Which NFL First Round Pick Was Happiest to be Drafted?
The NFL Draft kicked off last night and certainly lived up to the hype with shocking picks and trades galore. For 13 lucky young players hanging out in the prospect green room in Detroit, they got to experience the thrill of hearing their name called up close and in person. While it was a dream come true to join the ranks of NFL players for all of those prospects, some were likely happier to be selected by the team that took them than others. We at VegasInsider used a machine learning model to analyze photos of all 13 of those draftees in attendance holding up their new jerseys to see who was the happiest to be drafted, as well as analyze the other emotions shown on their faces. Below you can find our findings and methodology (including the photos analyzed).
Before we dive in on who was most excited to be picked Thursday night, you can find the best offers on wagers regarding how these rookies will perform this season by using our bet365 bonus code!
Who Was The Happiest Draftee?
Unsurprisingly, most of last night’s draftees were overwhelmingly excited to live out their NFL dreams. Nobody was happier than 3rd overall pick Drake Maye though. The New England Patriots new quarterback of the future was the only prospect with a happiness score of 100. Maye showed no emotion other than pure happiness as he proudly displayed his new jersey on the stage. Rome Odunze, the newest Chicago Bear, just barely missed out on a perfect score, registering a happiness score of 99.99.
The face can show a lot of emotions at once, so it’s no surprise that six different prospects registered a happiness score of 94 or higher, while also showing flashes of others. Terrion Arnold, Darius Robinson, and Brian Thomas Jr. Each scored very highly in happiness but also showed some neutrality on their face, or in the case of Arnold, interestingly, fear (in his defense, he had just been selected by the Detroit Lions, the host of this years draft, and was standing in front of what seemed like their entire fan base, which could be slightly intimidating).
Marvin Harrison Jr. had a happiness score over 94 with his second most notable emotion being anger, which had a score of 4.51. Perhaps the first receiver off the board was unhappy that he had to wait until the fourth pick to hear his name called. Jayden Daniels had a nearly identical happiness score to Harrison, but his second highest score was surprise. After Daniels and the Commanders publicly squabbled over the team’s decision to host multiple passers during the Heisman winners visit with Washington perhaps he was surprised the NFC East team made him the pick anyway.
Caleb Williams, the consensus top pick in this year’s draft for much of the year, also showed a fair amount of surprise, which in of itself is surprising. Williams' 9.21 surprise score was the second highest for that emotion. It’s hard to imagine the #1 overall pick was shocked to be taken by the Bears, a team that was all in on him well before they were on the clock last night. Perhaps he was simply taken aback by the response he received in the home of his new rivals, the Detroit Lions.
Laiatu Latu, the first defensive player selected this year, was a ball of overall emotions. He was the only draftee to score over 1.0 for every emotion as well as the only one to not have any single emotion register a score over 50. His most prominent emotion was still happiness though, with a score of 42.6.
A few prospects, however, did not seem happy to be holding up their jerseys on draft night. The newest Philadelphia Eagle Quinyon Mitchell registered a happiness score of just .08, but an anger score of 99.14! It’s hard to imagine the former All-MAC star was angry to be selected by a possible Super Bowl contender, and Mitchell’s expression seemed pretty consistent from when he arrived at the green room all the way through his post pick interview. Maybe he’s just a mean-mugged defensive player who looks angry all the time. If that’s the case, he could become a fan favorite in Philly in a hurry.
Two prospects did not seem happy at all to be selected, registering a happiness score of 0. Our analysis shows Malik Nabers was overwhelmingly surprised, which had a score of 98.18 for the New York Giants newest offensive weapon. Maybe he had heard all the JJ McCarthy-Giants rumors as well and bought into them. Dallas Turner, the pass rusher who struck fear into the hearts of quarterbacks during his time at Alabama, himself showed fear as he accepted his new jersey on stage. The newest Minnesota Viking had a fear score of 94.43 according to our analysis. Maybe standing in front of thousands of his newest rival fans intimidated this years 17th overall pick.
Draftee | Dominant Emotion | Angry | Fear | Happy | Sad | Surprise | Neutral |
Drake Maye | Happy | 0.00 | 0.00 | 100.00 | 0.00 | 0.00 | 0.00 |
Rome Odunze | Happy | 0.00 | 0.00 | 99.99 | 0.00 | 0.00 | 0.01 |
Terrion Arnold | Happy | 0.00 | 1.13 | 98.73 | 0.00 | 0.00 | 0.14 |
Darius Robinson | Happy | 0.00 | 0.01 | 96.84 | 0.01 | 0.00 | 3.14 |
Brian Thomas Jr | Happy | 0.00 | 0.00 | 96.64 | 0.00 | 0.00 | 3.36 |
Marvin Harrison Jr | Happy | 4.51 | 0.29 | 94.60 | 0.59 | 0.00 | 0.02 |
Jayden Daniels | Happy | 0.83 | 0.01 | 94.46 | 0.85 | 2.71 | 1.14 |
Caleb Williams | Happy | 0.11 | 1.28 | 89.37 | 0.02 | 9.21 | 0.01 |
JC Latham | Happy | 5.20 | 0.20 | 76.40 | 3.09 | 0.00 | 15.11 |
Laiatu Latu | Happy | 1.09 | 11.36 | 42.60 | 1.06 | 1.69 | 42.19 |
Quinyon Mitchell | Angry | 99.14 | 0.28 | 0.08 | 0.49 | 0.00 | 0.00 |
Malik Nabers | Surprise | 0.19 | 1.62 | 0.00 | 0.01 | 98.18 | 0.00 |
Dallas Turner | Fear | 1.25 | 94.43 | 0.00 | 4.32 | 0.00 | 0.00 |
Methodology
Photos of NFL draft attendees were gathered immediately following the conclusion of the first round. All photos were public and official shots of the draftee on stage holding up their new jersey. All photos used in this article were the pictures analyzed. The rest of the photos used can be seen below.
To enhance the accuracy of emotion analysis, the images undergo a preprocessing phase where external objects and background distractions are removed. The focus is narrowed down exclusively to the players’ faces, using cropping and other image manipulation techniques to isolate facial features critical for accurate emotion detection. The core of this project utilizes the VGG Face Analysis Model integrated within the DeepFace framework to process the isolated facial images. This powerful model analyzes each face to detect and interpret various emotional states, categorizing them into predefined emotional responses such as happiness, sadness, surprise, anger, and others. The output from the machine learning model is then used to conduct a detailed analysis of the emotional states of the players. This includes quantifying the intensity of each emotion and determining the dominant emotional response for each player.
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