you can stick them and possibly knock the ball loose . Go high on them and they brush you off with a dip of the shoulder . So as a defender you better look at the back and make that physical adjustment to your tackling style .
I think baseball is best suited for analytics because of the size of any given set of data. There are so many games, so many at bats and so on.
Hockey and basketball probably come second with their 82 game seasons. Analytics are probably also useful in soccer where pro clubs play 40 or 50 matches per year.
Football is at a disadvantage for the use of analytics namely because the sample sizes are so small and the career lengths are generally short. By the time there is appreciable data on any given player, they’re usually retired.
I agree. It wasn’t called analytics until recently.
But you always here in MLB how every team has a book on each player. Hitters have a book on every pitcher knowing what pitches they throw and when they will likely throw them depending on the count etc.
Pitchers and catchers the same with hitters. Which pitches to throw them and when to throw them.
Baseball is well suited to analytics because it is static, meaning on every pitch all players are in position from the start of the pitching motion, so the outfield can be moved around, infield in, pitchout, etc. before a pitch is thrown.
CFL has pretty much unlimited motion except the line on offence and Defence can move at will.
CFL Football is more on tendencies, but analytics still plays a role
Well I guess that analytics is here to stay. With a computer program churning out info on data that was entered.
But your still going to need a football guy to read it and how to use it in an actual game