8/23:
Onside recovery -> TD -> ~5% chance of occurring

Onside Fail -> Force 3+Out -> TD -> ~3.68% chance of occurring
9/23: Had LaFleur elected to go for it on 4th and 8, there were a lot more directions the game could’ve gone so let’s take a look:
10/23: #NFL metrics suggested that #GoPackGo had a 21.2% chance of converting on 4th and goal from the 8. They then would’ve had a 46.8% chance at converting the necessary 2pt. conversion. Even in this scenario, the #GoBucs would’ve had ~2:00 and 3 timeouts to manufacture points.
11/23: Failing to convert 4th down would have put #GoPackGo in a similar situation as tweet 5 above, with slightly better odds since their opponent starting field position would have been around the -10 yard line.
12/23: Their chance of forcing a 3+Out (47%) is similar, but their chance of scoring is better due to improved field position. In this scenario, they would also need a 2pt. conversion following a TD. I assumed a 12.1% TD+2pt. rate after a 3+Out.
13/23: If #GoPackGo would have converted the 4th down and FAILED the 2pt. conversion, their path to winning was similar to what was discussed above in tweets 3-7. They would’ve had slightly better odds to score since they only would’ve needed a FG to win, rather than a TD.
14/23: I assumed 65% FG conversion rate off of an onside recovery (v. 50% TD rate) or a 15.3% FG conversion rate off of a 3+out (v. 8.7% TD rate)
15/23: Had #GoPackGo converted 4th down AND the 2pt. (9.92% rate), there would have still needed to stop #GoBucs to either force OT or have a chance to win in regulation. For simplicity I assumed 50/50 on winning in OT, and the same 15.3% FG rate for points after stopping #GoBucs
16/23: #GoPackGo Winning Paths with an attempted 4th down:
Convert -> Convert 2pt -> Stop #GoBucs -> Score or Win in OT (~3.47%)

Convert -> Fail 2pt -> Onside Attempt (paths described above) -> Score FG to win (1.463%)

Fail 4th -> 3+Out -> Tie it -> Win in OT (2.24%)
17/23: I also considered a scenario where #GoPackGo converted both 4th down AND the 2pt conversion, then #GoBucs scored to take the lead back. The only win path I considered for #GoPackGo here would have been to match the #GoBucs score and win in OT (0.216%).
18/23: Summing all of the “Go for It” scenarios yields a 7.389% win chance for #GoPackGo versus the “Kick It” decision’s 8.68% win chance.
19/23: Numbers and data should be used to challenge the norm, but when it comes to in-game decision making, external factors HAVE to be considered (i.e. willingly giving the ball back to TB12). The best #NFL coaches have the ability to balance both to help their team win games.
20/23: The reality is Kicking the FG last night did improve #GoPackGo ‘s chances of winning, but not by much. When you’re down late against #GoBucs with a chance at the SB on the line, take a chance with your Franchise QB rather than trying to stop theirs.
21/23: This is just a quick and rough interpretation of a small amount of the work that goes into the “decision cards” often referenced by broadcasters. No exact scenario can ever be predicted or replicated, which is why a good statistics background is key.
22/23: #Analytics can help a team win 8/100 times instead of 7/100 times, but in-game decisions only have a 1-time chance at winning; that is why understanding statistics and having a strong analytical team is becoming an important factor for winning in the #NFL .
23/23: All play-by-play data courtesy of @nflfastr. Thanks for reading!

cc: @SharpFootball @EBoKnowss @coachmo4040 @Stat_Ron @mrcaseb
You can follow @drewshay15.
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